Thrunt debug

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

Orchestrator role: Gather symptoms, spawn thrunt-incident-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>

<available_agent_types> Valid THRUNT subagent types (use exact names — do not fall back to 'general-purpose'):

• thrunt-incident-debugger — Diagnoses and fixes issues </available_agent_types>

<context> User's issue: $ARGUMENTS

Check for active sessions:

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

</context> <process>

0. Initialize Context

INIT=$(node ".github/thrunt-god/bin/thrunt-tools.cjs" state load)
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fi

Extract commit_docs from init JSON. Resolve debugger model:

debugger_model=$(node ".github/thrunt-god/bin/thrunt-tools.cjs" resolve-model thrunt-incident-debugger --raw)

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 thrunt-incident-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="thrunt-incident-debugger",
  model="{debugger_model}",
  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 /hunt-plan --gaps
  • "Manual fix" - done

If ## CHECKPOINT REACHED:

• Present checkpoint details to user
• Get user response
• If checkpoint type is human-verify:
  • If user confirms fixed: continue so agent can finalize/resolve/archive
  • If user reports issues: continue so agent returns to investigation/fixing
• 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>
<files_to_read>
- .planning/debug/{slug}.md (Debug session state)
</files_to_read>
</prior_state>

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

<mode>
goal: find_and_fix
</mode>

Task(
  prompt=continuation_prompt,
  subagent_type="thrunt-incident-debugger",
  model="{debugger_model}",
  description="Continue debug {slug}"
)

</process>

<success_criteria>

• Active sessions checked
• Symptoms gathered (if new)
• thrunt-incident-debugger spawned with context
• Checkpoints handled correctly
• Root cause confirmed before fixing </success_criteria>