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factory-complete-issue

Mark a GitHub issue as done and update its status labels

60

Quality

70%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./mastracode/factory/factory-skills/factory-complete-issue/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

86%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 content is a tight, well-structured instruction skill with concrete commands and thoughtful idempotency guards. The main gap is the omission of exact gh CLI flag syntax and an explicit post-change verification step.

Suggestions

Specify the full gh CLI invocation, e.g. 'gh issue edit <issue> --remove-label "status: needs triage" --add-label "status: pending-close"', so the guidance is copy-paste ready.

Add an explicit verification step after the edit, such as re-reading the issue to confirm the triage labels are gone and pending-close is present.

Show the comment-posting command explicitly (e.g. 'gh issue comment <issue> --body "..."') alongside the conditional logic for when it should be skipped.

DimensionReasoningScore

Conciseness

The body is lean and efficient with no padding or explanation of concepts Claude already knows; every line earns its place and it assumes Claude's competence.

5 / 5

Actionability

Provides the concrete command 'gh issue edit', lists exact label names, and gives the verbatim comment, but does not spell out the full flag syntax (e.g. '--remove-label') for copy-paste execution.

4 / 5

Workflow Clarity

Clear sequence (parse args, read state/labels, remove labels, conditionally add pending-close and comment) with idempotency checkpoints and an open/closed branch, but lacks an explicit post-action verification that the label changes landed.

4 / 5

Progressive Disclosure

A simple skill under 50 lines with no need for external references, organized as a clear single-purpose flow with a title, intro, and listed labels; qualifies for the simple-skill exception at 5.

5 / 5

Total

18

/

20

Passed

Description

53%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 states a clear purpose and domain with two concrete actions, but lacks an explicit 'when to use' trigger clause and natural-language synonyms that would aid discovery. It is distinct but not yet comprehensive.

Suggestions

Add a 'Use when...' clause naming concrete trigger situations, e.g. 'Use when a Factory work item is completed and its GitHub issue needs to be marked done.'

Include natural trigger synonyms such as 'complete', 'close', or 'Factory work item' so users phrasing the request differently still surface the skill.

Specify which status labels are touched (e.g. 'remove triage labels and add status: pending-close') to raise specificity beyond the generic 'update its status labels'.

DimensionReasoningScore

Specificity

Names the domain (GitHub issues) and two concrete actions ('Mark a GitHub issue as done and update its status labels'), but 'update its status labels' is generic and coverage is not comprehensive.

3 / 5

Completeness

Has a clear 'what' (mark done, update labels) but no explicit 'Use when...' or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Includes natural terms 'GitHub issue', 'done', and 'status labels', but misses common synonyms and variations a user might say such as 'complete', 'close', or 'Factory work item'.

3 / 5

Distinctiveness Conflict Risk

Targets a distinct niche (completing GitHub issues) with low conflict risk, though it could overlap with other general issue-management skills; not a 5 because triggers are not maximally specific.

4 / 5

Total

13

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mastra-ai/mastra
Reviewed

Table of Contents

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