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codehealth-mcp

Real-time structural Code Health via CodeScene MCP — review before edits, verify score deltas after changes, gate commits and PRs. Use when reviewing code quality, refactoring, checking if AI changes degraded a file, or before commit/PR.

Quality

82%

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

70%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 delivers an excellent, validated workflow (baseline → edit → delta check → commit gate → branch analysis) with concrete tools and thresholds, and commendable security/opt-in boundaries. Its weaknesses are token-efficiency (duplicated When-to-Use/pairing sections and a restating example) and the absence of any progressive disclosure — a single 160-line file with one dangling external path reference.

Suggestions

Merge "When to Activate" into "When to Use" with a one-line note that ECC auto-activation keys off that heading, and consolidate the "Pairing with ECC" table with the "Related Skills" list into a single section — both currently repeat nearly the same information.

Move the Flask example, the AGENTS.md enforcement block, and the pairing details into a references/ file (e.g., references/examples.md) and link them from the body, keeping SKILL.md as a lean overview.

Add the actual tool-call signatures or argument lists (target path, base branch for analyze_change_set) so guidance is fully executable, and either include mcp-configs/mcp-servers.json in the bundle or inline the full config block instead of pointing at a missing file.

DimensionReasoningScore

Conciseness

Mostly efficient (tables, terse bullets, no concepts Claude already knows), but several sections are redundant: "When to Use" vs "When to Activate", the "Pairing with ECC" table vs the "Related Skills" list, and the AGENTS.md example which restates the feedback loop. This is more than the minor trimmable instances of anchor 4, fitting anchor 3.

3 / 5

Actionability

Provides concrete tool names with when-to-use table, a copy-paste MCP config JSON block, score thresholds with per-range agent behavior, and scope-by-score rules. Minor gap: exact tool-call signatures/arguments (e.g., path, base-branch params) are never shown, keeping it below the fully-executable anchor 5.

4 / 5

Workflow Clarity

The "Run the feedback loop" section sequences before-file (baseline + smells), after-change (delta vs baseline), pre-commit, and pre-PR steps with an explicit validation feedback loop ("If the score regressed, fix before continuing. Never mark the task done while the score is lower"), plus an anti-pattern example reinforcing the checkpoints.

5 / 5

Progressive Disclosure

The body is well-headed but monolithic: ~160 lines with everything inline and no reference files, while content like the examples, pairing table, and AGENTS.md block would fit separate files. It also points to "mcp-configs/mcp-servers.json", a path not present in this skill's bundle. Structure exists and is navigable (above anchor 2), but organization into one-level-deep references is absent.

3 / 5

Total

15

/

20

Passed

Description

88%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 actions, an explicit 'Use when' clause with natural trigger phrases, and a clearly distinguishable MCP niche. The only weakness is slightly thin synonym coverage (e.g., 'maintainability', 'tech debt') and mild overlap with generic code-quality review phrasing. It uses third person voice throughout with no fluff.

DimensionReasoningScore

Specificity

Lists three concrete, distinct actions — "review before edits", "verify score deltas after changes", "gate commits and PRs" — which comprehensively covers the skill's capability surface; anchor 4 would require noticeable coverage gaps, and none exist.

5 / 5

Completeness

Explicitly answers both what it does (structural Code Health review, delta verification, commit/PR gating) and when to use it ("Use when reviewing code quality, refactoring, checking if AI changes degraded a file, or before commit/PR") with concrete trigger phrases — a direct match for anchor 5.

5 / 5

Trigger Term Quality

Includes natural phrases users would say ("reviewing code quality", "refactoring", "checking if AI changes degraded a file", "before commit/PR") but misses common synonyms such as "maintainability" or "tech debt", so it falls just short of the comprehensive-synonym anchor 5 while clearly exceeding anchor 3.

4 / 5

Distinctiveness Conflict Risk

The CodeScene/Code Health MCP framing carves a clear structural-maintainability niche, but the trigger "reviewing code quality" has minor overlap risk with generic code-review and lint skills, fitting anchor 4 rather than the minimal-conflict anchor 5.

4 / 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

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

affaan-m/ECC

Path

skills/codehealth-mcp/SKILL.md

Reviewed

Table of Contents

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