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openai-api-troubleshooting

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.

80

Quality

100%

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SKILL.md
Quality
Evals
Security

Quality

Content

100%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The skill body is a concise, actionable routing decision tree with concrete codes, explicit checkpoints, and a well-structured single reference. It scores top marks on every content dimension.

DimensionReasoningScore

Conciseness

The body is lean and routing-focused with no padding about what the OpenAI API is or how errors work; every line earns its place and it assumes Claude's competence.

3 / 3

Actionability

Concrete error codes (401, invalid_api_key, insufficient_quota, rate_limit_exceeded, 403, model_not_found), a specific rerun directive (sandbox_permissions=require_escalated), and exact billing/limits URLs make the guidance directly executable rather than descriptive.

3 / 3

Workflow Clarity

A numbered routing sequence (1-5) with an explicit checkpoint (rerun, then if a real API response is returned, continue below) and a Rules section disambiguating overlapping cases provides clear sequencing with feedback for error recovery.

3 / 3

Progressive Disclosure

Content is organized into Routing, Rules, and References sections, with a single one-level-deep, clearly signaled reference (references/evals.md) that exists as a real file; navigation is easy.

3 / 3

Total

12

/

12

Passed

Description

100%Weight 40%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, well-triggered, complete, and clearly distinguished from sibling skills via explicit delegation. It earns top marks across all dimensions.

DimensionReasoningScore

Specificity

Names concrete actions ("classify the likely cause, explain the next step, and route to the right follow-up") and enumerates specific failure classes (blocked network, invalid credentials, quota/credits, rate limits, model/project/org access), matching the multiple-specific-actions anchor.

3 / 3

Completeness

Explicitly answers both what (classify, explain next step, route to follow-up) and when ("Use when an OpenAI API request fails..."), satisfying the explicit-trigger anchor for the top level.

3 / 3

Trigger Term Quality

Natural user-facing terms like "OpenAI API request fails", "invalid credentials", "rate limits", and "exhausted API quota or credits" are phrased as users would say them; voice is third person, so no specificity penalty applies.

3 / 3

Distinctiveness Conflict Risk

Scoped to runtime OpenAI API failures and explicitly delegates key provisioning to openai-platform-api-key and docs to openai-docs, giving it a clear niche unlikely to trigger the wrong skill.

3 / 3

Total

12

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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