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pantheon-ai/gitlab-api

Retrieve and analyze GitLab merge request comments and metadata using authenticated API calls

72

Quality

91%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Overview
Quality
Evals
Security
Files

Quality

Content

77%

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

A well-structured, actionable skill body with strong workflow validation and executable examples. Its main weaknesses are moderate verbosity in the anti-pattern sections and a referenced script that is not backed by an actual bundle file.

Suggestions

Tighten the Anti-Patterns section by collapsing the repeated WHY/BAD/GOOD scaffolding into a single compact list, keeping only the non-obvious rationale.

Provide the referenced get_mr_comments.sh inside a scripts/ bundle directory, or note explicitly that the script must be supplied externally, so the disclosure reference is real.

Trim the 'When to Examine Script Internals' paragraph — the deferral intent is already implied by giving a script location and line count.

DimensionReasoningScore

Conciseness

Mostly efficient and free of basic-concept explanation, but the repeated WHY/BAD/GOOD anti-pattern blocks and the meta 'When to Examine Script Internals' paragraph could be tightened without losing value.

2 / 3

Actionability

Provides fully executable bash invocation lines, concrete examples, explicit exit codes, and a defined output format — copy-paste ready.

3 / 3

Workflow Clarity

Workflows are clearly sequenced with explicit validation checkpoints (grep -q 'Author:' / 'Date:' guards with exit 1) and feedback loops for error recovery.

3 / 3

Progressive Disclosure

Sections are well-organized and the script reference is clearly signaled with a path, but no bundle files exist (no scripts/ directory) so the referenced script is not actually present in the bundle to disclose into.

2 / 3

Total

10

/

12

Passed

Description

100%

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, specific description that names concrete capabilities and provides explicit, natural-language trigger guidance for when to invoke the skill. No fluff or over-claims.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'fetching comment threads, retrieving reviewer feedback, filtering unresolved discussions, and generating MR activity reports' — rather than vague language.

3 / 3

Completeness

Explicitly answers both what it does (capabilities sentence) and when to use it via a clear 'Use when the user asks about...' trigger clause.

3 / 3

Trigger Term Quality

Covers natural terms users would say: 'GitLab MR comments, code review discussions, review feedback, approval status, troubleshooting review delays' plus 'merge request metadata via the GitLab API'.

3 / 3

Distinctiveness Conflict Risk

A clear GitLab-MR-comments niche with distinct, specific triggers; unlikely to be confused with other skills.

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.

Reviewed

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