CtrlK
BlogDocsLog inGet started
Tessl Logo

skill-refactor

Scan Codex session history for skill failures, usage patterns, and coverage gaps. Use when the user wants daily skill-health monitoring or evidence-backed recommendations about installing, improving, merging, or pruning skills.

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

The risk profile of this skill

SKILL.md
Quality
Evals
Security

Quality

Content

62%Scale 1-3

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-structured analytical workflow with strong validation checkpoints and clear failure-mode handling. Its main weaknesses are the lack of executable examples (no concrete command invocations or output schemas inline) and moderate redundancy across Constraints, Anti-patterns, Gotchas, and Failure mode sections. The progressive disclosure approach with 'Read when' headers is effective but the referenced files couldn't be verified.

Suggestions

Add at least one concrete command-line invocation showing how to run the referenced scripts (e.g., `python scripts/scan_codex_sessions.py --scope=last-week --output=findings.json`) to improve actionability.

Include a minimal example of the structured output format (the keep/improve/merge/retire action table with evidence anchors) so Claude knows exactly what to produce.

Consolidate 'Constraints', 'Anti-patterns', 'Gotchas', and 'Failure mode' into a single 'Guardrails' section to reduce redundancy and improve conciseness.

DimensionReasoningScore

Conciseness

The skill is reasonably efficient but includes some sections that could be tightened—'Philosophy' bullets are somewhat generic, 'Examples' are natural-language prompts rather than concrete demonstrations, and 'Gotchas' partially duplicates 'Anti-patterns' and 'Constraints'. Some redundancy between sections (e.g., 'Failure mode' repeats constraint about missing evidence).

2 / 3

Actionability

The procedure provides a clear sequence of steps and references specific scripts and paths, but there are no executable code snippets, command-line invocations, or concrete output examples. The guidance is specific enough to follow but not copy-paste ready—e.g., how to invoke scan_codex_sessions.py or what the output schema looks like is deferred to references.

2 / 3

Workflow Clarity

The 6-step procedure is clearly sequenced with explicit validation steps (Section 'Validation' with 4 checkpoints), a fail-fast policy for missing evidence, and anti-patterns that serve as guardrails. The feedback loop of 'stop and report gaps' before proceeding is well-defined for this analytical workflow.

3 / 3

Progressive Disclosure

The skill references external files (contract.yaml, session-evidence-workflow.md, scripts) with clear 'Read when' signals at the top, which is good structure. However, without bundle files provided to verify these references exist, and with some inline content that could be offloaded (e.g., the full constraints/anti-patterns/gotchas sections), the disclosure structure is decent but not fully optimized.

2 / 3

Total

9

/

12

Passed

Description

100%Scale 1-3

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 well-crafted skill description that clearly communicates both its purpose and trigger conditions. It uses specific, concrete language about scanning session history and identifying skill issues, and provides an explicit 'Use when' clause with natural trigger terms. The description occupies a distinct niche around skill-health diagnostics that is unlikely to conflict with other skills.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'scan session history for skill failures, usage patterns, and coverage gaps' plus 'installing, improving, merging, or pruning skills'. These are concrete, actionable capabilities.

3 / 3

Completeness

Clearly answers both what ('Scan Codex session history for skill failures, usage patterns, and coverage gaps') and when ('Use when the user wants daily skill-health monitoring or evidence-backed recommendations about installing, improving, merging, or pruning skills') with an explicit 'Use when' clause.

3 / 3

Trigger Term Quality

Includes strong natural trigger terms users would say: 'skill failures', 'usage patterns', 'coverage gaps', 'skill-health monitoring', 'installing', 'improving', 'merging', 'pruning skills', 'session history'. These cover a good range of how users would phrase requests about skill management and diagnostics.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche focused on Codex session history analysis and skill-health monitoring. The combination of 'session history', 'skill failures', 'coverage gaps', and skill lifecycle management (install/improve/merge/prune) creates a clear, unique identity unlikely to conflict with other skills.

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

metadata_version

'metadata.version' is missing

Warning

Total

10

/

11

Passed

Repository
jscraik/Agent-Skills
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.