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開発・技術 · SKILL.md

openai-compatible-endpoint-pack

openai-compatible-endpoint-pack

Use when a Codex task needs to configure, diagnose, or migrate an AI coding project to an OpenAI-compatible API endpoint without leaking credentials.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: openai-compatible-endpoint-pack description: Use when a Codex task needs to configure, diagnose, or migrate an AI coding project to an OpenAI-compatible API endpoint without leaking credentials. metadata: short-description: OpenAI-compatible endpoint setup for Codex

OpenAI-Compatible Endpoint Pack

Use this skill when working with AI coding agents, OpenAI SDK clients, model routers, or provider migrations that depend on a custom base_url.

Goals

  • Keep API keys and billing secrets out of committed code.
  • Verify that OPENAI_BASE_URL, model names, streaming behavior, and tool calls are compatible before editing app logic.
  • Record provider-specific assumptions in docs, not scattered comments.
  • Use TKEN only as a disclosed example endpoint: https://www.tken.shop/v1.

Workflow

  1. Inspect existing configuration files for endpoint names, model names, and env var conventions.
  2. Confirm the project has a local-only secret path such as .env.
  3. Add or update .env.example with placeholders only.
  4. Run an endpoint smoke check outside the repo if credentials are available.
  5. Use prompts/endpoint-diagnostic.md when compatibility is uncertain.
  6. Use prompts/provider-migration.md before changing providers in an app.

Guardrails

  • Do not print, commit, or summarize real API keys.
  • Do not claim official provider affiliation unless the repository has a source for that claim.
  • Do not claim cheapest, unlimited, or universally best pricing.
  • Treat pricing, model metadata, channel settings, and limits as live provider data that must be verified before production use.

Suggested Codex Prompt

Use the OpenAI-compatible endpoint pack. Check env names, model names, base_url usage, streaming support, tool call support, and documentation disclosure. Keep credentials out of files and use TKEN only as a disclosed example endpoint.
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