{ "$schema": "https://ui.shadcn.com/schema/registry-item.json", "name": "ultra-chatbot-agent", "title": "Ultra Chatbot Agent", "description": "A complete AI SDK application-shape agent workspace with persistent chat, resumable streams, documents, uploads, RAG, MCP, research reports, and gated sandbox tools.", "dependencies": [ "@ai-sdk/mcp", "@ai-sdk/openai", "@ai-sdk/react", "@base-ui/react", "@modelcontextprotocol/sdk", "@neondatabase/serverless", "@phosphor-icons/react", "@vercel/blob", "@vercel/sandbox", "ai", "class-variance-authority", "drizzle-orm", "ioredis", "lucide-react", "pdfjs-dist", "resumable-stream", "server-only", "zod" ], "registryDependencies": [ "utils", "alert-dialog", "badge", "breadcrumb", "button", "card", "dialog", "dropdown-menu", "separator", "skeleton", "spinner", "textarea", "tooltip", "https://elements.ai-sdk.dev/api/registry/attachments.json", "https://elements.ai-sdk.dev/api/registry/code-block.json", "https://elements.ai-sdk.dev/api/registry/confirmation.json", "https://elements.ai-sdk.dev/api/registry/conversation.json", "https://elements.ai-sdk.dev/api/registry/message.json", "https://elements.ai-sdk.dev/api/registry/model-selector.json", "https://elements.ai-sdk.dev/api/registry/reasoning.json", "https://elements.ai-sdk.dev/api/registry/shimmer.json", "https://elements.ai-sdk.dev/api/registry/sources.json", "https://elements.ai-sdk.dev/api/registry/suggestion.json", "https://elements.ai-sdk.dev/api/registry/tool.json" ], "files": [ { "path": "registry/ultra-chatbot-agent/.agents/skills/grill-with-docs/ADR-FORMAT.md", "content": "# ADR Format\n\nADRs live in `docs/adr/` and use sequential numbering: `0001-slug.md`, `0002-slug.md`, etc.\n\nCreate the `docs/adr/` directory lazily — only when the first ADR is needed.\n\n## Template\n\n```md\n# {Short title of the decision}\n\n{1-3 sentences: what's the context, what did we decide, and why.}\n```\n\nThat's it. An ADR can be a single paragraph. The value is in recording *that* a decision was made and *why* — not in filling out sections.\n\n## Optional sections\n\nOnly include these when they add genuine value. Most ADRs won't need them.\n\n- **Status** frontmatter (`proposed | accepted | deprecated | superseded by ADR-NNNN`) — useful when decisions are revisited\n- **Considered Options** — only when the rejected alternatives are worth remembering\n- **Consequences** — only when non-obvious downstream effects need to be called out\n\n## Numbering\n\nScan `docs/adr/` for the highest existing number and increment by one.\n\n## When to offer an ADR\n\nAll three of these must be true:\n\n1. **Hard to reverse** — the cost of changing your mind later is meaningful\n2. **Surprising without context** — a future reader will look at the code and wonder \"why on earth did they do it this way?\"\n3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons\n\nIf a decision is easy to reverse, skip it — you'll just reverse it. If it's not surprising, nobody will wonder why. If there was no real alternative, there's nothing to record beyond \"we did the obvious thing.\"\n\n### What qualifies\n\n- **Architectural shape.** \"We're using a monorepo.\" \"The write model is event-sourced, the read model is projected into Postgres.\"\n- **Integration patterns between contexts.** \"Ordering and Billing communicate via domain events, not synchronous HTTP.\"\n- **Technology choices that carry lock-in.** Database, message bus, auth provider, deployment target. Not every library — just the ones that would take a quarter to swap out.\n- **Boundary and scope decisions.** \"Customer data is owned by the Customer context; other contexts reference it by ID only.\" The explicit no-s are as valuable as the yes-s.\n- **Deliberate deviations from the obvious path.** \"We're using manual SQL instead of an ORM because X.\" Anything where a reasonable reader would assume the opposite. These stop the next engineer from \"fixing\" something that was deliberate.\n- **Constraints not visible in the code.** \"We can't use AWS because of compliance requirements.\" \"Response times must be under 200ms because of the partner API contract.\"\n- **Rejected alternatives when the rejection is non-obvious.** If you considered GraphQL and picked REST for subtle reasons, record it — otherwise someone will suggest GraphQL again in six months.\n", "type": "registry:file", "target": ".agents/skills/grill-with-docs/ADR-FORMAT.md" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/grill-with-docs/CONTEXT-FORMAT.md", "content": "# CONTEXT.md Format\n\n## Structure\n\n```md\n# {Context Name}\n\n{One or two sentence description of what this context is and why it exists.}\n\n## Language\n\n**Order**:\n{A one or two sentence description of the term}\n_Avoid_: Purchase, transaction\n\n**Invoice**:\nA request for payment sent to a customer after delivery.\n_Avoid_: Bill, payment request\n\n**Customer**:\nA person or organization that places orders.\n_Avoid_: Client, buyer, account\n```\n\n## Rules\n\n- **Be opinionated.** When multiple words exist for the same concept, pick the best one and list the others as aliases to avoid.\n- **Flag conflicts explicitly.** If a term is used ambiguously, call it out in \"Flagged ambiguities\" with a clear resolution.\n- **Keep definitions tight.** One or two sentences max. Define what it IS, not what it does.\n- **Show relationships.** Use bold term names and express cardinality where obvious.\n- **Only include terms specific to this project's context.** General programming concepts (timeouts, error types, utility patterns) don't belong even if the project uses them extensively. Before adding a term, ask: is this a concept unique to this context, or a general programming concept? Only the former belongs.\n- **Group terms under subheadings** when natural clusters emerge. If all terms belong to a single cohesive area, a flat list is fine.\n- **Write an example dialogue.** A conversation between a dev and a domain expert that demonstrates how the terms interact naturally and clarifies boundaries between related concepts.\n\n## Single vs multi-context repos\n\n**Single context (most repos):** One `CONTEXT.md` at the repo root.\n\n**Multiple contexts:** A `CONTEXT-MAP.md` at the repo root lists the contexts, where they live, and how they relate to each other:\n\n```md\n# Context Map\n\n## Contexts\n\n- [Ordering](./src/ordering/CONTEXT.md) — receives and tracks customer orders\n- [Billing](./src/billing/CONTEXT.md) — generates invoices and processes payments\n- [Fulfillment](./src/fulfillment/CONTEXT.md) — manages warehouse picking and shipping\n\n## Relationships\n\n- **Ordering → Fulfillment**: Ordering emits `OrderPlaced` events; Fulfillment consumes them to start picking\n- **Fulfillment → Billing**: Fulfillment emits `ShipmentDispatched` events; Billing consumes them to generate invoices\n- **Ordering ↔ Billing**: Shared types for `CustomerId` and `Money`\n```\n\nThe skill infers which structure applies:\n\n- If `CONTEXT-MAP.md` exists, read it to find contexts\n- If only a root `CONTEXT.md` exists, single context\n- If neither exists, create a root `CONTEXT.md` lazily when the first term is resolved\n\nWhen multiple contexts exist, infer which one the current topic relates to. If unclear, ask.\n", "type": "registry:file", "target": ".agents/skills/grill-with-docs/CONTEXT-FORMAT.md" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/grill-with-docs/SKILL.md", "content": "---\nname: grill-with-docs\ndescription: Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.\n---\n\n\n\nInterview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.\n\nAsk the questions one at a time, waiting for feedback on each question before continuing.\n\nIf a question can be answered by exploring the codebase, explore the codebase instead.\n\n\n\n\n\n## Domain awareness\n\nDuring codebase exploration, also look for existing documentation:\n\n### File structure\n\nMost repos have a single context:\n\n```\n/\n├── CONTEXT.md\n├── docs/\n│ └── adr/\n│ ├── 0001-event-sourced-orders.md\n│ └── 0002-postgres-for-write-model.md\n└── src/\n```\n\nIf a `CONTEXT-MAP.md` exists at the root, the repo has multiple contexts. The map points to where each one lives:\n\n```\n/\n├── CONTEXT-MAP.md\n├── docs/\n│ └── adr/ ← system-wide decisions\n├── src/\n│ ├── ordering/\n│ │ ├── CONTEXT.md\n│ │ └── docs/adr/ ← context-specific decisions\n│ └── billing/\n│ ├── CONTEXT.md\n│ └── docs/adr/\n```\n\nCreate files lazily — only when you have something to write. If no `CONTEXT.md` exists, create one when the first term is resolved. If no `docs/adr/` exists, create it when the first ADR is needed.\n\n## During the session\n\n### Challenge against the glossary\n\nWhen the user uses a term that conflicts with the existing language in `CONTEXT.md`, call it out immediately. \"Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?\"\n\n### Sharpen fuzzy language\n\nWhen the user uses vague or overloaded terms, propose a precise canonical term. \"You're saying 'account' — do you mean the Customer or the User? Those are different things.\"\n\n### Discuss concrete scenarios\n\nWhen domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.\n\n### Cross-reference with code\n\nWhen the user states how something works, check whether the code agrees. If you find a contradiction, surface it: \"Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?\"\n\n### Update CONTEXT.md inline\n\nWhen a term is resolved, update `CONTEXT.md` right there. Don't batch these up — capture them as they happen. Use the format in [CONTEXT-FORMAT.md](./CONTEXT-FORMAT.md).\n\n`CONTEXT.md` should be totally devoid of implementation details. Do not treat `CONTEXT.md` as a spec, a scratch pad, or a repository for implementation decisions. It is a glossary and nothing else.\n\n### Offer ADRs sparingly\n\nOnly offer to create an ADR when all three are true:\n\n1. **Hard to reverse** — the cost of changing your mind later is meaningful\n2. **Surprising without context** — a future reader will wonder \"why did they do it this way?\"\n3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons\n\nIf any of the three is missing, skip the ADR. Use the format in [ADR-FORMAT.md](./ADR-FORMAT.md).\n\n\n", "type": "registry:file", "target": ".agents/skills/grill-with-docs/SKILL.md" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/agents/openai.yaml", "content": "interface:\n display_name: \"Skill Creator\"\n short_description: \"Create or update a skill\"\n icon_small: \"./assets/skill-creator-small.svg\"\n icon_large: \"./assets/skill-creator.png\"\n", "type": "registry:file", "target": ".agents/skills/skill-creator/agents/openai.yaml" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/assets/skill-creator-small.svg", "content": "\n \n\n", "type": "registry:file", "target": ".agents/skills/skill-creator/assets/skill-creator-small.svg" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/assets/skill-creator.png", "content": "�PNG\r\n\u001a\n\u0000\u0000\u0000\rIHDR\u0000\u0000\u0000d\u0000\u0000\u0000d\b\u0006\u0000\u0000\u0000p�T\u0000\u0000\u0000\tpHYs\u0000\u0000\u000b\u0013\u0000\u0000\u000b\u0013\u0001\u0000��\u0018\u0000\u0000\u0000\u0001sRGB\u0000��\u001c�\u0000\u0000\u0000\u0004gAMA\u0000\u0000��\u000b�a\u0005\u0000\u0000\u0005�IDATx\u0001��]k\u001cU\u001c��ߙ�m�6i֦mBhd��\"\u00161\"B�M\u0013�P!�\u0005o�3�h\u0011�0x�M\u0013�\n\u0016�\u000f�\"Eھ\u0000I|\u0001%A/�\b�Z%\u0017>d�56Zj�4�fw3�9�\u001c�y�9�3�/��f��~�Ϝ��$\u0000EQ\u0014EQ\u0014EQ\u0014EQ\u0014EQ�B\f�����fPJu��t�\u001bu�\u0000�M&�\u001c�\u001b�E\b%\u001e�|�\u000b���(6d�s�M��/�Ь\t�q��>`\"�\u0012\u000b�?y+\u000b�c\u0018��\fܦ�Kе@`\u0012\u0007�/\u000e�qn\u0014��]�\u0007�� ;��\u0010|,Q ��p\u0006Ek��*\u0003���\u0019Ñ\u000b}�{֗}���\u0014\b�(ߜ�ϧG�S�\u0000\t\fC�?��G޿\b\u001f�=���d�����[)#� �x/��ܛ�X��!\u0002C�4{2��9w\u0007m�|\u0005�XD��\"�?�e�\u0015�\t��\u0010�\u0017\u001b\u001a��3�`�R\b�4��3�P,'d-Fe�Lʒ�\u0010\u001bP{e\u001f�\t�\nC\u0014ʤh%�}I�@�Ð\u0005����P,6�,>5�)���\u001b��\u0012�8�M��/��V,&D`�\u001b�;p/�fL�����\u0005;)�\f\u0014�y\u0010�!_���<\"���\u001dP��A�b�\"��P͂l�!�:\n��Y�n�!�.JB@�bȪ�R2rP��@�b��Gaf�_��b�BF��b5\u0001�\u0015C\u0016\u001aʮ��P,� ~a�\u0002Ga�`��L@�H���!+�,�\u0007�4����P�\u001c��\"\u000b\u0012\u0014F����\u0012��1\u001c����(\u001c\u001f��KJ�+Y$A����\u0017�S6�(̄�\u000f�c:\"VX\u00182ݚC}~\u001c�ꞃ�5l{\u001fK;�0��\u0000�ޜ\u0006�����\u0018KZ��Խ\t�E\n$l\f�7\u0014.1L�Pd@��!SAY��d6^��7\fQ$ޠ�6FeE�\u00157�j��u����eu�����OH�0D\u000e'%\u0010��㣊E\rC�\rJ`\u0018��F��*�l\u0013�@1ʏ�*\u0014u\f�\u001a��1D���k\u0005����9u���1D���\"���4t�\u0010\n\r�0�\u0015\n\ba8/p\u0010�pW� ���@\bC�@@\bC=�A\b�[��cȿ;I\u0018\u001e��-��\u0013���-�@�ԕa��\u000e`'�,I\u0018\"_�!��+�`|���E�^Z>�z�\t�\u0010�3!\f\u0015�\u0002�\u0013��$\u0011C�\u0019�<\u001d��\u001b�P��!�>!���25�$c�<���WU�P��!�6!����Wr�B\u0018�y\u0003ћ\u001d\u001e �5\na<�\u001b\b��C7F!��)�,�?�vw��(��>�\t)�\\bȖQ��\u001f\bc��?\u0006�+�}��֓{v���0��6`�k�rv$��j\u001aC�\f������k�vv>�(�P�z�ݝ~��<�H}\u001f���߾��G>�8U�h\u0006k9[>�X,0D� ���\n+\u0002(��\u0010)m���lڲ�Ay~��\"�^�\rU�|�\nC�4!�Ri��*LJ�0DJ rs��\u0010Qb�!R\u0005�lvY\b(��\u0010)��\u0015�V�\u0007�\u0012k\f�����\u0002@�=���*k�\nk��Z}���9��\u0010w\f��\t�h��U�'Eo��C\u0017b?\u00192� ����\u000f\u0015�P�,,>�\u001e;��\u000ew��\u0007��Ph���9J\u0019b\b�v�\u001dy�\u0003$,ן�\u0012�\u0010]��*\u0014\nuP�྽8�Ƌ�ӕ��,\u0018�Y�[�kzӘ�0�\u0004��A��������3.of��r�����g[��N\u001d͡�#��͑��?����3h�O6B1���ۗ��i\u0012�?�\u001c\u001b\u001b�'�A�>J*6_r�e\u0018�x�鉧(��(��(��(�����\u001fAI�ҟ�j�\u0000\u0000\u0000\u0000IEND�B`�", "type": "registry:file", "target": ".agents/skills/skill-creator/assets/skill-creator.png" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/license.txt", "content": "\n Apache License\n Version 2.0, January 2004\n http://www.apache.org/licenses/\n\n TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n\n 1. 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We also recommend that a\n file or class name and description of purpose be included on the\n same \"printed page\" as the copyright notice for easier\n identification within third-party archives.\n\n Copyright [yyyy] [name of copyright owner]\n\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\n Unless required by applicable law or agreed to in writing, software\n distributed under the License is distributed on an \"AS IS\" BASIS,\n WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n See the License for the specific language governing permissions and\n limitations under the License.\n", "type": "registry:file", "target": ".agents/skills/skill-creator/license.txt" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/references/openai_yaml.md", "content": "# openai.yaml fields (full example + descriptions)\n\n`agents/openai.yaml` is an extended, product-specific config intended for the machine/harness to read, not the agent. Other product-specific config can also live in the `agents/` folder.\n\n## Full example\n\n```yaml\ninterface:\n display_name: \"Optional user-facing name\"\n short_description: \"Optional user-facing description\"\n icon_small: \"./assets/small-400px.png\"\n icon_large: \"./assets/large-logo.svg\"\n brand_color: \"#3B82F6\"\n default_prompt: \"Optional surrounding prompt to use the skill with\"\n\ndependencies:\n tools:\n - type: \"mcp\"\n value: \"github\"\n description: \"GitHub MCP server\"\n transport: \"streamable_http\"\n url: \"https://api.githubcopilot.com/mcp/\"\n\npolicy:\n allow_implicit_invocation: true\n```\n\n## Field descriptions and constraints\n\nTop-level constraints:\n\n- Quote all string values.\n- Keep keys unquoted.\n- For `interface.default_prompt`: generate a helpful, short (typically 1 sentence) example starting prompt based on the skill. It must explicitly mention the skill as `$skill-name` (e.g., \"Use $skill-name-here to draft a concise weekly status update.\").\n\n- `interface.display_name`: Human-facing title shown in UI skill lists and chips.\n- `interface.short_description`: Human-facing short UI blurb (25–64 chars) for quick scanning.\n- `interface.icon_small`: Path to a small icon asset (relative to skill dir). Default to `./assets/` and place icons in the skill's `assets/` folder.\n- `interface.icon_large`: Path to a larger logo asset (relative to skill dir). Default to `./assets/` and place icons in the skill's `assets/` folder.\n- `interface.brand_color`: Hex color used for UI accents (e.g., badges).\n- `interface.default_prompt`: Default prompt snippet inserted when invoking the skill.\n- `dependencies.tools[].type`: Dependency category. Only `mcp` is supported for now.\n- `dependencies.tools[].value`: Identifier of the tool or dependency.\n- `dependencies.tools[].description`: Human-readable explanation of the dependency.\n- `dependencies.tools[].transport`: Connection type when `type` is `mcp`.\n- `dependencies.tools[].url`: MCP server URL when `type` is `mcp`.\n- `policy.allow_implicit_invocation`: When false, the skill is not injected into\n the model context by default, but can still be invoked explicitly via `$skill`.\n Defaults to true.\n", "type": "registry:file", "target": ".agents/skills/skill-creator/references/openai_yaml.md" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/scripts/generate_openai_yaml.py", "content": "#!/usr/bin/env python3\n\"\"\"\nOpenAI YAML Generator - Creates agents/openai.yaml for a skill folder.\n\nUsage:\n generate_openai_yaml.py [--name ] [--interface key=value]\n\"\"\"\n\nimport argparse\nimport re\nimport sys\nfrom pathlib import Path\n\nACRONYMS = {\n \"GH\",\n \"MCP\",\n \"API\",\n \"CI\",\n \"CLI\",\n \"LLM\",\n \"PDF\",\n \"PR\",\n \"UI\",\n \"URL\",\n \"SQL\",\n}\n\nBRANDS = {\n \"openai\": \"OpenAI\",\n \"openapi\": \"OpenAPI\",\n \"github\": \"GitHub\",\n \"pagerduty\": \"PagerDuty\",\n \"datadog\": \"DataDog\",\n \"sqlite\": \"SQLite\",\n \"fastapi\": \"FastAPI\",\n}\n\nSMALL_WORDS = {\"and\", \"or\", \"to\", \"up\", \"with\"}\n\nALLOWED_INTERFACE_KEYS = {\n \"display_name\",\n \"short_description\",\n \"icon_small\",\n \"icon_large\",\n \"brand_color\",\n \"default_prompt\",\n}\n\n\ndef yaml_quote(value):\n escaped = value.replace(\"\\\\\", \"\\\\\\\\\").replace('\"', '\\\\\"').replace(\"\\n\", \"\\\\n\")\n return f'\"{escaped}\"'\n\n\ndef format_display_name(skill_name):\n words = [word for word in skill_name.split(\"-\") if word]\n formatted = []\n for index, word in enumerate(words):\n lower = word.lower()\n upper = word.upper()\n if upper in ACRONYMS:\n formatted.append(upper)\n continue\n if lower in BRANDS:\n formatted.append(BRANDS[lower])\n continue\n if index > 0 and lower in SMALL_WORDS:\n formatted.append(lower)\n continue\n formatted.append(word.capitalize())\n return \" \".join(formatted)\n\n\ndef generate_short_description(display_name):\n description = f\"Help with {display_name} tasks\"\n\n if len(description) < 25:\n description = f\"Help with {display_name} tasks and workflows\"\n if len(description) < 25:\n description = f\"Help with {display_name} tasks with guidance\"\n\n if len(description) > 64:\n description = f\"Help with {display_name}\"\n if len(description) > 64:\n description = f\"{display_name} helper\"\n if len(description) > 64:\n description = f\"{display_name} tools\"\n if len(description) > 64:\n suffix = \" helper\"\n max_name_length = 64 - len(suffix)\n trimmed = display_name[:max_name_length].rstrip()\n description = f\"{trimmed}{suffix}\"\n if len(description) > 64:\n description = description[:64].rstrip()\n\n if len(description) < 25:\n description = f\"{description} workflows\"\n if len(description) > 64:\n description = description[:64].rstrip()\n\n return description\n\n\ndef read_frontmatter_name(skill_dir):\n skill_md = Path(skill_dir) / \"SKILL.md\"\n if not skill_md.exists():\n print(f\"[ERROR] SKILL.md not found in {skill_dir}\")\n return None\n content = skill_md.read_text()\n match = re.match(r\"^---\\n(.*?)\\n---\", content, re.DOTALL)\n if not match:\n print(\"[ERROR] Invalid SKILL.md frontmatter format.\")\n return None\n frontmatter_text = match.group(1)\n\n import yaml\n\n try:\n frontmatter = yaml.safe_load(frontmatter_text)\n except yaml.YAMLError as exc:\n print(f\"[ERROR] Invalid YAML frontmatter: {exc}\")\n return None\n if not isinstance(frontmatter, dict):\n print(\"[ERROR] Frontmatter must be a YAML dictionary.\")\n return None\n name = frontmatter.get(\"name\", \"\")\n if not isinstance(name, str) or not name.strip():\n print(\"[ERROR] Frontmatter 'name' is missing or invalid.\")\n return None\n return name.strip()\n\n\ndef parse_interface_overrides(raw_overrides):\n overrides = {}\n optional_order = []\n for item in raw_overrides:\n if \"=\" not in item:\n print(f\"[ERROR] Invalid interface override '{item}'. Use key=value.\")\n return None, None\n key, value = item.split(\"=\", 1)\n key = key.strip()\n value = value.strip()\n if not key:\n print(f\"[ERROR] Invalid interface override '{item}'. Key is empty.\")\n return None, None\n if key not in ALLOWED_INTERFACE_KEYS:\n allowed = \", \".join(sorted(ALLOWED_INTERFACE_KEYS))\n print(f\"[ERROR] Unknown interface field '{key}'. Allowed: {allowed}\")\n return None, None\n overrides[key] = value\n if key not in (\"display_name\", \"short_description\") and key not in optional_order:\n optional_order.append(key)\n return overrides, optional_order\n\n\ndef write_openai_yaml(skill_dir, skill_name, raw_overrides):\n overrides, optional_order = parse_interface_overrides(raw_overrides)\n if overrides is None:\n return None\n\n display_name = overrides.get(\"display_name\") or format_display_name(skill_name)\n short_description = overrides.get(\"short_description\") or generate_short_description(display_name)\n\n if not (25 <= len(short_description) <= 64):\n print(\n \"[ERROR] short_description must be 25-64 characters \"\n f\"(got {len(short_description)}).\"\n )\n return None\n\n interface_lines = [\n \"interface:\",\n f\" display_name: {yaml_quote(display_name)}\",\n f\" short_description: {yaml_quote(short_description)}\",\n ]\n\n for key in optional_order:\n value = overrides.get(key)\n if value is not None:\n interface_lines.append(f\" {key}: {yaml_quote(value)}\")\n\n agents_dir = Path(skill_dir) / \"agents\"\n agents_dir.mkdir(parents=True, exist_ok=True)\n output_path = agents_dir / \"openai.yaml\"\n output_path.write_text(\"\\n\".join(interface_lines) + \"\\n\")\n print(f\"[OK] Created agents/openai.yaml\")\n return output_path\n\n\ndef main():\n parser = argparse.ArgumentParser(\n description=\"Create agents/openai.yaml for a skill directory.\",\n )\n parser.add_argument(\"skill_dir\", help=\"Path to the skill directory\")\n parser.add_argument(\n \"--name\",\n help=\"Skill name override (defaults to SKILL.md frontmatter)\",\n )\n parser.add_argument(\n \"--interface\",\n action=\"append\",\n default=[],\n help=\"Interface override in key=value format (repeatable)\",\n )\n args = parser.parse_args()\n\n skill_dir = Path(args.skill_dir).resolve()\n if not skill_dir.exists():\n print(f\"[ERROR] Skill directory not found: {skill_dir}\")\n sys.exit(1)\n if not skill_dir.is_dir():\n print(f\"[ERROR] Path is not a directory: {skill_dir}\")\n sys.exit(1)\n\n skill_name = args.name or read_frontmatter_name(skill_dir)\n if not skill_name:\n sys.exit(1)\n\n result = write_openai_yaml(skill_dir, skill_name, args.interface)\n if result:\n sys.exit(0)\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()\n", "type": "registry:file", "target": ".agents/skills/skill-creator/scripts/generate_openai_yaml.py" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/scripts/init_skill.py", "content": "#!/usr/bin/env python3\n\"\"\"\nSkill Initializer - Creates a new skill from template\n\nUsage:\n init_skill.py --path [--resources scripts,references,assets] [--examples] [--interface key=value]\n\nExamples:\n init_skill.py my-new-skill --path skills/public\n init_skill.py my-new-skill --path skills/public --resources scripts,references\n init_skill.py my-api-helper --path skills/private --resources scripts --examples\n init_skill.py custom-skill --path /custom/location\n init_skill.py my-skill --path skills/public --interface short_description=\"Short UI label\"\n\"\"\"\n\nimport argparse\nimport re\nimport sys\nfrom pathlib import Path\n\nfrom generate_openai_yaml import write_openai_yaml\n\nMAX_SKILL_NAME_LENGTH = 64\nALLOWED_RESOURCES = {\"scripts\", \"references\", \"assets\"}\n\nSKILL_TEMPLATE = \"\"\"---\nname: {skill_name}\ndescription: \"TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.\"\n---\n\n# {skill_title}\n\n## Overview\n\n[TODO: 1-2 sentences explaining what this skill enables]\n\n## Structuring This Skill\n\n[TODO: Choose the structure that best fits this skill's purpose. Common patterns:\n\n**1. Workflow-Based** (best for sequential processes)\n- Works well when there are clear step-by-step procedures\n- Example: DOCX skill with \"Workflow Decision Tree\" -> \"Reading\" -> \"Creating\" -> \"Editing\"\n- Structure: ## Overview -> ## Workflow Decision Tree -> ## Step 1 -> ## Step 2...\n\n**2. Task-Based** (best for tool collections)\n- Works well when the skill offers different operations/capabilities\n- Example: PDF skill with \"Quick Start\" -> \"Merge PDFs\" -> \"Split PDFs\" -> \"Extract Text\"\n- Structure: ## Overview -> ## Quick Start -> ## Task Category 1 -> ## Task Category 2...\n\n**3. Reference/Guidelines** (best for standards or specifications)\n- Works well for brand guidelines, coding standards, or requirements\n- Example: Brand styling with \"Brand Guidelines\" -> \"Colors\" -> \"Typography\" -> \"Features\"\n- Structure: ## Overview -> ## Guidelines -> ## Specifications -> ## Usage...\n\n**4. Capabilities-Based** (best for integrated systems)\n- Works well when the skill provides multiple interrelated features\n- Example: Product Management with \"Core Capabilities\" -> numbered capability list\n- Structure: ## Overview -> ## Core Capabilities -> ### 1. Feature -> ### 2. Feature...\n\nPatterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).\n\nDelete this entire \"Structuring This Skill\" section when done - it's just guidance.]\n\n## [TODO: Replace with the first main section based on chosen structure]\n\n[TODO: Add content here. See examples in existing skills:\n- Code samples for technical skills\n- Decision trees for complex workflows\n- Concrete examples with realistic user requests\n- References to scripts/templates/references as needed]\n\n## Resources (optional)\n\nCreate only the resource directories this skill actually needs. Delete this section if no resources are required.\n\n### scripts/\nExecutable code (Python/Bash/etc.) that can be run directly to perform specific operations.\n\n**Examples from other skills:**\n- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation\n- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing\n\n**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.\n\n**Note:** Scripts may be executed without loading into context, but can still be read by Codex for patching or environment adjustments.\n\n### references/\nDocumentation and reference material intended to be loaded into context to inform Codex's process and thinking.\n\n**Examples from other skills:**\n- Product management: `communication.md`, `context_building.md` - detailed workflow guides\n- BigQuery: API reference documentation and query examples\n- Finance: Schema documentation, company policies\n\n**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Codex should reference while working.\n\n### assets/\nFiles not intended to be loaded into context, but rather used within the output Codex produces.\n\n**Examples from other skills:**\n- Brand styling: PowerPoint template files (.pptx), logo files\n- Frontend builder: HTML/React boilerplate project directories\n- Typography: Font files (.ttf, .woff2)\n\n**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.\n\n---\n\n**Not every skill requires all three types of resources.**\n\"\"\"\n\nEXAMPLE_SCRIPT = '''#!/usr/bin/env python3\n\"\"\"\nExample helper script for {skill_name}\n\nThis is a placeholder script that can be executed directly.\nReplace with actual implementation or delete if not needed.\n\nExample real scripts from other skills:\n- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields\n- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images\n\"\"\"\n\ndef main():\n print(\"This is an example script for {skill_name}\")\n # TODO: Add actual script logic here\n # This could be data processing, file conversion, API calls, etc.\n\nif __name__ == \"__main__\":\n main()\n'''\n\nEXAMPLE_REFERENCE = \"\"\"# Reference Documentation for {skill_title}\n\nThis is a placeholder for detailed reference documentation.\nReplace with actual reference content or delete if not needed.\n\nExample real reference docs from other skills:\n- product-management/references/communication.md - Comprehensive guide for status updates\n- product-management/references/context_building.md - Deep-dive on gathering context\n- bigquery/references/ - API references and query examples\n\n## When Reference Docs Are Useful\n\nReference docs are ideal for:\n- Comprehensive API documentation\n- Detailed workflow guides\n- Complex multi-step processes\n- Information too lengthy for main SKILL.md\n- Content that's only needed for specific use cases\n\n## Structure Suggestions\n\n### API Reference Example\n- Overview\n- Authentication\n- Endpoints with examples\n- Error codes\n- Rate limits\n\n### Workflow Guide Example\n- Prerequisites\n- Step-by-step instructions\n- Common patterns\n- Troubleshooting\n- Best practices\n\"\"\"\n\nEXAMPLE_ASSET = \"\"\"# Example Asset File\n\nThis placeholder represents where asset files would be stored.\nReplace with actual asset files (templates, images, fonts, etc.) or delete if not needed.\n\nAsset files are NOT intended to be loaded into context, but rather used within\nthe output Codex produces.\n\nExample asset files from other skills:\n- Brand guidelines: logo.png, slides_template.pptx\n- Frontend builder: hello-world/ directory with HTML/React boilerplate\n- Typography: custom-font.ttf, font-family.woff2\n- Data: sample_data.csv, test_dataset.json\n\n## Common Asset Types\n\n- Templates: .pptx, .docx, boilerplate directories\n- Images: .png, .jpg, .svg, .gif\n- Fonts: .ttf, .otf, .woff, .woff2\n- Boilerplate code: Project directories, starter files\n- Icons: .ico, .svg\n- Data files: .csv, .json, .xml, .yaml\n\nNote: This is a text placeholder. Actual assets can be any file type.\n\"\"\"\n\n\ndef normalize_skill_name(skill_name):\n \"\"\"Normalize a skill name to lowercase hyphen-case.\"\"\"\n normalized = skill_name.strip().lower()\n normalized = re.sub(r\"[^a-z0-9]+\", \"-\", normalized)\n normalized = normalized.strip(\"-\")\n normalized = re.sub(r\"-{2,}\", \"-\", normalized)\n return normalized\n\n\ndef title_case_skill_name(skill_name):\n \"\"\"Convert hyphenated skill name to Title Case for display.\"\"\"\n return \" \".join(word.capitalize() for word in skill_name.split(\"-\"))\n\n\ndef parse_resources(raw_resources):\n if not raw_resources:\n return []\n resources = [item.strip() for item in raw_resources.split(\",\") if item.strip()]\n invalid = sorted({item for item in resources if item not in ALLOWED_RESOURCES})\n if invalid:\n allowed = \", \".join(sorted(ALLOWED_RESOURCES))\n print(f\"[ERROR] Unknown resource type(s): {', '.join(invalid)}\")\n print(f\" Allowed: {allowed}\")\n sys.exit(1)\n deduped = []\n seen = set()\n for resource in resources:\n if resource not in seen:\n deduped.append(resource)\n seen.add(resource)\n return deduped\n\n\ndef create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples):\n for resource in resources:\n resource_dir = skill_dir / resource\n resource_dir.mkdir(exist_ok=True)\n if resource == \"scripts\":\n if include_examples:\n example_script = resource_dir / \"example.py\"\n example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))\n example_script.chmod(0o755)\n print(\"[OK] Created scripts/example.py\")\n else:\n print(\"[OK] Created scripts/\")\n elif resource == \"references\":\n if include_examples:\n example_reference = resource_dir / \"api_reference.md\"\n example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))\n print(\"[OK] Created references/api_reference.md\")\n else:\n print(\"[OK] Created references/\")\n elif resource == \"assets\":\n if include_examples:\n example_asset = resource_dir / \"example_asset.txt\"\n example_asset.write_text(EXAMPLE_ASSET)\n print(\"[OK] Created assets/example_asset.txt\")\n else:\n print(\"[OK] Created assets/\")\n\n\ndef init_skill(skill_name, path, resources, include_examples, interface_overrides):\n \"\"\"\n Initialize a new skill directory with template SKILL.md.\n\n Args:\n skill_name: Name of the skill\n path: Path where the skill directory should be created\n resources: Resource directories to create\n include_examples: Whether to create example files in resource directories\n\n Returns:\n Path to created skill directory, or None if error\n \"\"\"\n # Determine skill directory path\n skill_dir = Path(path).resolve() / skill_name\n\n # Check if directory already exists\n if skill_dir.exists():\n print(f\"[ERROR] Skill directory already exists: {skill_dir}\")\n return None\n\n # Create skill directory\n try:\n skill_dir.mkdir(parents=True, exist_ok=False)\n print(f\"[OK] Created skill directory: {skill_dir}\")\n except Exception as e:\n print(f\"[ERROR] Error creating directory: {e}\")\n return None\n\n # Create SKILL.md from template\n skill_title = title_case_skill_name(skill_name)\n skill_content = SKILL_TEMPLATE.format(skill_name=skill_name, skill_title=skill_title)\n\n skill_md_path = skill_dir / \"SKILL.md\"\n try:\n skill_md_path.write_text(skill_content)\n print(\"[OK] Created SKILL.md\")\n except Exception as e:\n print(f\"[ERROR] Error creating SKILL.md: {e}\")\n return None\n\n # Create agents/openai.yaml\n try:\n result = write_openai_yaml(skill_dir, skill_name, interface_overrides)\n if not result:\n return None\n except Exception as e:\n print(f\"[ERROR] Error creating agents/openai.yaml: {e}\")\n return None\n\n # Create resource directories if requested\n if resources:\n try:\n create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples)\n except Exception as e:\n print(f\"[ERROR] Error creating resource directories: {e}\")\n return None\n\n # Print next steps\n print(f\"\\n[OK] Skill '{skill_name}' initialized successfully at {skill_dir}\")\n print(\"\\nNext steps:\")\n print(\"1. Edit SKILL.md to complete the TODO items and update the description\")\n if resources:\n if include_examples:\n print(\"2. Customize or delete the example files in scripts/, references/, and assets/\")\n else:\n print(\"2. Add resources to scripts/, references/, and assets/ as needed\")\n else:\n print(\"2. Create resource directories only if needed (scripts/, references/, assets/)\")\n print(\"3. Update agents/openai.yaml if the UI metadata should differ\")\n print(\"4. Run the validator when ready to check the skill structure\")\n print(\n \"5. Forward-test complex skills with realistic user requests to ensure they work as intended\"\n )\n\n return skill_dir\n\n\ndef main():\n parser = argparse.ArgumentParser(\n description=\"Create a new skill directory with a SKILL.md template.\",\n )\n parser.add_argument(\"skill_name\", help=\"Skill name (normalized to hyphen-case)\")\n parser.add_argument(\"--path\", required=True, help=\"Output directory for the skill\")\n parser.add_argument(\n \"--resources\",\n default=\"\",\n help=\"Comma-separated list: scripts,references,assets\",\n )\n parser.add_argument(\n \"--examples\",\n action=\"store_true\",\n help=\"Create example files inside the selected resource directories\",\n )\n parser.add_argument(\n \"--interface\",\n action=\"append\",\n default=[],\n help=\"Interface override in key=value format (repeatable)\",\n )\n args = parser.parse_args()\n\n raw_skill_name = args.skill_name\n skill_name = normalize_skill_name(raw_skill_name)\n if not skill_name:\n print(\"[ERROR] Skill name must include at least one letter or digit.\")\n sys.exit(1)\n if len(skill_name) > MAX_SKILL_NAME_LENGTH:\n print(\n f\"[ERROR] Skill name '{skill_name}' is too long ({len(skill_name)} characters). \"\n f\"Maximum is {MAX_SKILL_NAME_LENGTH} characters.\"\n )\n sys.exit(1)\n if skill_name != raw_skill_name:\n print(f\"Note: Normalized skill name from '{raw_skill_name}' to '{skill_name}'.\")\n\n resources = parse_resources(args.resources)\n if args.examples and not resources:\n print(\"[ERROR] --examples requires --resources to be set.\")\n sys.exit(1)\n\n path = args.path\n\n print(f\"Initializing skill: {skill_name}\")\n print(f\" Location: {path}\")\n if resources:\n print(f\" Resources: {', '.join(resources)}\")\n if args.examples:\n print(\" Examples: enabled\")\n else:\n print(\" Resources: none (create as needed)\")\n print()\n\n result = init_skill(skill_name, path, resources, args.examples, args.interface)\n\n if result:\n sys.exit(0)\n else:\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()\n", "type": "registry:file", "target": ".agents/skills/skill-creator/scripts/init_skill.py" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/scripts/quick_validate.py", "content": "#!/usr/bin/env python3\n\"\"\"\nQuick validation script for skills - minimal version\n\"\"\"\n\nimport re\nimport sys\nfrom pathlib import Path\n\nimport yaml\n\nMAX_SKILL_NAME_LENGTH = 64\n\n\ndef validate_skill(skill_path):\n \"\"\"Basic validation of a skill\"\"\"\n skill_path = Path(skill_path)\n\n skill_md = skill_path / \"SKILL.md\"\n if not skill_md.exists():\n return False, \"SKILL.md not found\"\n\n content = skill_md.read_text()\n if not content.startswith(\"---\"):\n return False, \"No YAML frontmatter found\"\n\n match = re.match(r\"^---\\n(.*?)\\n---\", content, re.DOTALL)\n if not match:\n return False, \"Invalid frontmatter format\"\n\n frontmatter_text = match.group(1)\n\n try:\n frontmatter = yaml.safe_load(frontmatter_text)\n if not isinstance(frontmatter, dict):\n return False, \"Frontmatter must be a YAML dictionary\"\n except yaml.YAMLError as e:\n return False, f\"Invalid YAML in frontmatter: {e}\"\n\n allowed_properties = {\"name\", \"description\", \"license\", \"allowed-tools\", \"metadata\"}\n\n unexpected_keys = set(frontmatter.keys()) - allowed_properties\n if unexpected_keys:\n allowed = \", \".join(sorted(allowed_properties))\n unexpected = \", \".join(sorted(unexpected_keys))\n return (\n False,\n f\"Unexpected key(s) in SKILL.md frontmatter: {unexpected}. Allowed properties are: {allowed}\",\n )\n\n if \"name\" not in frontmatter:\n return False, \"Missing 'name' in frontmatter\"\n if \"description\" not in frontmatter:\n return False, \"Missing 'description' in frontmatter\"\n\n name = frontmatter.get(\"name\", \"\")\n if not isinstance(name, str):\n return False, f\"Name must be a string, got {type(name).__name__}\"\n name = name.strip()\n if name:\n if not re.match(r\"^[a-z0-9-]+$\", name):\n return (\n False,\n f\"Name '{name}' should be hyphen-case (lowercase letters, digits, and hyphens only)\",\n )\n if name.startswith(\"-\") or name.endswith(\"-\") or \"--\" in name:\n return (\n False,\n f\"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens\",\n )\n if len(name) > MAX_SKILL_NAME_LENGTH:\n return (\n False,\n f\"Name is too long ({len(name)} characters). \"\n f\"Maximum is {MAX_SKILL_NAME_LENGTH} characters.\",\n )\n\n description = frontmatter.get(\"description\", \"\")\n if not isinstance(description, str):\n return False, f\"Description must be a string, got {type(description).__name__}\"\n description = description.strip()\n if description:\n if \"<\" in description or \">\" in description:\n return False, \"Description cannot contain angle brackets (< or >)\"\n if len(description) > 1024:\n return (\n False,\n f\"Description is too long ({len(description)} characters). Maximum is 1024 characters.\",\n )\n\n return True, \"Skill is valid!\"\n\n\nif __name__ == \"__main__\":\n if len(sys.argv) != 2:\n print(\"Usage: python quick_validate.py \")\n sys.exit(1)\n\n valid, message = validate_skill(sys.argv[1])\n print(message)\n sys.exit(0 if valid else 1)\n", "type": "registry:file", "target": ".agents/skills/skill-creator/scripts/quick_validate.py" }, { "path": "registry/ultra-chatbot-agent/.agents/skills/skill-creator/SKILL.md", "content": "---\nname: skill-creator\ndescription: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.\nmetadata:\n short-description: Create or update a skill\n---\n\n# Skill Creator\n\nThis skill provides guidance for creating effective skills.\n\n## About Skills\n\nSkills are modular, self-contained folders that extend Codex's capabilities by providing\nspecialized knowledge, workflows, and tools. Think of them as \"onboarding guides\" for specific\ndomains or tasks—they transform Codex from a general-purpose agent into a specialized agent\nequipped with procedural knowledge that no model can fully possess.\n\n### What Skills Provide\n\n1. Specialized workflows - Multi-step procedures for specific domains\n2. Tool integrations - Instructions for working with specific file formats or APIs\n3. Domain expertise - Company-specific knowledge, schemas, business logic\n4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks\n\n## Core Principles\n\n### Concise is Key\n\nThe context window is a public good. Skills share the context window with everything else Codex needs: system prompt, conversation history, other Skills' metadata, and the actual user request.\n\n**Default assumption: Codex is already very smart.** Only add context Codex doesn't already have. Challenge each piece of information: \"Does Codex really need this explanation?\" and \"Does this paragraph justify its token cost?\"\n\nPrefer concise examples over verbose explanations.\n\n### Set Appropriate Degrees of Freedom\n\nMatch the level of specificity to the task's fragility and variability:\n\n**High freedom (text-based instructions)**: Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.\n\n**Medium freedom (pseudocode or scripts with parameters)**: Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.\n\n**Low freedom (specific scripts, few parameters)**: Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.\n\nThink of Codex as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).\n\n### Protect Validation Integrity\n\nYou may use subagents during iteration to validate whether a skill works on realistic tasks or whether a suspected problem is real. This is most useful when you want an independent pass on the skill's behavior, outputs, or failure modes after a revision. Only do this when it is possible to start new subagents.\n\nWhen using subagents for validation, treat that as an evaluation surface. The goal is to learn whether the skill generalizes, not whether another agent can reconstruct the answer from leaked context.\n\nPrefer raw artifacts such as example prompts, outputs, diffs, logs, or traces. Give the minimum task-local context needed to perform the validation. Avoid passing the intended answer, suspected bug, intended fix, or your prior conclusions unless the validation explicitly requires them.\n\n### Anatomy of a Skill\n\nEvery skill consists of a required SKILL.md file and optional bundled resources:\n\n```\nskill-name/\n├── SKILL.md (required)\n│ ├── YAML frontmatter metadata (required)\n│ │ ├── name: (required)\n│ │ └── description: (required)\n│ └── Markdown instructions (required)\n├── agents/ (recommended)\n│ └── openai.yaml - UI metadata for skill lists and chips\n└── Bundled Resources (optional)\n ├── scripts/ - Executable code (Python/Bash/etc.)\n ├── references/ - Documentation intended to be loaded into context as needed\n └── assets/ - Files used in output (templates, icons, fonts, etc.)\n```\n\n#### SKILL.md (required)\n\nEvery SKILL.md consists of:\n\n- **Frontmatter** (YAML): Contains `name` and `description` fields. These are the only fields that Codex reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.\n- **Body** (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).\n\n#### Agents metadata (recommended)\n\n- UI-facing metadata for skill lists and chips\n- Read references/openai_yaml.md before generating values and follow its descriptions and constraints\n- Create: human-facing `display_name`, `short_description`, and `default_prompt` by reading the skill\n- Generate deterministically by passing the values as `--interface key=value` to `scripts/generate_openai_yaml.py` or `scripts/init_skill.py`\n- On updates: validate `agents/openai.yaml` still matches SKILL.md; regenerate if stale\n- Only include other optional interface fields (icons, brand color) if explicitly provided\n- See references/openai_yaml.md for field definitions and examples\n\n#### Bundled Resources (optional)\n\n##### Scripts (`scripts/`)\n\nExecutable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.\n\n- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed\n- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks\n- **Benefits**: Token efficient, deterministic, may be executed without loading into context\n- **Note**: Scripts may still need to be read by Codex for patching or environment-specific adjustments\n\n##### References (`references/`)\n\nDocumentation and reference material intended to be loaded as needed into context to inform Codex's process and thinking.\n\n- **When to include**: For documentation that Codex should reference while working\n- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications\n- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides\n- **Benefits**: Keeps SKILL.md lean, loaded only when Codex determines it's needed\n- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md\n- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.\n\n##### Assets (`assets/`)\n\nFiles not intended to be loaded into context, but rather used within the output Codex produces.\n\n- **When to include**: When the skill needs files that will be used in the final output\n- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography\n- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified\n- **Benefits**: Separates output resources from documentation, enables Codex to use files without loading them into context\n\n#### What to Not Include in a Skill\n\nA skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:\n\n- README.md\n- INSTALLATION_GUIDE.md\n- QUICK_REFERENCE.md\n- CHANGELOG.md\n- etc.\n\nThe skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxiliary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.\n\n### Progressive Disclosure Design Principle\n\nSkills use a three-level loading system to manage context efficiently:\n\n1. **Metadata (name + description)** - Always in context (~100 words)\n2. **SKILL.md body** - When skill triggers (<5k words)\n3. **Bundled resources** - As needed by Codex (Unlimited because scripts can be executed without reading into context window)\n\n#### Progressive Disclosure Patterns\n\nKeep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.\n\n**Key principle:** When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.\n\n**Pattern 1: High-level guide with references**\n\n```markdown\n# PDF Processing\n\n## Quick start\n\nExtract text with pdfplumber:\n[code example]\n\n## Advanced features\n\n- **Form filling**: See [FORMS.md](FORMS.md) for complete guide\n- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods\n- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns\n```\n\nCodex loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.\n\n**Pattern 2: Domain-specific organization**\n\nFor Skills with multiple domains, organize content by domain to avoid loading irrelevant context:\n\n```\nbigquery-skill/\n├── SKILL.md (overview and navigation)\n└── reference/\n ├── finance.md (revenue, billing metrics)\n ├── sales.md (opportunities, pipeline)\n ├── product.md (API usage, features)\n └── marketing.md (campaigns, attribution)\n```\n\nWhen a user asks about sales metrics, Codex only reads sales.md.\n\nSimilarly, for skills supporting multiple frameworks or variants, organize by variant:\n\n```\ncloud-deploy/\n├── SKILL.md (workflow + provider selection)\n└── references/\n ├── aws.md (AWS deployment patterns)\n ├── gcp.md (GCP deployment patterns)\n └── azure.md (Azure deployment patterns)\n```\n\nWhen the user chooses AWS, Codex only reads aws.md.\n\n**Pattern 3: Conditional details**\n\nShow basic content, link to advanced content:\n\n```markdown\n# DOCX Processing\n\n## Creating documents\n\nUse docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).\n\n## Editing documents\n\nFor simple edits, modify the XML directly.\n\n**For tracked changes**: See [REDLINING.md](REDLINING.md)\n**For OOXML details**: See [OOXML.md](OOXML.md)\n```\n\nCodex reads REDLINING.md or OOXML.md only when the user needs those features.\n\n**Important guidelines:**\n\n- **Avoid deeply nested references** - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.\n- **Structure longer reference files** - For files longer than 100 lines, include a table of contents at the top so Codex can see the full scope when previewing.\n\n## Skill Creation Process\n\nSkill creation involves these steps:\n\n1. Understand the skill with concrete examples\n2. Plan reusable skill contents (scripts, references, assets)\n3. Initialize the skill (run init_skill.py)\n4. Edit the skill (implement resources and write SKILL.md)\n5. Validate the skill (run quick_validate.py)\n6. Iterate based on real usage and forward-test complex skills.\n\nFollow these steps in order, skipping only if there is a clear reason why they are not applicable.\n\n### Skill Naming\n\n- Use lowercase letters, digits, and hyphens only; normalize user-provided titles to hyphen-case (e.g., \"Plan Mode\" -> `plan-mode`).\n- When generating names, generate a name under 64 characters (letters, digits, hyphens).\n- Prefer short, verb-led phrases that describe the action.\n- Namespace by tool when it improves clarity or triggering (e.g., `gh-address-comments`, `linear-address-issue`).\n- Name the skill folder exactly after the skill name.\n\n### Step 1: Understanding the Skill with Concrete Examples\n\nSkip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.\n\nTo create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.\n\nFor example, when building an image-editor skill, relevant questions include:\n\n- \"What functionality should the image-editor skill support? Editing, rotating, anything else?\"\n- \"Can you give some examples of how this skill would be used?\"\n- \"I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?\"\n- \"What would a user say that should trigger this skill?\"\n- \"Where should I create this skill? If you do not have a preference, I will place it in `$CODEX_HOME/skills` (or `~/.codex/skills` when `CODEX_HOME` is unset) so Codex can discover it automatically.\"\n\nTo avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.\n\nConclude this step when there is a clear sense of the functionality the skill should support.\n\n### Step 2: Planning the Reusable Skill Contents\n\nTo turn concrete examples into an effective skill, analyze each example by:\n\n1. Considering how to execute on the example from scratch\n2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly\n\nExample: When building a `pdf-editor` skill to handle queries like \"Help me rotate this PDF,\" the analysis shows:\n\n1. Rotating a PDF requires re-writing the same code each time\n2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill\n\nExample: When designing a `frontend-webapp-builder` skill for queries like \"Build me a todo app\" or \"Build me a dashboard to track my steps,\" the analysis shows:\n\n1. Writing a frontend webapp requires the same boilerplate HTML/React each time\n2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill\n\nExample: When building a `big-query` skill to handle queries like \"How many users have logged in today?\" the analysis shows:\n\n1. Querying BigQuery requires re-discovering the table schemas and relationships each time\n2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill\n\nTo establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.\n\n### Step 3: Initializing the Skill\n\nAt this point, it is time to actually create the skill.\n\nSkip this step only if the skill being developed already exists. In this case, continue to the next step.\n\nBefore running `init_skill.py`, ask where the user wants the skill created. If they do not specify a location, default to `$CODEX_HOME/skills`; when `CODEX_HOME` is unset, fall back to `~/.codex/skills` so the skill is auto-discovered.\n\nWhen creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.\n\nUsage:\n\n```bash\nscripts/init_skill.py --path [--resources scripts,references,assets] [--examples]\n```\n\nExamples:\n\n```bash\nscripts/init_skill.py my-skill --path \"${CODEX_HOME:-$HOME/.codex}/skills\"\nscripts/init_skill.py my-skill --path \"${CODEX_HOME:-$HOME/.codex}/skills\" --resources scripts,references\nscripts/init_skill.py my-skill --path ~/work/skills --resources scripts --examples\n```\n\nThe script:\n\n- Creates the skill directory at the specified path\n- Generates a SKILL.md template with proper frontmatter and TODO placeholders\n- Creates `agents/openai.yaml` using agent-generated `display_name`, `short_description`, and `default_prompt` passed via `--interface key=value`\n- Optionally creates resource directories based on `--resources`\n- Optionally adds example files when `--examples` is set\n\nAfter initialization, customize the SKILL.md and add resources as needed. If you used `--examples`, replace or delete placeholder files.\n\nGenerate `display_name`, `short_description`, and `default_prompt` by reading the skill, then pass them as `--interface key=value` to `init_skill.py` or regenerate with:\n\n```bash\nscripts/generate_openai_yaml.py --interface key=value\n```\n\nOnly include other optional interface fields when the user explicitly provides them. For full field descriptions and examples, see references/openai_yaml.md.\n\n### Step 4: Edit the Skill\n\nWhen editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Codex to use. Include information that would be beneficial and non-obvious to Codex. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Codex instance execute these tasks more effectively.\n\nAfter substantial revisions, or if the skill is particularly tricky, you should use subagents to forward-test the skill on realistic tasks or artifacts. When doing so, pass the artifact under validation rather than your diagnosis of what is wrong, and keep the prompt generic enough that success depends on transferable reasoning rather than hidden ground truth.\n\n#### Start with Reusable Skill Contents\n\nTo begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`.\n\nAdded scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.\n\nIf you used `--examples`, delete any placeholder files that are not needed for the skill. Only create resource directories that are actually required.\n\n#### Update SKILL.md\n\n**Writing Guidelines:** Always use imperative/infinitive form.\n\n##### Frontmatter\n\nWrite the YAML frontmatter with `name` and `description`:\n\n- `name`: The skill name\n- `description`: This is the primary triggering mechanism for your skill, and helps Codex understand when to use the skill.\n - Include both what the Skill does and specific triggers/contexts for when to use it.\n - Include all \"when to use\" information here - Not in the body. The body is only loaded after triggering, so \"When to Use This Skill\" sections in the body are not helpful to Codex.\n - Example description for a `docx` skill: \"Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when Codex needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks\"\n\nDo not include any other fields in YAML frontmatter.\n\n##### Body\n\nWrite instructions for using the skill and its bundled resources.\n\n### Step 5: Validate the Skill\n\nOnce development of the skill is complete, validate the skill folder to catch basic issues early:\n\n```bash\nscripts/quick_validate.py \n```\n\nThe validation script checks YAML frontmatter format, required fields, and naming rules. If validation fails, fix the reported issues and run the command again.\n\n### Step 6: Iterate\n\nAfter testing the skill, you may detect the skill is complex enough that it requires forward-testing; or users may request improvements.\n\nUser testing often this happens right after using the skill, with fresh context of how the skill performed.\n\n**Forward-testing and iteration workflow:**\n\n1. Use the skill on real tasks\n2. Notice struggles or inefficiencies\n3. Identify how SKILL.md or bundled resources should be updated\n4. Implement changes and test again\n5. Forward-test if it is reasonable and appropriate\n\n## Forward-testing\n\nTo forward-test, launch subagents as a way to stress test the skill with minimal context.\nSubagents should *not* know that they are being asked to test the skill. They should be treated as\nan agent asked to perform a task by the user. Prompts to subagents should look like:\n `Use $skill-x at /path/to/skill-x to solve problem y`\nNot:\n `Review the skill at /path/to/skill-x; pretend a user asks you to...`\n\nDecision rule for forward-testing:\n - Err on the side of forward-testing\n - Ask for approval if you think there's a risk that forward-testing would:\n * take a long time,\n * require additional approvals from the user, or\n * modify live production systems\n\n In these cases, show the user your proposed prompt and request (1) a yes/no decision, and\n (2) any suggested modifictions.\n\nConsiderations when forward-testing:\n - use fresh threads for independent passes\n - pass the skill, and a request in a similar way the user would.\n - pass raw artifacts, not your conclusions\n - avoid showing expected answers or intended fixes\n - rebuild context from source artifacts after each iteration\n - review the subagent's output and reasoning and emitted artifacts\n - avoid leaving artifacts the agent can find on disk between iterations;\n clean up subagents' artifacts to avoid additional contamination.\n\nIf forward-testing only succeeds when subagents see leaked context, tighten the skill or the\nforward-testing setup before trusting the result.\n", "type": "registry:file", "target": ".agents/skills/skill-creator/SKILL.md" }, { "path": "registry/ultra-chatbot-agent/app/api/cron/ultra-chatbot-agent-cleanup/route.ts", "content": "import { getUltraChatbotAgentAppEnv } from \"@/lib/ultra-chatbot-agent/server/env\";\n\nconst appEnv = getUltraChatbotAgentAppEnv();\nimport {\n getCronSecret,\n getCronSecretError,\n} from \"@/lib/ultra-chatbot-agent/server/env\";\nimport {\n cleanupExpiredUltraChatbotAgentDemoData,\n ultraChatbotAgentCleanupCronScheduleUtc,\n} from \"@/lib/ultra-chatbot-agent/server/cleanup\";\n\nfunction isAuthorizedCronRequest(request: Request, cronSecret: string) {\n const authorizationHeader = request.headers.get(\"authorization\");\n\n return authorizationHeader === `Bearer ${cronSecret}`;\n}\n\nexport async function GET(request: Request) {\n let cronSecret: string;\n\n try {\n cronSecret = getCronSecret(appEnv);\n } catch (error) {\n return Response.json(\n {\n error: error instanceof Error ? error.message : getCronSecretError(),\n },\n { status: 500 }\n );\n }\n\n if (!isAuthorizedCronRequest(request, cronSecret)) {\n return Response.json(\n {\n error: \"Unauthorized ultra-chatbot-agent cleanup request.\",\n },\n { status: 401 }\n );\n }\n\n try {\n const result = await cleanupExpiredUltraChatbotAgentDemoData();\n\n return Response.json({\n ...result,\n scheduleUtc: ultraChatbotAgentCleanupCronScheduleUtc,\n });\n } catch (error) {\n return Response.json(\n {\n error:\n error instanceof Error\n ? error.message\n : \"Ultra-chatbot-agent cleanup failed.\",\n },\n { status: 500 }\n );\n }\n}\n", "type": "registry:page", "target": "app/api/cron/ultra-chatbot-agent-cleanup/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/[id]/capabilities/route.ts", "content": "import { handleUltraChatbotAgentCapabilitySettingsPatchRequest } from \"@/lib/ultra-chatbot-agent/server/capability-settings\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\ninterface RouteContext {\n params: Promise<{\n id: string;\n }>;\n}\n\nexport async function PATCH(request: Request, context: RouteContext) {\n const { id } = await context.params;\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentCapabilitySettingsPatchRequest(request, {\n chatId: id,\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/[id]/capabilities/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/[id]/messages/route.ts", "content": "import { handleUltraChatbotAgentMessageEditRequest } from \"@/lib/ultra-chatbot-agent/server/message-edit\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\ninterface RouteContext {\n params: Promise<{\n id: string;\n }>;\n}\n\nexport async function PATCH(request: Request, context: RouteContext) {\n const { id } = await context.params;\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentMessageEditRequest(request, {\n chatId: id,\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/[id]/messages/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/[id]/route.ts", "content": "import { handleUltraChatbotAgentDeleteChatRequest } from \"@/lib/ultra-chatbot-agent/server/history\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\ninterface RouteContext {\n params: Promise<{\n id: string;\n }>;\n}\n\nexport async function DELETE(request: Request, context: RouteContext) {\n const { id } = await context.params;\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentDeleteChatRequest(id, {\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/[id]/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/[id]/session/route.ts", "content": "import { handleUltraChatbotAgentSessionRequest } from \"@/lib/ultra-chatbot-agent/server/runtime\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\nexport async function GET(\n request: Request,\n { params }: { params: Promise<{ id: string }> }\n) {\n const { id } = await params;\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentSessionRequest(id, {\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/[id]/session/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/[id]/stream/route.ts", "content": "import { handleUltraChatbotAgentStreamResumeRequest } from \"@/lib/ultra-chatbot-agent/server/runtime\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\nexport async function GET(\n request: Request,\n { params }: { params: Promise<{ id: string }> }\n) {\n const { id } = await params;\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentStreamResumeRequest(id, {\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/[id]/stream/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/[id]/visibility/route.ts", "content": "import { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\nimport { handleUltraChatbotAgentVisibilityPatchRequest } from \"@/lib/ultra-chatbot-agent/server/visibility\";\n\ninterface RouteContext {\n params: Promise<{\n id: string;\n }>;\n}\n\nexport async function PATCH(request: Request, context: RouteContext) {\n const { id } = await context.params;\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentVisibilityPatchRequest(request, {\n chatId: id,\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/[id]/visibility/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/document/route.ts", "content": "import { handleUltraChatbotAgentDocumentRequest } from \"@/lib/ultra-chatbot-agent/server/documents\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\nexport async function GET(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentDocumentRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n\nexport async function POST(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentDocumentRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n\nexport async function DELETE(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentDocumentRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/document/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/files/upload/route.ts", "content": "import { handleUltraChatbotAgentFileUploadRequest } from \"@/lib/ultra-chatbot-agent/server/upload\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\nexport async function POST(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (ownedRequest, viewer) =>\n handleUltraChatbotAgentFileUploadRequest(ownedRequest, {\n visitorId: viewer.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/files/upload/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/history/route.ts", "content": "import {\n handleUltraChatbotAgentDeleteHistoryRequest,\n handleUltraChatbotAgentHistoryRequest,\n} from \"@/lib/ultra-chatbot-agent/server/history\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\nexport async function GET(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentHistoryRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n\nexport async function DELETE(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentDeleteHistoryRequest({\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/history/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/mcp/project-docs/route.ts", "content": "import { handleProjectDocsMcpRequest } from \"@/lib/ultra-chatbot-agent/project-docs-mcp/project-mcp-server\";\n\nexport const runtime = \"nodejs\";\n\nexport function DELETE(request: Request) {\n return handleProjectDocsMcpRequest(request);\n}\n\nexport function GET(request: Request) {\n return handleProjectDocsMcpRequest(request);\n}\n\nexport function POST(request: Request) {\n return handleProjectDocsMcpRequest(request);\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/mcp/project-docs/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/models/route.ts", "content": "import { getUltraChatbotAgentModelCatalog } from \"@/lib/ultra-chatbot-agent/server/models\";\n\nexport async function GET() {\n return Response.json(\n {\n models: getUltraChatbotAgentModelCatalog(),\n },\n {\n headers: {\n \"Cache-Control\": \"public, max-age=86400, s-maxage=86400\",\n },\n }\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/models/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/route.ts", "content": "import { handleUltraChatbotAgentChatRequest } from \"@/lib/ultra-chatbot-agent/server/runtime\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\nexport async function POST(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentChatRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/suggestions/route.ts", "content": "import { handleUltraChatbotAgentSuggestionsRequest } from \"@/lib/ultra-chatbot-agent/server/suggestions\";\nimport { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\n\nexport async function GET(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentSuggestionsRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/suggestions/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/api/demos/ultra-chatbot-agent/vote/route.ts", "content": "import { handleUltraChatbotAgentVisitorRequest } from \"@/lib/ultra-chatbot-agent/server/viewer-context\";\nimport {\n handleUltraChatbotAgentVoteListRequest,\n handleUltraChatbotAgentVotePatchRequest,\n} from \"@/lib/ultra-chatbot-agent/server/votes\";\n\nexport async function GET(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentVoteListRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n\nexport async function PATCH(request: Request) {\n return handleUltraChatbotAgentVisitorRequest(\n request,\n async (_request, visitor) =>\n handleUltraChatbotAgentVotePatchRequest(request, {\n visitorId: visitor.visitorId,\n })\n );\n}\n", "type": "registry:page", "target": "app/api/demos/ultra-chatbot-agent/vote/route.ts" }, { "path": "registry/ultra-chatbot-agent/app/demos/ultra-chatbot-agent/[id]/page.tsx", "content": "import { notFound } from \"next/navigation\";\n\nimport { loadUltraChatbotAgentScreenData } from \"@/lib/ultra-chatbot-agent/server/session\";\nimport { UltraChatbotAgentScreen } from \"@/components/ultra-chatbot-agent/ultra-chatbot-agent-screen\";\n\nexport default async function UltraChatbotAgentConversationPage({\n params,\n}: {\n params: Promise<{ id: string }>;\n}) {\n const { id } = await params;\n const screenData = await loadUltraChatbotAgentScreenData({\n chatId: id,\n });\n\n if (!screenData.initialSession) {\n notFound();\n }\n\n return ;\n}\n", "type": "registry:page", "target": "app/demos/ultra-chatbot-agent/[id]/page.tsx" }, { "path": "registry/ultra-chatbot-agent/app/demos/ultra-chatbot-agent/page.tsx", "content": "import { loadUltraChatbotAgentScreenData } from \"@/lib/ultra-chatbot-agent/server/session\";\nimport { UltraChatbotAgentScreen } from \"@/components/ultra-chatbot-agent/ultra-chatbot-agent-screen\";\n\nexport const dynamic = \"force-dynamic\";\n\nexport default async function UltraChatbotAgentPage() {\n const screenData = await loadUltraChatbotAgentScreenData({\n chatId: null,\n });\n\n return ;\n}\n", "type": "registry:page", "target": "app/demos/ultra-chatbot-agent/page.tsx" }, { "path": "registry/ultra-chatbot-agent/components/ai-elements/code-block.tsx", "content": "\"use client\";\n\n/* eslint-disable react-hooks/refs */\n\nimport { Button } from \"@/components/ui/button\";\nimport {\n Select,\n SelectContent,\n SelectItem,\n SelectTrigger,\n SelectValue,\n} from \"@/components/ui/select\";\nimport { cn } from \"@/lib/utils\";\nimport { CheckIcon, CopyIcon } from \"lucide-react\";\nimport type { ComponentProps, CSSProperties, HTMLAttributes } from \"react\";\nimport {\n createContext,\n memo,\n useCallback,\n useContext,\n useEffect,\n useMemo,\n useRef,\n useState,\n} from \"react\";\nimport type {\n BundledLanguage,\n BundledTheme,\n HighlighterGeneric,\n ThemedToken,\n} from \"shiki\";\nimport { createHighlighter } from \"shiki\";\n\n// Shiki uses bitflags for font styles: 1=italic, 2=bold, 4=underline\n// oxlint-disable-next-line eslint(no-bitwise)\nconst isItalic = (fontStyle: number | undefined) => fontStyle && fontStyle & 1;\n// oxlint-disable-next-line eslint(no-bitwise)\nconst isBold = (fontStyle: number | undefined) => fontStyle && fontStyle & 2;\nconst isUnderline = (fontStyle: number | undefined) =>\n // oxlint-disable-next-line eslint(no-bitwise)\n fontStyle && fontStyle & 4;\n\n// Transform tokens to include pre-computed keys to avoid noArrayIndexKey lint\ninterface KeyedToken {\n token: ThemedToken;\n key: string;\n}\ninterface KeyedLine {\n tokens: KeyedToken[];\n key: string;\n}\n\nconst addKeysToTokens = (lines: ThemedToken[][]): KeyedLine[] =>\n lines.map((line, lineIdx) => ({\n key: `line-${lineIdx}`,\n tokens: line.map((token, tokenIdx) => ({\n key: `line-${lineIdx}-${tokenIdx}`,\n token,\n })),\n }));\n\n// Token rendering component\nconst TokenSpan = ({ token }: { token: ThemedToken }) => (\n \n {token.content}\n \n);\n\n// Line number styles using CSS counters\nconst LINE_NUMBER_CLASSES = cn(\n \"block\",\n \"before:content-[counter(line)]\",\n \"before:inline-block\",\n \"before:[counter-increment:line]\",\n \"before:w-8\",\n \"before:mr-4\",\n \"before:text-right\",\n \"before:text-muted-foreground/50\",\n \"before:font-mono\",\n \"before:select-none\"\n);\n\n// Line rendering component\nconst LineSpan = ({\n keyedLine,\n showLineNumbers,\n}: {\n keyedLine: KeyedLine;\n showLineNumbers: boolean;\n}) => (\n \n {keyedLine.tokens.length === 0\n ? \"\\n\"\n : keyedLine.tokens.map(({ token, key }) => (\n \n ))}\n \n);\n\n// Types\ntype CodeBlockProps = HTMLAttributes & {\n code: string;\n language: BundledLanguage;\n showLineNumbers?: boolean;\n};\n\ninterface TokenizedCode {\n tokens: ThemedToken[][];\n fg: string;\n bg: string;\n}\n\ninterface CodeBlockContextType {\n code: string;\n}\n\n// Context\nconst CodeBlockContext = createContext({\n code: \"\",\n});\n\n// Highlighter cache (singleton per language)\nconst highlighterCache = new Map<\n string,\n Promise>\n>();\n\n// Token cache\nconst tokensCache = new Map();\n\n// Subscribers for async token updates\nconst subscribers = new Map void>>();\n\nconst getTokensCacheKey = (code: string, language: BundledLanguage) => {\n const start = code.slice(0, 100);\n const end = code.length > 100 ? code.slice(-100) : \"\";\n return `${language}:${code.length}:${start}:${end}`;\n};\n\nconst getHighlighter = (\n language: BundledLanguage\n): Promise> => {\n const cached = highlighterCache.get(language);\n if (cached) {\n return cached;\n }\n\n const highlighterPromise = createHighlighter({\n langs: [language],\n themes: [\"github-light\", \"github-dark\"],\n });\n\n highlighterCache.set(language, highlighterPromise);\n return highlighterPromise;\n};\n\n// Create raw tokens for immediate display while highlighting loads\nconst createRawTokens = (code: string): TokenizedCode => ({\n bg: \"transparent\",\n fg: \"inherit\",\n tokens: code.split(\"\\n\").map((line) =>\n line === \"\"\n ? []\n : [\n {\n color: \"inherit\",\n content: line,\n } as ThemedToken,\n ]\n ),\n});\n\n// Synchronous highlight with callback for async results\nexport const highlightCode = (\n code: string,\n language: BundledLanguage,\n // oxlint-disable-next-line eslint-plugin-promise(prefer-await-to-callbacks)\n callback?: (result: TokenizedCode) => void\n): TokenizedCode | null => {\n const tokensCacheKey = getTokensCacheKey(code, language);\n\n // Return cached result if available\n const cached = tokensCache.get(tokensCacheKey);\n if (cached) {\n return cached;\n }\n\n // Subscribe callback if provided\n if (callback) {\n if (!subscribers.has(tokensCacheKey)) {\n subscribers.set(tokensCacheKey, new Set());\n }\n subscribers.get(tokensCacheKey)?.add(callback);\n }\n\n // Start highlighting in background - fire-and-forget async pattern\n getHighlighter(language)\n // oxlint-disable-next-line eslint-plugin-promise(prefer-await-to-then)\n .then((highlighter) => {\n const availableLangs = highlighter.getLoadedLanguages();\n const langToUse = availableLangs.includes(language) ? language : \"text\";\n\n const result = highlighter.codeToTokens(code, {\n lang: langToUse,\n themes: {\n dark: \"github-dark\",\n light: \"github-light\",\n },\n });\n\n const tokenized: TokenizedCode = {\n bg: result.bg ?? \"transparent\",\n fg: result.fg ?? \"inherit\",\n tokens: result.tokens,\n };\n\n // Cache the result\n tokensCache.set(tokensCacheKey, tokenized);\n\n // Notify all subscribers\n const subs = subscribers.get(tokensCacheKey);\n if (subs) {\n for (const sub of subs) {\n sub(tokenized);\n }\n subscribers.delete(tokensCacheKey);\n }\n })\n // oxlint-disable-next-line eslint-plugin-promise(prefer-await-to-then), eslint-plugin-promise(prefer-await-to-callbacks)\n .catch((error) => {\n console.error(\"Failed to highlight code:\", error);\n subscribers.delete(tokensCacheKey);\n });\n\n return null;\n};\n\nconst CodeBlockBody = memo(\n ({\n tokenized,\n showLineNumbers,\n className,\n }: {\n tokenized: TokenizedCode;\n showLineNumbers: boolean;\n className?: string;\n }) => {\n const preStyle = useMemo(\n () => ({\n backgroundColor: tokenized.bg,\n color: tokenized.fg,\n }),\n [tokenized.bg, tokenized.fg]\n );\n\n const keyedLines = useMemo(\n () => addKeysToTokens(tokenized.tokens),\n [tokenized.tokens]\n );\n\n return (\n \n \n {keyedLines.map((keyedLine) => (\n \n ))}\n \n \n );\n },\n (prevProps, nextProps) =>\n prevProps.tokenized === nextProps.tokenized &&\n prevProps.showLineNumbers === nextProps.showLineNumbers &&\n prevProps.className === nextProps.className\n);\n\nCodeBlockBody.displayName = \"CodeBlockBody\";\n\nexport const CodeBlockContainer = ({\n className,\n language,\n style,\n ...props\n}: HTMLAttributes & { language: string }) => (\n \n);\n\nexport const CodeBlockHeader = ({\n children,\n className,\n ...props\n}: HTMLAttributes) => (\n \n {children}\n \n);\n\nexport const CodeBlockTitle = ({\n children,\n className,\n ...props\n}: HTMLAttributes) => (\n
\n {children}\n
\n);\n\nexport const CodeBlockFilename = ({\n children,\n className,\n ...props\n}: HTMLAttributes) => (\n \n {children}\n \n);\n\nexport const CodeBlockActions = ({\n children,\n className,\n ...props\n}: HTMLAttributes) => (\n \n {children}\n \n);\n\nexport const CodeBlockContent = ({\n code,\n language,\n showLineNumbers = false,\n}: {\n code: string;\n language: BundledLanguage;\n showLineNumbers?: boolean;\n}) => {\n // Memoized raw tokens for immediate display\n const rawTokens = useMemo(() => createRawTokens(code), [code]);\n\n // Synchronous cache lookup — avoids setState in effect for cached results\n const syncTokens = useMemo(\n () => highlightCode(code, language) ?? rawTokens,\n [code, language, rawTokens]\n );\n\n // Async highlighting result (populated after shiki loads)\n const [asyncTokens, setAsyncTokens] = useState(null);\n const asyncKeyRef = useRef({ code, language });\n\n // Invalidate stale async tokens synchronously during render\n if (\n asyncKeyRef.current.code !== code ||\n asyncKeyRef.current.language !== language\n ) {\n asyncKeyRef.current = { code, language };\n setAsyncTokens(null);\n }\n\n useEffect(() => {\n let cancelled = false;\n\n highlightCode(code, language, (result) => {\n if (!cancelled) {\n setAsyncTokens(result);\n }\n });\n\n return () => {\n cancelled = true;\n };\n }, [code, language]);\n\n const tokenized = asyncTokens ?? syncTokens;\n\n return (\n
\n \n
\n );\n};\n\nexport const CodeBlock = ({\n code,\n language,\n showLineNumbers = false,\n className,\n children,\n ...props\n}: CodeBlockProps) => {\n const contextValue = useMemo(() => ({ code }), [code]);\n\n return (\n \n \n {children}\n \n \n \n );\n};\n\nexport type CodeBlockCopyButtonProps = ComponentProps & {\n onCopy?: () => void;\n onError?: (error: Error) => void;\n timeout?: number;\n};\n\nexport const CodeBlockCopyButton = ({\n onCopy,\n onError,\n timeout = 2000,\n children,\n className,\n ...props\n}: CodeBlockCopyButtonProps) => {\n const [isCopied, setIsCopied] = useState(false);\n const timeoutRef = useRef(0);\n const { code } = useContext(CodeBlockContext);\n\n const copyToClipboard = useCallback(async () => {\n if (typeof window === \"undefined\" || !navigator?.clipboard?.writeText) {\n onError?.(new Error(\"Clipboard API not available\"));\n return;\n }\n\n try {\n if (!isCopied) {\n await navigator.clipboard.writeText(code);\n setIsCopied(true);\n onCopy?.();\n timeoutRef.current = window.setTimeout(\n () => setIsCopied(false),\n timeout\n );\n }\n } catch (error) {\n onError?.(error as Error);\n }\n }, [code, onCopy, onError, timeout, isCopied]);\n\n useEffect(\n () => () => {\n window.clearTimeout(timeoutRef.current);\n },\n []\n );\n\n const Icon = isCopied ? CheckIcon : CopyIcon;\n\n return (\n \n {children ?? }\n \n );\n};\n\nexport type CodeBlockLanguageSelectorProps = ComponentProps;\n\nexport const CodeBlockLanguageSelector = (\n props: CodeBlockLanguageSelectorProps\n) =>