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Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.

67

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

82%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.

The body is highly actionable and well-structured, with concrete commands, regexes, and templates that a contributor can follow directly. Its main gap is the absence of an explicit error-recovery feedback loop in the workflow.

Suggestions

Add an explicit feedback loop after step 7 ('Wait for automated checks to pass'): if checks fail, read the failure, fix the issue, and re-run until green — this would lift workflow_clarity to 5.

Consider consolidating the recurring type enumerations (branch-naming table, PR-type table, commit type-to-label table) into a single canonical type reference to reduce redundancy.

Optionally move the large branch-naming and commit-format reference tables into a references/ file, keeping SKILL.md as a tighter overview, to strengthen progressive disclosure.

DimensionReasoningScore

Conciseness

The body is lean and table/code-driven without explaining concepts Claude already knows, though the type list recurs across the branch-naming and commit type-to-label tables, leaving minor redundancy.

4 / 5

Actionability

Provides copy-paste ready bash commands (git checkout -b, shellcheck, gh pr create/edit), concrete regexes, and filled-in PR body templates covering the common cases.

5 / 5

Workflow Clarity

A clear 7-step workflow with upfront validation (verify status:approved) and a closing 'wait for automated checks to pass' step plus checklists, but no explicit validate->fix->retry feedback loop is spelled out.

4 / 5

Progressive Disclosure

A single self-contained file with well-signaled section headers and no nested references; well organized, though the long reference tables could theoretically live in a separate file.

4 / 5

Total

17

/

20

Passed

Description

78%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.

The description cleanly states both what the skill does and when to invoke it, with a concrete trigger clause and natural PR-related keywords. It is somewhat light on breadth of actions, which keeps specificity at mid-range.

DimensionReasoningScore

Specificity

Names the domain ('pull requests') and one concrete action ('Create ... pull requests') plus a constraint ('issue-first checks'), but does not comprehensively list the supporting actions (labeling, branch naming) found in the body.

3 / 5

Completeness

Explicitly answers 'what' ('Create Gentle AI pull requests with issue-first checks') and 'when' via an explicit 'Trigger:' clause with concrete trigger phrases, satisfying both halves.

5 / 5

Trigger Term Quality

Includes natural terms users would say ('pull requests', 'PRs') and concrete trigger verbs ('creating, opening, or preparing PRs for review'), though a few common synonyms are absent.

4 / 5

Distinctiveness Conflict Risk

The 'Gentle AI ... issue-first checks' niche and PR-review triggers are mostly distinct, with only minor overlap risk against generic git/PR skills.

4 / 5

Total

16

/

20

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
Gentleman-Programming/gentle-ai
Reviewed

Table of Contents

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