Agent skill

gsd-debug

Systematic debugging with persistent state across context resets

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Install this agent skill to your Project

npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.codex/skills/gsd-debug

Metadata

Additional technical details for this skill

short description
Systematic debugging with persistent state across context resets

SKILL.md

<codex_skill_adapter>

A. Skill Invocation

  • This skill is invoked by mentioning $gsd-debug.
  • Treat all user text after $gsd-debug as {{GSD_ARGS}}.
  • If no arguments are present, treat {{GSD_ARGS}} as empty.

B. AskUserQuestion → request_user_input Mapping

GSD workflows use AskUserQuestion (Claude Code syntax). Translate to Codex request_user_input:

Parameter mapping:

  • headerheader
  • questionquestion
  • Options formatted as "Label" — description{label: "Label", description: "description"}
  • Generate id from header: lowercase, replace spaces with underscores

Batched calls:

  • AskUserQuestion([q1, q2]) → single request_user_input with multiple entries in questions[]

Multi-select workaround:

  • Codex has no multiSelect. Use sequential single-selects, or present a numbered freeform list asking the user to enter comma-separated numbers.

Execute mode fallback:

  • When request_user_input is rejected (Execute mode), present a plain-text numbered list and pick a reasonable default.

C. Task() → spawn_agent Mapping

GSD workflows use Task(...) (Claude Code syntax). Translate to Codex collaboration tools:

Direct mapping:

  • Task(subagent_type="X", prompt="Y")spawn_agent(agent_type="X", message="Y")
  • Task(model="...") → omit (Codex uses per-role config, not inline model selection)
  • fork_context: false by default — GSD agents load their own context via <files_to_read> blocks

Parallel fan-out:

  • Spawn multiple agents → collect agent IDs → wait(ids) for all to complete

Result parsing:

  • Look for structured markers in agent output: CHECKPOINT, PLAN COMPLETE, SUMMARY, etc.
  • close_agent(id) after collecting results from each agent </codex_skill_adapter>

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.

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

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

Check for active sessions:

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

0. Initialize Context

bash
INIT=$(node "/mnt/local-analysis/workspace-hub/.codex/get-shit-done/bin/gsd-tools.cjs" state load)
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fi

Extract commit_docs from init JSON. Resolve debugger model:

bash
debugger_model=$(node "/mnt/local-analysis/workspace-hub/.codex/get-shit-done/bin/gsd-tools.cjs" resolve-model gsd-debugger --raw)

1. Check Active Sessions

If active sessions exist AND no {{GSD_ARGS}}:

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

If {{GSD_ARGS}} 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:

markdown
<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",
  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 $gsd-plan-phase --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:

markdown
<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="gsd-debugger",
  model="{debugger_model}",
  description="Continue debug {slug}"
)

<success_criteria>

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

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