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repo-health-check

Run the dotnet/machinelearning repository health check locally, covering issue backlog, pull requests, GitHub Actions, and Azure DevOps pipelines, then draft a dashboard update and prioritized investigations. Use when asked for ML.NET repository health, maintenance status, stale work, or CI trends.

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

75%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, efficient instruction-only skill: clear workflow with validation checkpoints and approval gating, with heavy detail correctly pushed into the playbook reference. Main gaps are the missing error-recovery loop, some duplication between the Workflow and Local substitutions sections, and one referenced sibling skill that is absent from the bundle.

Suggestions

Add a brief error-recovery step to the workflow (e.g., what to do when a validation check fails, such as re-derive fingerprints or re-check the baseline before drafting).

Deduplicate the Workflow and Local substitutions sections — the /tmp state path and the budgets are stated twice; state each once.

Fix or guard the ../repo-health-investigate/SKILL.md reference, which does not exist in this bundle — either ship it as a reference file or describe the inline investigation steps instead.

DimensionReasoningScore

Conciseness

The ~30-line body is lean with no explanations of concepts Claude already knows. Minor redundancy keeps it below a 5: '/tmp/mlnet-repo-health/' and the dashboard/delta/investigation budgets are each stated twice (Workflow and Local substitutions sections).

4 / 5

Actionability

Mostly concrete instruction-style guidance — exact state directory, the 'dnceng-public/public' fallback API, explicit budgets, and delegated execution rules in the verified references/playbook.md. Falls short of a 5 because no executable commands are inlined and step 4 ('Prefer available authenticated GitHub and Azure DevOps tools') is abstract.

4 / 5

Workflow Clarity

A clear 8-step sequence with an explicit Validation section (fingerprints, baseline non-new marking, required sections, no source mutation) and approval gating before any writes. No error-recovery feedback loop (what to do when a validation check fails), so it does not reach the anchor-5 pattern.

4 / 5

Progressive Disclosure

Good structure: a concise overview that clearly signals the one-level-deep references/playbook.md (verified to exist, 399 lines) for all detailed rules. One referenced path, ../repo-health-investigate/SKILL.md, does not exist in the bundle, which is a minor navigation gap.

4 / 5

Total

16

/

20

Passed

Description

87%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: concrete, third-person, with an explicit trigger clause tied to a specific repository niche. It scores at or near the top on completeness and distinctiveness, with only minor room to broaden natural trigger synonyms.

Suggestions

Add one or two more natural trigger synonyms such as 'backlog', 'triage', or 'CI failures' to the 'Use when' clause.

Consider naming the repository itself ('dotnet/machinelearning') in the trigger clause since users may reference the repo rather than 'ML.NET'.

DimensionReasoningScore

Specificity

Names the domain (dotnet/machinelearning) and several concrete actions and coverage areas — 'issue backlog, pull requests, GitHub Actions, and Azure DevOps pipelines, then draft a dashboard update and prioritized investigations'. Falls short of a 5 because 'run the repository health check' restates the skill name rather than fully decomposing the actions.

4 / 5

Completeness

Clearly answers both 'what' (concrete coverage areas, dashboard update, prioritized investigations) and 'when' via an explicit 'Use when asked for…' clause with concrete trigger phrases — the anchor-5 pattern.

5 / 5

Trigger Term Quality

'ML.NET repository health, maintenance status, stale work, or CI trends' are natural phrases a user would say. A few natural terms are missing (e.g., backlog, triage, or the repo name itself as users might phrase it), so it does not reach comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

Pinned to a single named repository and the ML.NET niche with distinct triggers ('ML.NET repository health', 'CI trends'); minimal overlap risk with any generic skill.

5 / 5

Total

18

/

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

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository

dotnet/machinelearning

Path

.github/skills/repo-health-check/SKILL.md

Reviewed

Table of Contents

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