autofix

Apply approved fixes for unresolved CodeRabbit review comments, Codex P1-P3 findings, PR feedback, and code review issues with validation evidence. Use when asked to address review comments, fix review findings, clear unresolved comments, or autofix PR feedback.

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Quality

Content

77%

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

The body is concise, well-sequenced, and validation-rich, with genuine bundle-file references. It loses points for actionability (no executable commands) and for progressive disclosure (several referenced Infrastructure paths are missing).

Suggestions

Add at least one concrete, executable validation command example (e.g., the actual CodeRabbit CLI invocation or test command) to lift actionability from abstract to copy-paste ready.

Fix or remove the broken Progressive Disclosure references to Infrastructure/references/openai-cookbook-expert-lens-pack.md, openai-cookbook-skill-expertise-map.md, and Infrastructure/references/deferred-skill-context/agent-ops-autofix/, which do not exist in the bundle.

Verify every path cited under Progressive Disclosure resolves to a real file so navigation is one level deep and trustworthy.

Dimension	Reasoning	Score
Conciseness	Lean imperative body with no padding or explanation of concepts Claude already knows; each section earns its place, matching the 'lean and efficient' anchor.	3 / 3
Actionability	Concrete normalization rules and numbered steps are present, but it is instruction-only with no executable commands or code samples ('run scoped validation commands' is unspecified); not 3 because guidance is abstract in places, not 1 because it does instruct rather than describe.	2 / 3
Workflow Clarity	An 11-step sequenced workflow with explicit validation checkpoints (step 5 stop, step 10 run checks, 'fail fast on failed gates') and feedback loops for batch/destructive edits, matching the top anchor.	3 / 3
Progressive Disclosure	Overview points one level deep to real bundle files (contract.yaml, evals.yaml, task-profile.json, discovery-interview.md), but several referenced paths do not exist (Infrastructure/references/openai-cookbook-*.md and deferred-skill-context/agent-ops-autofix/); broken references keep it at 2 rather than 3.	2 / 3
	Total	10 / 12 Passed

Description

92%

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 concrete, complete, and trigger-rich, with an explicit 'Use when' clause and named review sources. Its only weakness is mild overlap risk from the generic 'code review issues' / 'PR feedback' phrasing.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ('Apply approved fixes', 'validation evidence') across named sources (CodeRabbit comments, Codex P1-P3 findings, PR feedback), matching the 'lists multiple specific concrete actions' anchor.	3 / 3
Completeness	Explicitly answers both what (apply approved fixes with validation evidence) and when via a clear 'Use when ...' clause, matching the top anchor; not below because neither what nor when is missing or implied.	3 / 3
Trigger Term Quality	Natural trigger phrases a user would say ('address review comments', 'fix review findings', 'clear unresolved comments', 'autofix PR feedback') give good coverage; not below 3 because common variations are present.	3 / 3
Distinctiveness Conflict Risk	CodeRabbit/Codex/P1-P3 framing is a clear niche, but 'code review issues' and 'PR feedback' are broad enough to overlap with general review skills; not 3 because of that overlap risk, not 1 because the source-specific triggers add distinction.	2 / 3
	Total	11 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: jscraik/Agent-Skills
Commit: 5a6027f

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.