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factory-review

Review a pull request for a Factory work item — history and context first, then a verdict published on the PR — and mark the review complete

64

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

88%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.

An exceptionally actionable, well-sequenced review procedure: concrete commands, explicit gates, and feedback loops cover nearly every edge case, and supplemental detail is properly split into one-level-deep reference files. The only real costs are token weight from repeated policy statements and very dense paragraphs, and a body that carries more operational detail inline than a minimal overview would.

DimensionReasoningScore

Conciseness

The body is dense, domain-specific policy with essentially no explanation of concepts Claude already knows — every rule is procedural and non-obvious. It falls short of anchor 5 because several policies are stated more than once (credential stripping, verdict anti-hedging, the gh --jq shell note) and a few paragraphs (notably the Phase 3 test-check bullet) pack many rules into run-on form that could be tightened without losing content.

4 / 5

Actionability

Fully executable throughout: exact gh commands with --jq filters, a complete paginated GraphQL query, credential-stripping command prefixes (env -u GH_TOKEN -u GITHUB_TOKEN pnpm --filter <pkg> test), exact file paths (.artifacts/factory-review/pr-<number>-<headSha>.md), exact verdict line formats, pre-publication gate commands (head -n1 <file>), and specific tool call sequences. Copy-paste ready with concrete failure modes and fallbacks.

5 / 5

Workflow Clarity

Six explicitly sequenced phases with validation checkpoints and feedback loops at every risky point: pre-diff design discipline (Phase 1), bot-pending polling with a 60s/10min loop (Phase 2), environment-readiness checks and test-plan publication before execution (Phase 3), adversarial check and six named approval gates before any approve (Phase 5), and pre-publication file gates, head-moved checks, and address-then-retry on verdict-call rejection (Phase 6). This matches anchor 5's clear sequence with explicit validation and error-recovery loops.

5 / 5

Progressive Disclosure

The bundle structure is well organized: the body is the core procedure, references/categories/README.md is a clearly signaled one-level-deep index of 16 category pages (verified present), and references/archaeology.md holds command recipes — both paths named explicitly in the body. It stops short of anchor 5 because the body itself is a 216-line procedure manual rather than an overview, carrying detailed operational minutiae (e.g. the Phase 6 routing/cross-check and author-identity edge cases) that could arguably live in reference files.

4 / 5

Total

18

/

20

Passed

Description

66%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 is concrete and action-oriented, correctly using third-person voice, but it lacks any 'when to use' trigger clause and omits common natural synonyms (PR, code review). Its distinctiveness rests almost entirely on the 'Factory work item' qualifier. Adding an explicit trigger clause and natural variations would lift it to the top band.

Suggestions

Add a 'Use when...' clause naming the trigger conditions — e.g. 'Use when a Factory work item enters the review phase and a pull request must be reviewed and a verdict published' — to raise completeness above 3.

Include natural synonyms and abbreviations users would say, such as 'PR', 'code review', or 'review the PR', to improve trigger-term coverage.

Briefly name what the review evaluates (correctness, tests, scope, pattern-consistency) to make the capability list comprehensive rather than stage-based.

DimensionReasoningScore

Specificity

The description lists several concrete actions — "Review a pull request for a Factory work item", "history and context first", "a verdict published on the PR", "mark the review complete" — with only minor gaps in coverage (the review dimensions like correctness, tests, and security are not named). It sits between anchor 3 (1-2 actions) and anchor 5 (comprehensive), matching anchor 4's 'several specific actions; minor gaps'.

4 / 5

Completeness

It clearly answers 'what' (review a PR: history/context first, then a published verdict, then mark complete) but contains no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. Not 2 because the 'what' is concrete and multi-part, not vague.

3 / 5

Trigger Term Quality

Natural keywords a user would say are present — "review", "pull request", "verdict", "Factory work item" — but common variations like "PR", "code review", and "review the PR" are missing, placing it at anchor 4 (good coverage, a few natural terms missing) rather than 5.

4 / 5

Distinctiveness Conflict Risk

"For a Factory work item" gives it a clear niche that distinguishes it from generic review skills, but the opening "Review a pull request" still overlaps with general code-review/PR-review skills, matching anchor 4 (mostly distinct, minor overlap risk) rather than 5's minimal-conflict profile.

4 / 5

Total

15

/

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

referenced_paths_exist

Referenced path issues: 1 deeper-than-1-level

Warning

Total

15

/

16

Passed

Repository

mastra-ai/mastra

Path

mastracode/factory/factory-skills/factory-review/SKILL.md

Reviewed

Table of Contents

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