CtrlK
BlogDocsLog inGet started
Tessl Logo

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.

67

Quality

81%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

62%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is richly actionable and clearly sequenced with validation checkpoints, but it is over its own line budget with redundant conversational prose, and several load-bearing references (eval-viewer/generate_review.py and the agents/*.md files) point at files absent from the bundle, which weakens both actionability and navigation.

Suggestions

Resolve the broken script reference: either ship eval-viewer/generate_review.py or rewrite the ~5 call sites to use the existing scripts/generate_report.py so the central review step is runnable as written.

Add the referenced agents/ directory (grader.md, comparator.md, analyzer.md) or move that guidance into references/ and update the pointers, so navigation targets actually exist.

Trim the body under 500 lines by removing the verbatim repeat of the core loop at the bottom and the conversational asides, and by moving the kernel.py plugin guidance and the per-environment (claude.ai / Cowork) sections into reference files.

DimensionReasoningScore

Conciseness

The body runs ~613 lines, exceeding its own stated '<500 lines ideal', and carries conversational filler and repetition — the core loop is stated at the top and repeated verbatim at the bottom ('Repeating one more time the core loop here for emphasis'), plus asides like 'This goes without saying, but...' and 'Please add steps to your TodoList'. It is not level 3 because of this padding and redundancy; it is not level 1 because the content is domain-specific actionable guidance rather than explanation of concepts Claude already knows.

2 / 3

Actionability

Most guidance is concrete and executable (host.skills.* API calls, `python -m scripts.aggregate_benchmark`, `python -m scripts.run_loop`, JSON templates), but the load-bearing review step repeatedly invokes `eval-viewer/generate_review.py` which is not present in the bundle (only scripts/generate_report.py exists), and it references agents/grader.md, agents/comparator.md, agents/analyzer.md which also do not exist. It is not level 3 because a central, repeated command cannot be run as written and key subagent instructions point at missing files; it is not level 1 because the majority of instructions are copy-paste ready.

2 / 3

Workflow Clarity

Multi-step processes are explicitly sequenced with validation checkpoints — the eval run is broken into Step 1 (spawn with-skill and baseline in the same turn) through Step 5 (read feedback), with a grade → aggregate → analyst validation pass and an explicit iteration loop with feedback-driven retry. It is not level 2 because validation steps and feedback loops are present and explicit, not merely implied.

3 / 3

Progressive Disclosure

Structure exists with signaled pointers to real files (references/schemas.md and assets/eval_review.html and scripts/* all exist), but the body exceeds 500 lines with content that could be split out (kernel.py plugin guidance, the claude.ai and Cowork sections, description optimization), and it references non-existent paths (eval-viewer/generate_review.py and the agents/*.md files). It is not level 3 because of the over-length inline content and broken references; it is not level 1 because references are clearly signaled and mostly one level deep.

2 / 3

Total

9

/

12

Passed

Description

100%

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, third-person description that concretely lists capabilities and provides an explicit 'Use when' trigger clause covering creation, editing, optimization, eval running, benchmarking, and description tuning. It is concise, specific, and low conflict risk.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete actions — 'Create new skills, modify and improve existing skills, ... run evals ... benchmark skill performance with variance analysis ... optimize a skill's description' — matching the level-3 anchor of listing several specific concrete actions. It is not level 2 because the action set is comprehensive rather than partial, and uses consistent third-person voice.

3 / 3

Completeness

It answers both 'what' (create/modify/improve/measure skills) and 'when' via an explicit 'Use when users want to ...' clause listing concrete triggering contexts. It is not level 2 because the 'when' is explicitly stated, not merely implied.

3 / 3

Trigger Term Quality

It surfaces natural phrases a user would actually say — 'create a skill from scratch', 'edit ... an existing skill', 'optimize', 'run evals', 'benchmark skill performance', 'triggering accuracy' — giving good coverage of common variations. It is not level 2 because it covers multiple natural phrasings rather than a single keyword.

3 / 3

Distinctiveness Conflict Risk

It occupies a clear niche (skill authoring and optimization) with distinct triggers unlikely to fire for unrelated skills. It is not level 2 because the scope is narrowly scoped to skill creation/evaluation rather than overlapping with generic coding or document skills.

3 / 3

Total

12

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (614 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
UnicomAI/wanwu
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.