Skip to content
cccskills
FreePublished on GitHub

gsd-debug

Systematic debugging with persistent state across context resets

The English summary is being prepared. Showing the original description.

SpillwaveSolutions/agent-brain119 stars(GitHub 119 + cccskills 0)

Run score Not tested

See how to install

Files included (1)

  • SKILL.md5.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

<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:

  • header → header
  • question → question
  • 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>
<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>

<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>
<context> User's issue: {{GSD_ARGS}}

Check for active sessions:

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

0. Initialize Context

INIT=$(node "/Users/richardhightower/clients/spillwave/src/agent-brain/.codex/get-shit-done/bin/gsd-tools.cjs" state load)
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fi

Extract commit_docs from init JSON. Resolve debugger model:

debugger_model=$(node "/Users/richardhightower/clients/spillwave/src/agent-brain/.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:

<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:

<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}"
)
</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>

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Installation and configuration skill for Agent Brain document search system. Use when asked to "install agent brain", "setup agent brain", "configure agent brain", "setting up document search", "installing agent-brain packages", "configuring API keys", "initializing project for search", "troubleshooting agent brain", "pip install agent-brain", "agent brain not working", "agent brain setup error", "configure embeddings provider", "setup ollama for agent brain", "agent brain environment variables", "install agent brain mcp", "configure mcp server", or "connect agent brain to claude desktop". Covers package installation (server, CLI, MCP), provider configuration, project initialization, and server management.

The English summary is being prepared. Showing the original description.

SpillwaveSolutions/agent-brain119Updated Sep 20, 2026

Add an idea to the backlog parking lot (999.x numbering)

The English summary is being prepared. Showing the original description.

SpillwaveSolutions/agent-brain119Updated Sep 20, 2026

Add phase to end of current milestone in roadmap

The English summary is being prepared. Showing the original description.

SpillwaveSolutions/agent-brain119Updated Sep 20, 2026

Generate tests for a completed phase based on UAT criteria and implementation

The English summary is being prepared. Showing the original description.

SpillwaveSolutions/agent-brain119Updated Sep 20, 2026

Capture idea or task as todo from current conversation context

The English summary is being prepared. Showing the original description.

SpillwaveSolutions/agent-brain119Updated Sep 20, 2026

Audit milestone completion against original intent before archiving

The English summary is being prepared. Showing the original description.

SpillwaveSolutions/agent-brain119Updated Sep 20, 2026

See all skills by SpillwaveSolutions

Report a problem with this skill