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check-pr

Check a GitHub, GitLab, or Perforce PR/MR/CL for review comments, failing checks, and PR-body gaps. Use when asked to inspect, fix, or prepare a change for submission.

68

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

Highly actionable, executable content with strong sequenced workflow and validation checkpoints. The main weakness is conciseness and progressive disclosure: the large inline Greptile-freshness logic and platform-variant duplication bloat the body.

Suggestions

Move the verbose Greptile-freshness gating logic (section 4) and its GitHub/GitLab/Perforce variants into a dedicated reference file, keeping only the decision rule and link inline.

Consolidate the repeated per-platform command blocks (sections 1-2) into a compact table of equivalent field names and commands rather than restating each platform separately.

Trim inline rationale sentences like 'This is especially important after pushing a new commit' that restate context Claude can infer.

DimensionReasoningScore

Conciseness

Assumes Claude's competence (no explaining what CI/PRs are) and provides executable commands, but the long Greptile-freshness section repeats rationale and parallels across GitHub/GitLab/Perforce and could be tightened.

2 / 3

Actionability

Fully executable gh/glab/p4/jq commands with concrete field names and conclusion enums, copy-paste ready throughout, matching the 'fully executable code/commands' anchor.

3 / 3

Workflow Clarity

Clear 0-10 numbered sequence with explicit validation checkpoints (poll to terminal state, stale-head gating) and fix-push-re-run feedback loops for risky review operations.

3 / 3

Progressive Disclosure

Two genuine one-level-deep references (graphql-queries.md, gitlab-api.md) are clearly signaled with markdown links, but the SKILL.md body itself is a long monolithic wall of inline bash/jq that could be offloaded.

2 / 3

Total

10

/

12

Passed

Description

85%

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

A strong, third-person description that clearly states both capabilities and a 'Use when' trigger clause covering three VCS platforms. Trigger term coverage could be slightly broader with more colloquial phrasings.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('review comments, failing checks, and PR-body gaps') across GitHub/GitLab/Perforce, matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly states what it does (check PR/MR/CL for comments/checks/gaps) and when ('Use when asked to inspect, fix, or prepare a change for submission'), satisfying the 'what AND when with explicit triggers' anchor.

3 / 3

Trigger Term Quality

Includes natural triggers ('inspect, fix, or prepare a change for submission') but the verbs are fairly generic and miss common variations like 'check my PR' or 'review my merge request'.

2 / 3

Distinctiveness Conflict Risk

The multi-platform PR/MR/CL review niche with explicit Greptile-freshness handling is a clear, distinct trigger set unlikely to conflict with other skills.

3 / 3

Total

11

/

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
paperclipai/paperclip
Reviewed

Table of Contents

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