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skill-creator

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Quality

85%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%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 highly actionable, well-sequenced workflow document with copy-paste commands, JSON templates, explicit checkpoints, and clear iteration/termination criteria. Its weaknesses are a chatty, over-length body (609 lines vs its own 500-line guidance) and dangling bundle references — the agents/ files and eval-viewer script it repeatedly points to do not exist in the skill directory.

Suggestions

Add the missing agents/grader.md, agents/comparator.md, and agents/analyzer.md files (or remove the pointers) — three of the five bundled resources the body directs the model to read do not exist in the skill directory.

Fix the eval-viewer path: the body repeatedly invokes eval-viewer/generate_review.py, but no eval-viewer directory exists; either add it or point to the actual scripts/generate_report.py.

Trim the conversational filler ("Cool? Cool.", the plumbers anecdote, the repeated core-loop summary at the end, the all-caps Cowork aside) to bring the body under the 500-line guidance the skill itself sets.

DimensionReasoningScore

Conciseness

The bulk is dense, substantive instruction, but the 609-line body exceeds the skill's own '<500 lines ideal' guidance and is interleaved with padded asides: "Cool? Cool.", the plumbers/grandparents anecdote, "Good luck!", "we are trying to create billions a year in economic value here!", an all-caps Cowork rant, and a full closing section that repeats the core loop already stated at the top. This lands on the score-3 anchor (mostly efficient but could be tightened) rather than 2, since the padding is stylistic overlay rather than explanation of concepts Claude doesn't know.

3 / 5

Actionability

Guidance is copy-paste ready throughout: exact commands ("npx skills find '<keywords>'", the sparse-checkout clone block, "python -m scripts.aggregate_benchmark <workspace>/iteration-N --skill-name <name>", "nohup python <skill-creator-path>/eval-viewer/generate_review.py ..."), complete JSON templates for evals.json/eval_metadata.json/timing.json/feedback.json, and a ready-to-use subagent prompt template. Score 5 rather than 4 because the specific examples cover the common cases with placeholders that are clearly meant to be filled per-run.

5 / 5

Workflow Clarity

The multi-step process is clearly sequenced (intent capture → interview → reference discovery → write → test → grade/aggregate/analyze → review → improve → package) with numbered steps in the eval section, explicit checkpoints ("Save this data immediately... This is the only opportunity to capture this data", snapshot-before-editing for baselines, kill the viewer when done), and explicit termination criteria ("The user says they're happy / feedback is all empty / not making meaningful progress"). This matches the score-5 anchor's feedback loops and error-recovery guidance.

5 / 5

Progressive Disclosure

References are clearly signaled with 'when to read' guidance and `references/schemas.md`, `assets/eval_review.html`, and the `scripts/` files all exist in the bundle. However, four referenced paths are dangling: `agents/grader.md`, `agents/comparator.md`, and `agents/analyzer.md` (no agents/ directory exists) and `eval-viewer/generate_review.py` (no eval-viewer directory; scripts/generate_report.py exists instead) — and the grader/analyzer files are invoked from core workflow steps. That is a material navigation failure beyond the score-4 anchor's 'minor organization gaps', while the overall structure is far better than the score-3 anchor's typical inlining, so 3 is the best fit.

3 / 5

Total

16

/

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: third-person, concrete, and comprehensive, with an explicit 'Use when...' clause covering creation, editing, optimization, evaluation, and benchmarking scenarios. Keyword coverage is good but a few natural user phrasings ('make a skill', 'build a skill') are absent, keeping trigger-term coverage just short of the top anchor.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions covering the skill's full scope: "Create new skills, modify and improve existing skills, and measure skill performance" plus "run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy." It matches the score-5 anchor (multiple specific concrete actions, comprehensive coverage) and stays in third-person voice. It is not a 4 because no meaningful capability of the skill (create, edit, optimize, evaluate, benchmark, description tuning) is left uncovered.

5 / 5

Completeness

It explicitly answers both questions: the 'what' ("Create new skills, modify and improve existing skills, and measure skill performance") and the 'when' via a concrete "Use when users want to..." clause enumerating trigger scenarios. This matches the score-5 anchor exactly; the 'when' clause is explicit and specific, not the weaker 'when' of the score-4 anchor.

5 / 5

Trigger Term Quality

Trigger phrases like "create a skill from scratch", "edit, or optimize an existing skill", "run evals to test a skill", "benchmark skill performance", and "optimize a skill's description" are natural things a user would say. It falls just short of the score-5 anchor because common synonyms like "build a skill", "make a skill", or "improve my skill's triggering" are missing, while it clearly exceeds the score-3 anchor's 'missing common variations or synonyms'.

4 / 5

Distinctiveness Conflict Risk

The skill-authoring/optimization niche is clear with distinct triggers ("create a skill", "run evals", "optimize a skill's description"), so it is mostly distinguishable from other skills. Minor overlap risk remains with general evaluation/benchmarking skills ("run evals to test a skill, benchmark skill performance") — this fits the score-4 anchor rather than the minimal-conflict score-5 anchor, and is far more distinct than the score-3 'somewhat specific' anchor.

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

skill_md_line_count

SKILL.md is long (611 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository

XiaoLuoLYG/GOD

Path

jiuwenclaw/jiuwenclaw/resources/agent/jiuwenclaw_workspace/skills/skill-creator/SKILL.md

Reviewed

Table of Contents

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