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structured-debug

AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).

80

Quality

100%

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

100%Weight 40%Scale 1-3

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

The content is a compact, evidence-first debugging workflow with executable commands, explicit validation checkpoints, and a clear output template; it scores highly on conciseness, actionability, and workflow clarity with appropriate structure for a simple single-file skill.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — it gives a numbered workflow, exact commands, and a compact red-flags table without explaining basic debugging concepts, so every token earns its place.

3 / 3

Actionability

It provides copy-paste-ready commands (e.g. `npx ai-devkit@latest memory search --query "<observed behavior>" --tags "debug,root-cause"`), a concrete output template, and specific per-hypothesis fields (predicted/disconfirming evidence, exact test command).

3 / 3

Workflow Clarity

The Clarify → Reproduce → Hypothesize/Test → Plan → Validation sequence is explicit with a hard approval checkpoint and a verify feedback loop including regression verification, satisfying the top anchor for sequenced validation steps.

3 / 3

Progressive Disclosure

No bundle files exist in references/scripts/assets, and this is a single-purpose skill under 50 lines, so the well-organized sections (Hard Rule, Workflow, Validation, Task Tracing, Red Flags, Output Template) justify the top score per the simple-skills scoring note.

3 / 3

Total

12

/

12

Passed

Description

100%Weight 40%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.

The description is strong across all dimensions: it states concrete capabilities, provides a rich set of natural trigger terms, and explicitly pairs what-it-does with when-to-use guidance in a distinctive debugging niche.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions: "clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps," matching the top anchor for specific concrete actions.

3 / 3

Completeness

It clearly answers both what it does ("Guide structured debugging before code changes...") and when to use it with an explicit "Use when users ask to..." clause enumerating concrete triggers.

3 / 3

Trigger Term Quality

It includes natural terms users would say — "debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA)" — giving broad coverage of common variations.

3 / 3

Distinctiveness Conflict Risk

The debugging/RCA niche is clearly scoped with distinct triggers ("investigate regressions, triage incidents, diagnose failing behavior"), making it unlikely to trigger for unrelated skills.

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
codeaholicguy/ai-devkit
Reviewed

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