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error-diagnostics-smart-debug

Diagnose software failures using observability data, ranked hypotheses, and targeted instrumentation. Use when the cause is unclear or an issue requires systematic investigation.

52

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Low

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tessl review fix ./skills/error-diagnostics-smart-debug/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

48%Weight 40%Scale 1-5

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

The body presents a genuinely well-sequenced 10-stage debugging workflow with validation and prevention stages, but it is padded with boilerplate filler, persona text, and vendor/taxonomy lists Claude already knows, and its only worked example is non-executable pseudocode against fictional APIs. Splitting reference material into bundle files and replacing filler with executable commands would substantially raise quality.

Suggestions

Delete the templated 'Use this skill when / Do not use this skill when' filler, the generic 'Instructions' bullets, the 'You are an expert...' persona line, and the duplicate trailing 'Issue to debug: $ARGUMENTS' block.

Replace the pseudocode example (aiAnalyze, getSentryIssue, getDataDogTraces) with executable commands, e.g. real Sentry/Datadog API or CLI invocations, and remove or verify the 'Task tool (subagent_type="debugger")' reference.

Move the observability vendor catalog, bug-category taxonomy, and strategy/technique details into one-level-deep reference files (e.g. references/observability.md, references/strategies.md) and link them from a lean SKILL.md overview.

Add an explicit failure feedback loop after the validation step: what to do when success criteria are not met (e.g. re-rank hypotheses and iterate).

DimensionReasoningScore

Conciseness

Several sections are pure padding: the templated "Use this skill when / Do not use this skill when" lists that just restate the skill name ("Working on error diagnostics smart debug tasks or workflows"), generic "Instructions" bullets ("Clarify goals, constraints, and required inputs. Apply relevant best practices and validate outcomes."), the role-play line "You are an expert AI-assisted debugging specialist", exhaustive vendor name lists (Sentry, Rollbar, Bugsnag, DataDog...) and bug taxonomy lists (race conditions, null handling...) that Claude already knows, plus a duplicated "$ARGUMENTS" block at the end. This matches the anchor 'Noticeably verbose; several unnecessary explanations or padded sections' rather than a 3, because the filler is pervasive rather than incidental.

2 / 5

Actionability

The workflow gives a usable framework (parse the issue, gather observability data, score hypotheses with falsification criteria, choose a strategy) but the single code example is pseudocode built on fictional APIs ("await aiAnalyze({...})", "getSentryIssue", "getDataDogTraces") that cannot be executed, and "Use Task tool (subagent_type=\"debugger\")" references a subagent that may not exist. This fits the anchor 'Some concrete guidance but incomplete; pseudocode instead of executable code; missing key details' — above a 2 because the step structure and tool choices are concrete, below a 4 because nothing shown is copy-paste executable.

3 / 5

Workflow Clarity

The ten numbered stages are clearly sequenced from triage through validation to prevention, with an explicit validation step ("Run test suite", "Performance comparison", "Canary deployment") and a success-criteria checklist ("Tests pass", "No performance regression", "Error rate unchanged or decreased"), plus falsification criteria per hypothesis. This matches 'Clear sequence with most checkpoints present; minor validation gaps': it falls short of 5 because the validation steps lack concrete commands and there is no explicit feedback loop describing what to do when validation fails (e.g. return to hypothesis ranking).

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are all absent) and the ~190-line body inlines content that would be better split out — the observability vendor catalog, the bug-category taxonomy, and the per-strategy technique descriptions would each fit a separate reference file, and the example session belongs in an examples file. Section headers are clear (so not a 2), but structure is only partially appropriate, matching the anchor 'Some structure but could be better organized; content that should be separate is inline'.

3 / 5

Total

12

/

20

Passed

Description

67%Weight 40%Scale 1-5

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

A solid description with a clear third-person statement of capabilities and an explicit 'Use when' clause. Its main weakness is trigger vocabulary: it avoids the everyday debugging words (debug, troubleshoot, error, root cause) users are most likely to say, leaving the when-clause more abstract than concrete.

Suggestions

Add natural trigger synonyms to the when-clause, e.g. "Use when the user asks to debug, troubleshoot, or find the root cause of an error, crash, or unexpected behavior".

Enumerate a fuller set of capabilities to close coverage gaps, e.g. root cause analysis and fix validation, not just diagnosis and instrumentation.

DimensionReasoningScore

Specificity

The description lists several concrete actions — "Diagnose software failures", "ranked hypotheses", "targeted instrumentation", and "observability data" — comparable to the anchor 'Extracts text from PDF files, fills forms, converts pages to images'. It falls short of a 5 because coverage has gaps: root cause analysis, fix validation, and error/stack-trace handling are part of the skill but unmentioned; it is clearly above a 3 since more than 1-2 specific actions are named.

4 / 5

Completeness

It explicitly answers both questions: the what is "Diagnose software failures using observability data, ranked hypotheses, and targeted instrumentation" and the when is "Use when the cause is unclear or an issue requires systematic investigation". This matches the anchor 'Has both what and when; when could be more explicit or specific' — the when clause is present but abstract, lacking concrete trigger phrases like 'when the user mentions bugs, errors, or debugging', so it does not reach 5.

4 / 5

Trigger Term Quality

The trigger "Use when the cause is unclear or an issue requires systematic investigation" contains some natural phrases but misses the most common variations users would actually say — "debug", "debugging", "troubleshoot", "error", "root cause", "why is this failing". This matches the anchor 'Some relevant keywords but missing common variations or synonyms' (like "Works with PDF files"); it is not a 4 because the natural vocabulary of debugging is largely absent.

3 / 5

Distinctiveness Conflict Risk

The description carves out a clear debugging/diagnostics niche with distinct triggers (unclear cause, systematic investigation), with only minor overlap risk against closely related skills such as code review or testing skills. It does not reach 5 because the generic "systematic investigation" phrasing could pull in non-debugging investigation tasks.

4 / 5

Total

15

/

20

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

rmyndharis/antigravity-skills

Path

skills/error-diagnostics-smart-debug/SKILL.md

Reviewed

Table of Contents

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