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gh-review-requests

Fetch unread GitHub notifications for open PRs where review is requested from a specified team or opened by a team member. Use when asked to "find PRs I need to review", "show my review requests", "what needs my review", "fetch GitHub review requests", or "check team review queue".

75

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is gh-review-requests in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

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

A well-structured, lean, highly actionable skill body: clear three-step workflow with explicit zero-result and script-failure handling, a concrete output contract, and a manual fallback. The only notable gap is the hardcoded `--org getsentry` value with no guidance on parameterizing it for other organizations.

DimensionReasoningScore

Conciseness

The body is lean: a one-line summary, a prerequisites line, three short sequenced sections, and a compact fallback. Nothing explains concepts Claude already knows, and every element (slug normalization rule, output JSON contract, reasons enum, zero-case message) adds information Claude could not infer. It matches the anchor-5 'every token earns its place' example in structure and density.

5 / 5

Actionability

Guidance is mostly copy-paste ready: the exact `uv run ${CLAUDE_SKILL_ROOT}/scripts/fetch_review_requests.py --org getsentry --teams <team-slug>` command, a multi-team variant, a concrete output example, an explicit presentation format, and a manual `gh api` fallback with the exact endpoints and skip conditions. It falls short of 5 because `--org getsentry` is hardcoded with no note on when or how to substitute another org, leaving a minor gap for users outside that org.

4 / 5

Workflow Clarity

Steps are clearly sequenced (identify team with an explicit ask-if-unspecified checkpoint, run script, present results) and both failure modes are handled explicitly: "If `total` is 0, say: 'No unread review requests found...'" and "If the script fails, run manually" with concrete fallback commands. The operation is read-only, so the destructive/batch validation cap does not apply, and the error-recovery fallback plus zero-case handling match the anchor-5 feedback-loop pattern for this simple skill.

5 / 5

Progressive Disclosure

The SKILL.md is a self-contained ~70-line overview with well-organized headers and a single one-level-deep reference (`scripts/fetch_review_requests.py`) clearly signaled in its own step. No bundle reference files were provided to verify the script path, but on the content itself nothing that belongs in a separate file is inlined — the short fallback commands and output example are appropriately placed for a skill of this size.

5 / 5

Total

19

/

20

Passed

Description

95%Weight 40%Scale 1-5

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 description: third-person voice, precise capability statement, and an explicit 'Use when' clause with five natural quoted trigger phrases. The only minor limitation is that it describes one fetch operation with filtering criteria rather than enumerating several distinct actions.

DimensionReasoningScore

Specificity

"Fetch unread GitHub notifications for open PRs where review is requested from a specified team or opened by a team member" concretely names the domain and two distinct filtering behaviors (review-requested-from-team, opened-by-team-member). It falls short of a 5 because it covers a single fetch operation rather than listing multiple specific actions with comprehensive coverage, and exceeds a 3 because the actions described are precise and qualified (unread, open PRs, team-filtered) rather than generic.

4 / 5

Completeness

The first sentence explicitly answers "what" (fetch unread review_requested notifications for open PRs filtered by team) and the second answers "when" with concrete quoted trigger phrases. This mirrors the anchor-5 example structure of a clear what-clause plus an explicit 'Use when...' clause with concrete triggers.

5 / 5

Trigger Term Quality

The description quotes five natural user phrasings — "find PRs I need to review", "show my review requests", "what needs my review", "fetch GitHub review requests", "check team review queue" — covering synonyms and colloquial variations users would actually say. This matches the comprehensive-synonyms anchor; no common variation is obviously missing.

5 / 5

Distinctiveness Conflict Risk

"Fetch unread GitHub notifications for open PRs where review is requested from a specified team" carves out a clear niche (team-scoped review-request notification fetching) distinct from generic PR-review or code-review skills, and triggers like "check team review queue" and "fetch GitHub review requests" are unlikely to fire for the wrong skill. It is above the 4 anchor because the overlap risk with closely related skills is minimal given the team/notification scoping.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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