skill-comply

Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines

Quality

77%

Does it follow best practices?

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Securityby

Advisory

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tessl review fix ./skills/skill-comply/SKILL.md

Quality

Content

87%

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

The body is a concise, well-organized overview with executable CLI examples and a clear pipeline summary, appropriately delegating implementation to the scripts bundle. The only gap is the lack of explicit validation/feedback-loop checkpoints in the described workflow.

Suggestions

Add a brief validation checkpoint to the workflow description, e.g. noting that scenario runs are graded against the spec and low-compliance steps are flagged for hook promotion, to make the feedback loop explicit.

Optionally surface a one-line pointer to the scripts/ module layout so readers can navigate to grader.py/classifier.py for the grading logic.

Dimension	Reasoning	Score
Conciseness	The body is lean and well-sectioned with no padding or explanation of concepts Claude already knows; every section (intro, targets, activation, usage, key concept, report contents) earns its place.	3 / 3
Actionability	The Usage section provides concrete, copy-paste-ready commands ('uv run python -m scripts.run ~/.claude/rules/common/testing.md', '--dry-run', '--gen-model haiku --model sonnet') and the numbered pipeline list is concrete.	3 / 3
Workflow Clarity	The 6-stage pipeline is sequenced, but the body describes stages rather than presenting an operator workflow with explicit validation checkpoints or feedback loops for the batch grading operation.	2 / 3
Progressive Disclosure	For a sub-50-line overview skill, content is cleanly split into well-signaled sections with a single-level reference to the real scripts/ package (run.py, runner.py, grader.py, etc.) and no nested reference chains.	3 / 3
	Total	11 / 12 Passed

Description

67%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific and distinctive, clearly enumerating the skill's concrete actions and staking out a unique compliance-measurement niche. Its main weakness is the absence of an explicit 'Use when...' trigger and limited natural-language trigger term coverage.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks whether a rule or skill is actually being followed, or to verify agent compliance after adding new rules/skills.'

Broaden natural trigger terms to include phrasings users would actually say, such as 'is this rule being followed', 'compliance check', or 'does the agent follow the skill'.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines' — matching the level-3 anchor.	3 / 3
Completeness	Clearly states what the skill does, but there is no explicit 'Use when...' trigger clause; the 'when' is only implied, which caps completeness at 2 per the guidelines.	2 / 3
Trigger Term Quality	Contains some natural terms ('skills, rules, and agent definitions are actually followed', 'compliance rates') but leans technical ('behavioral sequences', 'prompt strictness levels') and omits common variations users would naturally say.	2 / 3
Distinctiveness Conflict Risk	Occupies a clear niche (measuring whether skills/rules/agent definitions are actually followed, with compliance rates) that is unlikely to conflict with other skills.	3 / 3
	Total	10 / 12 Passed

Validation

87%

Warnings & errors only

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

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: affaan-m/ECC
Commit: 754b8dd

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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.