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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.

64

Quality

76%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./resources/skills/skill-creator/SKILL.md
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 skill's core strength is its highly actionable, well-sequenced evaluation workflow with exact commands, templates, and validation checkpoints. Its weaknesses are padding (chatty asides and duplicated emphasis) and progressive disclosure: references to a missing `agents/` directory and `eval-viewer/generate_review.py` are broken, and environment-specific instructions (Cherry Studio, Claude.ai, Cowork) are inlined rather than offloaded to reference files.

Suggestions

Remove the conversational padding (e.g., "Cool? Cool.", the plumber/grandparent digression, the "billions a year in economic value" aside, and the duplicated "Repeating one more time" core-loop section) — they add tokens without adding instruction.

Fix broken bundle references: either add the `agents/` directory (grader.md, comparator.md, analyzer.md) and `eval-viewer/generate_review.py`, or repoint those references to the existing `scripts/generate_report.py` and fold the subagent guidance into `references/`.

Move the environment-specific sections (Cherry Studio workflow, Claude.ai-specific, Cowork-specific) into separate reference files (e.g., references/environments.md) with a short pointer from SKILL.md, keeping the body focused on the core create-evaluate-improve loop.

DimensionReasoningScore

Conciseness

The body is noticeably padded: conversational asides like "Cool? Cool.", the riff about "plumbers to open up their terminals, parents and grandparents to google 'how to install npm'", "we are trying to create billions a year in economic value here!", the apologetic all-caps Cowork paragraph, and a full re-statement of the core loop "Repeating one more time... for emphasis" all burn tokens without adding instruction. It is above level 1 because the bulk is still genuinely instructional rather than explaining concepts Claude already knows, but several sections could be cut outright.

2 / 5

Actionability

Guidance is fully executable: exact commands ("python -m scripts.aggregate_benchmark <workspace>/iteration-N --skill-name <name>", the run_loop invocation with flags), copy-paste JSON templates for evals.json, eval_metadata.json, timing.json and feedback.json, ready-to-use subagent prompt templates, and exact field-name requirements ("must use the fields text, passed, and evidence"). This matches the level-5 anchor's copy-paste-ready coverage of common cases.

5 / 5

Workflow Clarity

The eval loop is clearly sequenced (Step 1 spawn with-skill AND baseline runs in the same turn, Step 2 draft assertions while running, Step 3 capture timing per notification, Step 4 grade/aggregate/analyze/launch viewer, Step 5 read feedback) with explicit validation checkpoints (assertion grading, benchmark pass rates) and a defined feedback/retry loop with termination criteria. It is not a 4 because validation steps and error-recovery guidance are explicit rather than implicit.

5 / 5

Progressive Disclosure

Structure exists — a "Reference files" section lists `agents/grader.md`, `agents/comparator.md`, `agents/analyzer.md`, and `references/schemas.md` with when-to-read guidance — but the referenced `agents/` directory and `eval-viewer/generate_review.py` do not exist in the bundle (the actual files are `scripts/generate_report.py`, `references/schemas.md`, `assets/eval_review.html`), so several pointers are broken. Combined with ~500 lines of environment-specific sections inlined in SKILL.md that belong in separate references, navigation is only partially reliable — better than the buried/inline problems of level 2, but short of the well-signaled, one-level-deep organization of level 4.

3 / 5

Total

15

/

20

Passed

Description

83%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: it names concrete capabilities and pairs them with an explicit, well-phrased "Use when" clause covering creation, editing, eval, benchmarking, and description-optimization scenarios. It is only marginally short of top marks on trigger synonym coverage and slight genericness of "measure skill performance".

DimensionReasoningScore

Specificity

The description lists several concrete actions — "Create new skills, modify and improve existing skills", "run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy" — covering the skill's surface with only minor gaps (e.g., "measure skill performance" is slightly generic). It falls just short of the level-5 anchor's fully comprehensive, uniformly concrete action list.

4 / 5

Completeness

It explicitly answers both questions: the "what" ("Create new skills, modify and improve existing skills, and measure skill performance") and a concrete "Use when" clause enumerating trigger contexts ("create a skill from scratch, edit, or optimize an existing skill, run evals... benchmark... or optimize a skill's description"). This matches the level-5 anchor exactly; it is not a 4 because the when-guidance is explicit and specific rather than improvable-but-present.

5 / 5

Trigger Term Quality

Good natural-phrase coverage: "create a skill from scratch", "edit, or optimize an existing skill", "run evals", "benchmark", "triggering accuracy" are things a user would actually say. A few natural synonyms are missing (e.g., "SKILL.md", "agent skills", "improve my skill"), so it is a notch below the comprehensive level-5 example.

4 / 5

Distinctiveness Conflict Risk

The skill-creation niche is clear and triggers are skill-specific ("create a skill", "optimize a skill's description"), giving minimal conflict risk with unrelated skills. Minor overlap remains with generic evaluation/benchmarking helpers ("run evals", "benchmark performance"), keeping it below the fully-distinct level-5 anchor.

4 / 5

Total

17

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (518 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository
CherryHQ/cherry-studio
Reviewed

Table of Contents

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