Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install teotoplak-tempo-agents-skills-gsd-debuggit clone https://github.com/teotoplak/tempo.gitcp tempo/SKILL.MD ~/.claude/skills/teotoplak-tempo-agents-skills-gsd-debug/SKILL.md---
name: "gsd-debug"
description: "Systematic debugging with persistent state across context resets"
metadata:
short-description: "Systematic debugging with persistent state across context resets"
---
<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>
<context>
User's issue: {{GSD_ARGS}}
Check for active sessions:
```bash
ls .planning/debug/*.md 2>/dev/null | grep -v resolved | head -5
```
</context>
<process>
## 0. Initialize Context
```bash
INIT=$(node "/Users/teo/src/tempo/.codex/get-shit-done/bin/gsd-tools.cjs" state load)
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fi
```
Extract `commit_docs` from init JSON. Resolve debugger model:
```bash
debugger_model=$(node "/Users/teo/src/tempo/.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}"
)
```
</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>