Use when a debugging thread needs to be compressed into a reusable investigation ledger. Capture the target, evidence, attempted fixes, ruled-out hypotheses, viable hypotheses, and next experiments. Good triggers include "compact this debugging session", "summarize what we've tried", and "turn this into a debugging ledger".
99
100%
Does it follow best practices?
Impact
99%
3.66xAverage score across 8 eval scenarios
Passed
No known issues
Quality
Discovery
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 defines its purpose, lists specific concrete actions, provides explicit trigger guidance with natural user phrases, and occupies a distinct niche. It follows the recommended pattern of 'Use when...' with additional trigger examples, and uses appropriate third-person voice throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: capture the target, evidence, attempted fixes, ruled-out hypotheses, viable hypotheses, and next experiments. Also specifies the output format as a 'reusable investigation ledger'. | 3 / 3 |
Completeness | Clearly answers both what (compress debugging thread into a reusable investigation ledger capturing specific elements) and when (explicit 'Use when' clause plus 'Good triggers include' with concrete example phrases). | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases users would actually say: 'compact this debugging session', 'summarize what we've tried', 'turn this into a debugging ledger'. Also includes domain terms like 'debugging thread', 'investigation ledger', and 'hypotheses'. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche: specifically about compressing debugging sessions into structured ledgers. The combination of 'debugging', 'ledger', 'hypotheses', and 'investigation' creates a clear, unique identity unlikely to conflict with general summarization or debugging skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is an excellent skill that is concise, well-structured, and highly actionable. It provides a clear template and strict rules without over-explaining concepts Claude already understands. The separation of workflow steps, output format, and rules makes it easy to follow and apply consistently.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Every line serves a purpose. No unnecessary explanations of what debugging is or how ledgers work. The format is lean and assumes Claude understands the concepts. | 3 / 3 |
Actionability | The output format is a concrete, copy-paste-ready template with clear placeholders. The workflow steps are specific and the rules section provides unambiguous constraints (e.g., exactly one of three labels). This is an instruction-only skill where code isn't needed, and the guidance is fully actionable. | 3 / 3 |
Workflow Clarity | The 6-step workflow is clearly sequenced and logically ordered from extraction through to next experiments. For this type of non-destructive summarization task, explicit validation checkpoints aren't necessary, and the rules section serves as implicit quality checks (e.g., enforcing label consistency). | 3 / 3 |
Progressive Disclosure | This is a simple, single-purpose skill under 50 lines. The content is well-organized into clear sections (Goal, Workflow, Output Format, Rules) with no need for external references. The structure supports easy scanning and discovery. | 3 / 3 |
Total | 12 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
Reviewed
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