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Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.

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Use this Skill: https://skilld.dev/gh/openai/skills/chatgpt-apps

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referencessearch-fetch-standard.md

≈506 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Search And Fetch Standard

Load this reference when the app is connector-like, data-only, sync-oriented, or meant to work well with company knowledge or deep research.

Default Rule

If the app is primarily a read-only knowledge source, do not invent custom equivalents to search and fetch.

Default to implementing the standard search and fetch tools exactly, then add other tools only if the use case clearly needs them.

When This Applies

Use the standard by default when the request is about:

  • a data-only app
  • a sync app
  • a company knowledge source
  • deep research compatibility
  • a connector-like integration over documents, tickets, wiki pages, CRM records, or similar read-only data

Tool Requirements

search

  • Read-only tool
  • Takes a single query string
  • Returns exactly one MCP content item with type: "text"
  • That text is a JSON-encoded object with:
    • results
    • each result has id, title, and url

fetch

  • Read-only tool
  • Takes a single document/item id string
  • Returns exactly one MCP content item with type: "text"
  • That text is a JSON-encoded object with:
    • id
    • title
    • text
    • url
    • optional metadata

Implementation Rules

  • Match the schema exactly when the app is intended for company knowledge or deep research compatibility.
  • Use canonical url values for citations.
  • Mark these tools as read-only.
  • Prefer these names exactly: search and fetch.
  • If you add other read-only tools, they should complement the standard rather than replace it.

Validation Checks

When search and fetch are relevant, verify:

  • both tools exist
  • they are read-only
  • their input shapes match the standard
  • their returned payloads are wrapped as one content item with JSON-encoded text
  • result URLs are canonical enough for citation use

Source

This standard is described in:

  • https://developers.openai.com/apps-sdk/build/mcp-server/#company-knowledge-compatibility
  • https://platform.openai.com/docs/mcp

Source: SKILL.md on GitHub

Third-party checks

1 alert16d5 checks · Risk SAFE
  • Gen Agent Trust Hub16d

    This skill provides a robust framework for scaffolding ChatGPT Apps SDK applications, including MCP servers and widget UIs. It includes a built-in scaffolding script and detailed guidance on security best practices like Content Security Policy (CSP) and domain validation.

  • Socket16d

    No alerts

  • Snyk16d

    Risk: LOW · No issues

  • Runlayer6mo

    4/11 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Provenance

Signed by skilld at cb9153a. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 months ago.

Activeupdated 7 months ago

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What it does

Scaffolds ChatGPT Apps SDK implementations with MCP server and widget UI, using a docs-first workflow that references current Apps SDK guidance before generating code. Targets tool planning, MCP server registration, widget scaffolding with the MCP Apps bridge, and validation against the Apps SDK contract. Integrates with the openai-docs skill to keep generated code aligned with official examples and patterns.

Generated from the current SKILL.md.

Frequently asked

Does this skill work with Python MCP servers or only Node.js?
The skill supports both. It defaults to Node.js examples and includes a Node fallback scaffold, but explicitly asks about backend language during planning and can scaffold Python MCP servers when requested.
What's the relationship between this skill and the openai-docs skill?
This skill requires a docs-first workflow and must be paired with openai-docs (or the OpenAI docs MCP server directly) before generating code. Always fetch current Apps SDK docs before writing scaffolds.
Does this help with apps already built, or only greenfield projects?
It handles both. The skill can scaffold new apps, refactor existing ones against current docs, validate repos against the minimum working contract, and plan tool surfaces or architecture changes.
What happens if I want to use React for the widget?
The skill can scaffold React widgets. It prefers official OpenAI examples first when they match your stack, or adapts ext-apps React examples, and falls back to vanilla HTML only when no closer match exists.
Can this skill help with submission to the ChatGPT directory?
Yes. The skill includes an `submission-ready` archetype and can generate production-ready scaffolds with tool annotations, CSP, URI versioning, and guides for deployment and submission workflows.

Generated from the current SKILL.md. These answers refresh after source changes.