Skip to main content
skill CX Codex GP ChatGPT official · OpenAI

chatgpt-app-submission — Codex skill: installation

Inspects a ChatGPT Apps MCP server and prepares the submission JSON. Use it before review to collect app info, test cases, and findings.

Install into Codex · Skills CLI (Vercel) All methods and platforms ↓
npx skills add openai/plugins --skill chatgpt-app-submission -a codex
Open on GitHub

What chatgpt-app-submission does

The skill inspects an MCP server codebase in the current working directory. It reads project and package metadata, README files, manifests, tool descriptors, resource templates, and widget metadata, then compares each tool's implementation with its readOnlyHint, openWorldHint, destructiveHint, description, name, and CSP values.

It writes chatgpt-app-submission.json with App Info suggestions, tool-hint justifications, five positive test cases, and three negative test cases. It also reports review-check findings and tools that omit outputSchema. When annotations, descriptions, or CSP values conflict with the code, developer approval is required before source changes.

Install it when you are preparing a ChatGPT App backed by MCP and need a code-based submission check. It is a poor fit for unrelated repository reviews.

What it helps with

  • inspect an MCP server before ChatGPT App submission
  • generate chatgpt-app-submission.json from the repository
  • compare tool hints with actual side effects
  • prepare positive and negative review test cases
  • flag tools that lack outputSchema

Example prompts for the agent

  • Inspect the MCP server in the current directory and generate `chatgpt-app-submission.json`.
  • Compare `readOnlyHint`, `openWorldHint`, and `destructiveHint` with every tool implementation.
  • Prepare ChatGPT App review tests and report any `outputSchema` warnings.

How to install chatgpt-app-submission

1Skills CLI (Vercel)

npx skills add openai/plugins --skill chatgpt-app-submission -a codex

2Manually: put the files in place

.agents/skills/chatgpt-app-submission/SKILL.md

For all projects use ~/.agents/skills/

From the same set201

The whole set →
supabase official supabase Guides the agent through database configuration and strict RLS policies in Supabase. CX Codex GP ChatGPT 8installs remotion-render official Remotion Exports videos and static stills from Remotion projects using CLI commands. CX Codex GP ChatGPT 3installs figma-create-new-file official Figma Creates blank Figma, FigJam, or Slides files inside draft folders. It resolves planKey and editor types before invoking Figma MCP tools. CX Codex GP ChatGPT 6installs swiftui-performance-audit official OpenAI Pinpoints SwiftUI runtime issues like frame drops, unresponsive taps, and excessive view body computations. Works code-first and guides Instruments profiling. CX Codex GP ChatGPT 109installs swiftui-liquid-glass official OpenAI This skill helps build and review SwiftUI Liquid Glass interfaces for iOS 26+. Use it when adopting the API or checking fallbacks, interaction, and design fit. CX Codex GP ChatGPT 121installs swiftui-ui-patterns official OpenAI This skill helps build and refactor SwiftUI interfaces, from navigation and state to layouts and controls. Use it for new screens or changes to an existing project. CX Codex GP ChatGPT 114installs swiftui-view-refactor official OpenAI Refactors SwiftUI view files into clean, testable structures with dedicated subview types and proper Observation ownership. CX Codex GP ChatGPT 113installs ios-memgraph-leaks official OpenAI Captures and inspects iOS leaks from a simulator process or .memgraph. Useful for tracing retained objects and checking a fix with before-and-after evidence. CX Codex GP ChatGPT 1,054installs

Similar

migrating-oracle-to-postgres-data-access-code official github Moves .NET/C# data-access code from Oracle to PostgreSQL with Npgsql. Use it while migrating an application's code layer alongside its database. GitHub Copilot 10installs upstash-redis official Upstash Connect to Redis over HTTP in serverless runtimes using @upstash/redis and configure rate limiting with @upstash/ratelimit without TCP connection pooling. GitHub Copilot 7installs protobuf-grpc-api-review official github Reviews .proto and gRPC changes for format compatibility, migration risks, and RPC contract quality. Use it when changing schemas or investigating failures across client versions. GitHub Copilot 7installs mcp-builder official anthropics This skill walks through building an MCP server in TypeScript or Python, from reading the protocol spec to writing tests and evaluation questions. Claude Code Claude.ai 130,949installs google-agents-cli-adk-code official Google A reference skill for building ADK agents with tools, callbacks, state, and workflows. Use it when an agent project needs concrete API patterns or code examples. Claude Code CX Codex Cursor +1 511,400installs lark-im larksuite This skill lets an agent work with Lark IM messages, chats, files, and interactive cards. Use it when coding tasks need access to team conversations. Claude Code CX Codex Cursor +1 472,300installs lark-event larksuite Listens to Lark/Feishu events and streams them as NDJSON. Use it for bots, message processing, and long-running subscribers. Claude Code CX Codex Cursor +1 466,200installs caveman-discover JuliusBrussee Finds and labels every LLM workflow in your repository so Caveman Cloud breaks down spend by actual job rather than grouping everything into one bucket. Claude Code CX Codex Cursor +1 103,500installs

Questions about chatgpt-app-submission

How do I install chatgpt-app-submission in Codex?

Run npx skills add openai/plugins --skill chatgpt-app-submission. The skill file is placed at .agents/skills/chatgpt-app-submission/SKILL.md.

What does chatgpt-app-submission do?

It inspects a ChatGPT Apps MCP server, creates chatgpt-app-submission.json, prepares test cases and tool-hint justifications, and reports review findings.

How many test cases does the skill create?

It generates exactly five positive and three negative test cases. Positive cases use exact MCP action names in tools_triggered.

Source text

SKILL.md · Apache-2.0
---
name: chatgpt-app-submission
description: Inspect a ChatGPT Apps MCP server codebase and generate chatgpt-app-submission.json with app info suggestions, tool hint justifications, test cases, and negative test cases, then report review-check findings and outputSchema warnings for submission review.
---

# ChatGPT App Submission

Use this skill when a developer needs a `chatgpt-app-submission.json` file for a ChatGPT Apps submission. The file is uploaded in the Apps submission form to fill out parts of App Info, MCP Server, and Testing.

## Workflow

1. Inspect the MCP server codebase from the current working directory.
2. Read repo metadata, package metadata, README files, app manifests, tool descriptors, resource templates, and widget metadata needed to understand the app.
3. Find every exposed MCP tool, its declared `readOnlyHint`, `openWorldHint`, and `destructiveHint` annotations, and whether it declares `outputSchema`.
4. Read each tool implementation and any called helper functions needed to understand side effects.
5. Compare tool annotations, tool names, tool descriptions, and CSP values against actual behavior. If any value is missing, stale, misleading, or inconsistent, ask the developer for approval before updating source.
6. Generate concise review-facing app info suggestions, tool hint justifications, positive test cases, and negative test cases.
7. Write `chatgpt-app-submission.json` in the current working directory.
8. Print review-check findings and any missing `outputSchema` warnings in the final response, and explain what the developer should do with each finding before submission.

Do not infer behavior from the tool name alone. Use the real tool implementation and declared annotations. If a tool calls into another module or API client, inspect enough of that path to know whether it reads, writes, deletes, sends, publishes, or changes external state.

## App Info Rules

Suggest app info from source-of-truth project metadata and the tool behavior you inspected. Keep it plain-language and submission-review-facing.

- `display_name`: use the product or app name from repo metadata, package metadata, README, manifest, or existing configuration. Keep it short enough for the submission form.
- `subtitle`: summarize what the app does in one short functional phrase, not marketing copy. It must be 30 characters or less.
- `description`: describe concrete user value and the main workflows the tools support.
- `category`: choose one of `BUSINESS`, `COLLABORATION`, `DESIGN`, `DEVELOPER_TOOLS`, `EDUCATION`, `ENTERTAINMENT`, `FINANCE`, `FOOD`, `LIFESTYLE`, `NEWS`, `PRODUCTIVITY`, `SHOPPING`, or `TRAVEL`.

## Hint Rules

Use the Apps SDK review meanings:

- `readOnlyHint`: `true` only when the tool strictly fetches, looks up, lists, retrieves, or computes data without changing state. `false` if it can create, update, delete, send, enqueue, run jobs, write logs, start workflows, or otherwise mutate state.
- `destructiveHint`: `true` if the tool can delete, overwrite, send irreversible messages or transactions, revoke access, or perform destructive admin actions, including via some modes or parameters. Otherwise `false`.
- `openWorldHint`: `true` if the tool can change publicly visible internet state or external third-party systems, such as sending emails or messages, posting/publishing content, creating public tickets/issues, pushing code/content, or submitting external forms. `false` if it only operates in closed/private systems.

ChatGPT Apps submissions require every tool to set all three hints explicitly. Missing or null hints are submission blockers, even if MCP clients may have protocol-level defaults.

If a hint is missing, null, or does not match the actual behavior you found in code, stop before writing the JSON and ask the developer for approval to update the MCP server source. In the approval request, list each affected tool, the missing/current hint value, the behavior you observed, and the recommended explicit hint value. If the developer approves, make the smallest source change that sets the correct hint explicitly, then generate JSON using the updated values. If the developer does not approve or the correct edit location is ambiguous, do not generate misleading JSON; report the mismatch and the blocked update.

## Output Schema Warnings

While inspecting exposed MCP tools, record each tool whose descriptor or source definition omits `outputSchema` or sets it to `null`. Missing `outputSchema` is not a blocker for generating `chatgpt-app-submission.json`, and the submission JSON does not include output schemas.

Do not infer or invent output schemas for this warning. Use the actual MCP tool descriptor or source definition. In the final response, include a concise warning for any missing tools: `Add an outputSchema so models can use this tool's results more reliably. See https://modelcontextprotocol.io/specification/draft/server/tools#tool.` Include the affected tool names. If every tool declares `outputSchema`, do not include an outputSchema warning.

## Tool Descriptor and CSP Rules

Check tool names, tool descriptions, and widget CSP metadata while inspecting the app.

- Tool input schemas should not solicit sensitive data unless that data is strictly necessary for the app's stated user-facing workflow. Flag fields that ask for PHI, PCI, SSNs, credentials, MFA codes, government IDs, biometrics, or similarly sensitive identifiers.
- Tool names should match the action the tool performs and should not imply capabilities the implementation does not provide.
- Tool descriptions should accurately describe inputs, side effects, and user-visible results.
- CSP values should be as narrow as the implementation supports. Flag wildcard domains, unused domains, broad resource/connect domains, and missing domains required by actual widget behavior.

If tool names, descriptions, or CSP values appear missing or inconsistent with actual behavior, prompt the developer for approval before editing source. If the developer declines or the correct edit is ambiguous, keep the generated JSON truthful and report the finding in the final response.

## Test Case Rules

Generate exactly five positive test cases and exactly three negative test cases.

- Positive test cases must use exact MCP action names in `tools_triggered`.
- Positive prompts should cover the main tool-backed workflows and edge conditions that review should exercise.
- Negative test cases should describe prompts where the app should not trigger, including nearby-but-out-of-scope requests.
- Keep expected outputs review-facing and concise. Do not include secrets, credentials, source snippets, local paths, request IDs, stack traces, or private implementation details.

## Output Contract

Write exactly one JSON file named `chatgpt-app-submission.json`:

```json
{
  "$schema": "https://developers.openai.com/apps-sdk/schemas/chatgpt-app-submission.v1.json",
  "schema_version": 1,
  "app_info": {
    "display_name": "Example App",
    "subtitle": "Find and update records",
    "description": "Example App helps users find records, inspect details, and update workspace data through ChatGPT.",
    "category": "PRODUCTIVITY"
  },
  "tools": {
    "tool_name": {
      "annotations": {
        "readOnlyHint": true,
        "openWorldHint": false,
        "destructiveHint": false
      },
      "justifications": {
        "read_only_justification": "Only retrieves matching records and does not modify data.",
        "open_world_justification": "Does not write to public internet state or third-party systems.",
        "destructive_justification": "Does not delete, overwrite, revoke access, or perform irreversible actions."
      }
    }
  },
  "test_cases": [
    {
      "description": "Find records that match a specific user request.",
      "user_prompt": "Find my open records for this week.",
      "file_attachment_urls": null,
      "tools_triggered": "tool_name",
      "expected_output": "Returns matching records with enough detail for the user to choose the next action.",
      "expected_output_url": null
    }
  ],
  "negative_test_cases": [
    {
      "description": "Do not trigger for unrelated calendar requests.",
      "user_prompt": "What meetings do I have tomorrow?",
      "file_attachment_urls": null,
      "tools_triggered": null,
      "expected_output": "The app should not be invoked because the request is outside its supported workflows.",
      "expected_output_url": null
    }
  ]
}
```

`$schema` identifies the import file shape for editors and importers; Codex does not need to fetch it. `tools` is required. `app_info`, `test_cases`, and `negative_test_cases` are optional in the schema, but generate them whenever the repo contains enough information. Do not include review-check findings in this JSON file.

## Writing Justifications

- Keep each justification to one sentence.
- Be specific about the actual behavior, not the annotation itself.
- For write tools, state what system is changed and whether the change is bounded/private or public/external.
- For destructive tools, name the irreversible action and mention any real safeguard only if it exists in the code.
- Do not include source snippets, secrets, tokens, request IDs, local paths, stack traces, or private implementation details in the JSON.

Good examples:

- `Only retrieves project metadata and returns it without creating or updating records.`
- `Creates a private task in the user's workspace and cannot publish content to public URLs.`
- `Deletes the selected workspace document, which cannot be recovered after confirmation.`

Bad examples:

- `readOnlyHint is true because the tool is read-only.`
- `Probably safe.`
- `The function calls client.delete_item(...) in src/server.py.`

## Reporting Review Checks

Report these checks in the final response after writing `chatgpt-app-submission.json`. Do not write them into the JSON file.

- Sensitive data solicitation: flag tool input schema fields that request PHI, PCI, SSNs, credentials, MFA codes, government IDs, biometrics, or similarly sensitive identifiers. Include the tool name and input field in the finding.
- Tool data use: flag tools that collect, expose, mutate, or transmit sensitive data in a way the descriptor or tests do not clearly explain.
- Tool naming: flag names or descriptions that are too vague, misleading, overbroad, or inconsistent with implementation behavior.
- Weak CSPs: flag broad, wildcard, unused, or missing CSP domains in widget metadata.

For each finding, explain the practical next step: update source, update submission copy, narrow CSP, remove or justify a sensitive input, or manually review before submitting. If there are no findings, say that these checks did not find obvious issues from source inspection.

## Final Response

After writing the file, summarize the app info fields generated, number of tools covered, positive test case count, and negative test case count. Then include a `Review findings` section with any sensitive data solicitation, tool data use, tool naming, weak CSP findings, or missing `outputSchema` warnings and what to do with each one. If generation is blocked, lead with the exact missing hints or source ambiguity.

© OpenAI · Apache-2.0 · openai/plugins

See also

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor