Débogage structuré avec persistance de session

VérifiéSûr

Workflow de débogage scientifique utilisant des sous-agents isolés pour investiguer les problèmes avec suivi des checkpoints et persistance des sessions.

Spar Skills Guide Bot
DeveloppementIntermédiaire
4002/06/2026
Claude Code
#debugging#workflow#subagent#session

Recommandé pour

Notre avis

Workflow de débogage structuré utilisant la méthode scientifique avec isolation des sous-agents et persistance des sessions.

Points forts

  • Collecte systématique des symptômes avant investigation
  • Isolation du sous-agent pour préserver le contexte principal
  • Persistance des sessions pour les enquêtes longues
  • Gestion des points de contrôle avec retour utilisateur

Limites

  • Nécessite le support des sous-agents (Claude Code)
  • Dépend de la clarté des symptômes fournis par l'utilisateur
  • Peut être excessif pour des bugs simples
Quand l'utiliser

Idéal pour déboguer des problèmes complexes nécessitant une exploration approfondie des fichiers et des tests d'hypothèses.

Quand l'éviter

Évitez pour des bugs triviaux qui peuvent être corrigés rapidement en lisant le code concerné.

Analyse de sécurité

Sûr
Score qualité90/100

The skill only uses Bash to list files in a safe manner and spawns a debugging subagent; no destructive or exfiltration actions are instructed.

Aucun point d'attention détecté

Exemples

Debug API 500 error
Debug why my API returns 500 on POST /users. The endpoint worked yesterday and no changes were made to the API code.
Debug race condition
Help me debug a race condition where two concurrent requests sometimes cause duplicate entries in the database.
Investigate memory leak
Debug a memory leak in my Node.js server that causes OOM after ~10k requests. I suspect the caching layer but not sure.

name: gsd-debug description: Structured debugging workflow with session persistence and investigation tracking allowed-tools: Task, Read, Edit, Bash argument-hint: [issue]

<objective> Debug issues using scientific method with subagent isolation.

Orchestrator role: Gather symptoms, spawn gsd-debugger agent, handle checkpoints, spawn continuations.

Why subagent: Investigation burns context fast (reading files, forming hypotheses, testing). Fresh 200k context per investigation. Main context stays lean for user interaction. </objective>

<context> User's issue: $ARGUMENTS

Check for active sessions:

ls .planning/debug/*.md 2>/dev/null | grep -v resolved | head -5
</context> <process>

1. Check Active Sessions

If active sessions exist AND no $ARGUMENTS:

  • List sessions with status, hypothesis, next action
  • User picks number to resume OR describes new issue

If $ARGUMENTS provided OR user describes new issue:

  • Continue to symptom gathering

2. Gather Symptoms (if new issue)

Use AskUserQuestion for each:

  1. Expected behavior - What should happen?
  2. Actual behavior - What happens instead?
  3. Error messages - Any errors? (paste or describe)
  4. Timeline - When did this start? Ever worked?
  5. Reproduction - How do you trigger it?

After all gathered, confirm ready to investigate.

3. Spawn gsd-debugger Agent

Fill prompt and spawn:

<objective>
Investigate issue: {slug}

**Summary:** {trigger}
</objective>

<symptoms>
expected: {expected}
actual: {actual}
errors: {errors}
reproduction: {reproduction}
timeline: {timeline}
</symptoms>

<mode>
symptoms_prefilled: true
goal: find_and_fix
</mode>

<debug_file>
Create: .planning/debug/{slug}.md
</debug_file>
Task(
  prompt=filled_prompt,
  subagent_type="gsd-debugger",
  description="Debug {slug}"
)

4. Handle Agent Return

If ## ROOT CAUSE FOUND:

  • Display root cause and evidence summary
  • Offer options:
    • "Fix now" - spawn fix subagent
    • "Plan fix" - suggest {{COMMAND_PREFIX}}plan-phase --gaps
    • "Manual fix" - done

If ## CHECKPOINT REACHED:

  • Present checkpoint details to user
  • Get user response
  • Spawn continuation agent (see step 5)

If ## INVESTIGATION INCONCLUSIVE:

  • Show what was checked and eliminated
  • Offer options:
    • "Continue investigating" - spawn new agent with additional context
    • "Manual investigation" - done
    • "Add more context" - gather more symptoms, spawn again

5. Spawn Continuation Agent (After Checkpoint)

When user responds to checkpoint, spawn fresh agent:

<objective>
Continue debugging {slug}. Evidence is in the debug file.
</objective>

<prior_state>
Debug file: @.planning/debug/{slug}.md
</prior_state>

<checkpoint_response>
**Type:** {checkpoint_type}
**Response:** {user_response}
</checkpoint_response>

<mode>
goal: find_and_fix
</mode>
Task(
  prompt=continuation_prompt,
  subagent_type="gsd-debugger",
  description="Continue debug {slug}"
)
</process>

<success_criteria>

  • [ ] Active sessions checked
  • [ ] Symptoms gathered (if new)
  • [ ] gsd-debugger spawned with context
  • [ ] Checkpoints handled correctly
  • [ ] Root cause confirmed before fixing </success_criteria>
Skills similaires