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skill-tuning

Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Gemini CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".

65

Quality

78%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/skill-tuning/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

57%

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

This skill provides a well-organized overview of a complex diagnostic and optimization framework with excellent progressive disclosure and clear reference structure. However, the main document lacks concrete executable guidance — the actionable implementation details are almost entirely deferred to referenced files (which are not provided in the bundle). The workflow is sequenced but missing explicit inline validation/error-recovery loops for destructive operations.

Suggestions

Add at least one concrete, executable example of a diagnosis action (e.g., a code snippet or command showing how context explosion is actually detected and measured) rather than deferring all implementation to spec files.

Include explicit validation feedback loops inline in the workflow section — e.g., 'If action-verify fails: review issues → re-apply fixes → re-verify' — rather than deferring error recovery entirely to orchestrator.md.

Trim redundancy between the architecture diagram, workflow table, and action reference table — these three sections overlap significantly and could be consolidated.

DimensionReasoningScore

Conciseness

The skill is reasonably structured with tables and diagrams, but includes some redundancy (e.g., the action reference table largely repeats the workflow table, and the architecture diagram restates what the tables cover). The priority table and key principles are efficient, but overall it could be tightened.

2 / 3

Actionability

The skill provides a structured workflow with named actions and state management schema, but the actual executable guidance is thin — there are no concrete code snippets for implementing diagnosis or fixes, no actual commands beyond the usage examples (which are invocation patterns, not implementation). The real actionable content is deferred to referenced spec files.

2 / 3

Workflow Clarity

The workflow table provides a clear sequence of 8 steps with orchestrator decisions and outputs, which is good. However, validation/verification is mentioned only as a single step ('action-verify') without explicit feedback loops or error recovery details in the main document — those are deferred to phases/orchestrator.md. For a skill involving potentially destructive fix operations, the lack of inline validation checkpoints caps this at 2.

2 / 3

Progressive Disclosure

The skill excels at progressive disclosure with a clear overview in the main file and well-signaled, one-level-deep references to specs (problem-taxonomy.md, tuning-strategies.md, quality-gates.md), phases (orchestrator.md, state-schema.md), and action implementations. The reference documents table at the end provides excellent navigation.

3 / 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.

This is a strong skill description that clearly communicates its purpose, lists specific capabilities with concrete issue types it addresses, and provides explicit trigger terms. It uses proper third-person voice throughout and is concise without being vague. The only minor note is that 'Universal skill diagnosis and optimization tool' is slightly grandiose but is immediately backed up with specific details.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures.' Also mentions Gemini CLI support for deep analysis.

3 / 3

Completeness

Clearly answers both what ('Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures') and when ('Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug"').

3 / 3

Trigger Term Quality

Explicitly lists natural trigger terms: 'skill tuning', 'tune skill', 'skill diagnosis', 'optimize skill', 'skill debug'. These are terms users would naturally say when needing this functionality, with good variation coverage.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche around skill diagnosis and optimization with very specific trigger terms like 'skill tuning' and 'skill debug' that are unlikely to conflict with other skills. The specific issue types (context explosion, long-tail forgetting) further distinguish it.

3 / 3

Total

12

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

Total

10

/

11

Passed

Repository
catlog22/Claude-Code-Workflow
Reviewed

Table of Contents

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