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maintenance

Use when the user asks for a project health audit, a maintenance sweep, or a multi-category lead-engineer scan followed by interactive issue-by-issue resolution. Not for routine lint/test runs, single-file cleanups, or plain check-project requests.

67

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

76%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-architected multi-phase skill with explicit sequencing, validation gates, loud-failure handling, and clean one-level-deep reference splitting. The main improvement is trimming the repetitive justifications of the question-format rules to recover token budget.

Suggestions

Collapse the three-sentence justification of the 'repeat the counts inside the question' rule (Step 5) into one directive sentence; the rule is already clear from its statement.

Dedupe the FR-UNIVERSAL.QA-FORMAT self-containment guidance, which is restated in both the Question Format section and again inside Step 6.

Add a one-line concrete example of the subagent spawn invocation (e.g. the Task/Agent tool call shape) so the fan-out step is copy-paste ready across IDEs.

DimensionReasoningScore

Conciseness

Mostly efficient but several passages pad the same constraint repeatedly — the 'repeat the counts inside the question' rule is justified across three long sentences (Step 5) and the self-containment rule is restated in multiple places — so it could be tightened without losing clarity.

3 / 5

Actionability

Provides concrete executable guidance — specific fan-out pattern (5 parallel maintenance-scan-* subagents across buckets W1–W5), exact issue-line shape, literal severity strings, sorting/numbering rules, and a worked example — with only minor gaps around how to actually spawn the subagents in each IDE.

4 / 5

Workflow Clarity

A two-phase process (Scan, Resolution) is laid out as an explicitly numbered 6-step sequence with a mandatory verification gate (Step 3), a loud-failure 'NOT SCANNED' fallback, anti-inflation severity calibration, and a closing verification checklist with feedback loops for a destructive/batch operation.

5 / 5

Progressive Disclosure

SKILL.md carries only the index and routing; the per-category check detail is pushed one level deep into the 5 self-contained subagent bodies, and severity/verification/example references all resolve to real files in references/ (severity-rubric.md, verification-gate.md, example-findings.md), each clearly signaled and linked.

5 / 5

Total

17

/

20

Passed

Description

86%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 that pairs concrete capabilities with explicit positive and negative triggers, giving Claude clear activation guidance and scope boundaries. Minor gains are available by adding lay synonyms and trimming the internal 'lead-engineer' phrasing.

DimensionReasoningScore

Specificity

Names several concrete actions ('project health audit', 'maintenance sweep', 'multi-category lead-engineer scan', 'interactive issue-by-issue resolution') but stops short of enumerating the full category set or the exact resolution mechanics, leaving minor coverage gaps.

4 / 5

Completeness

Explicitly answers both what (multi-category scan + interactive issue-by-issue resolution) and when ('Use when the user asks for...') with concrete trigger phrases, and adds a clear negative-scope clause for what it is not for.

5 / 5

Trigger Term Quality

Captures natural user phrases ('project health audit', 'maintenance sweep', 'check-project') with good coverage, though it lacks a few common synonyms like 'tech-debt sweep' or 'codebase cleanup' and the term 'lead-engineer scan' is internal jargon a user is unlikely to say.

4 / 5

Distinctiveness Conflict Risk

The combination of multi-category lead-engineer scan plus interactive per-issue resolution, reinforced by an explicit 'Not for routine lint/test runs, single-file cleanups, or plain check-project requests' exclusion, carves a clear niche with minimal overlap against generic check/test skills.

5 / 5

Total

18

/

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
korchasa/flowai-plugins
Reviewed

Table of Contents

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