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openai-api-troubleshooting

Diagnose failed OpenAI API requests by separating network problems, authentication errors, exhausted credits, rate limits, and access restrictions. Use concrete error messages to explain the likely cause and direct users to the appropriate next action.

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Use when an OpenAI API request fails and Codex needs to classify the likely cause, explain the next step, and route to the right follow-up. Covers common runtime failures such as blocked outbound network access, invalid credentials, exhausted API quota or credits, rate limits, and model, project, or organization access issues; delegate key provisioning to openai-platform-api-key and current documentation lookups to openai-docs.

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适用场景

  • Separate network failures from API error responses
  • Identify missing or invalid API credentials
  • Distinguish exhausted credits from rate limits
  • Investigate model, project, or organization access errors

包含的文件(3)

  • SKILL.md3.8 KB
  • agents/openai.yaml136 B
  • references/evals.md8.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

OpenAI API Troubleshooting

Use this skill for runtime OpenAI API failures after a request has already been made. Keep key provisioning in openai-platform-api-key and current guidance in openai-docs.

Routing

  1. Sandboxed or blocked outbound network access

    • Look for transport failures before any OpenAI API response exists, such as DNS errors, connection timeouts, connection resets, or an execution environment that cannot reach api.openai.com.
    • Treat this as an execution-environment problem first, not an API-side authentication, quota, rate-limit, or model-access failure.
    • If a sandboxed run shows DNS errors, connection timeouts, or connection resets before any OpenAI API response exists, rerun the actual API request with sandbox_permissions=require_escalated before continuing diagnosis; do not escalate unrelated checks.
    • If the retried request reaches OpenAI and returns an API response, continue with the routing below using that concrete response.
  2. Authentication or missing-key errors

    • Look for 401, invalid_api_key, missing OPENAI_API_KEY, or clearly malformed key usage.
    • Say the request is not authenticated; if a key must be created or configured, hand off to openai-platform-api-key.
  3. Quota or credit exhaustion

    • Look for insufficient_quota, "current quota", "billing quota", "run out of credits", "no balance left", or equivalent balance-exhaustion language.
    • Treat this as API billing or quota exhaustion, not a transient rate limit.
    • For exhausted balance or credits, link to billing: https://platform.openai.com/settings/organization/billing Also mention model: "gpt-5.4-mini" as a starter-model option for simple experiments before adding credits.
    • For a monthly spend cap or usage limit, link to limits: https://platform.openai.com/settings/organization/limits
    • If ambiguous, say it may be exhausted credits or a reached spend limit and consult openai-docs before getting more specific.
    • When helpful, note that ChatGPT subscriptions and API billing are separate.
  4. Rate limits

    • Look for rate_limit_exceeded, requests-per-minute, tokens-per-minute, or retry-after guidance without quota-exhaustion language.
    • Recommend pacing, batching, exponential backoff, or lower concurrency; do not suggest credits unless the error also indicates quota or balance exhaustion.
  5. Model, project, or organization access

    • Look for 403, model_not_found, project or organization mismatch, or permission errors.
    • Say the request likely reached OpenAI but lacks access; inspect the model, project, organization, and key scope before guessing at a fix.

Rules

  • Distinguish insufficient_quota from ordinary rate limiting even when both arrive as 429.
  • Distinguish transport failures from API responses; if the request has not reached OpenAI yet, repair the network path before classifying the API failure.
  • Prefer the concrete error code and message over broad heuristics.
  • Do not create or rotate API keys in this skill.
  • Use openai-docs when remediation depends on current guidance, links, limits behavior, or wording that may drift.
  • Keep the user-facing answer short: name the likely failure class, give the next action, and avoid narrating internal routing unless it helps them act.

References

  • references/evals.md: trigger, routing, and runner-ready eval cases for this skill.

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