.agents/skills/gsd-debug/SKILL.md
Systematic debugging with persistent state across context resets
npx skillsauth add scaixeta/CindyAgent gsd-debugInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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'):
Check for active sessions:
ls .planning/debug/*.md 2>/dev/null | grep -v resolved | head -5
</context>
<process>
INIT=$(node ".agents/get-shit-done/bin/gsd-tools.cjs" state load)
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fi
Extract commit_docs from init JSON. Resolve debugger model:
debugger_model=$(node ".agents/get-shit-done/bin/gsd-tools.cjs" resolve-model gsd-debugger --raw)
If active sessions exist AND no $ARGUMENTS:
If $ARGUMENTS provided OR user describes new issue:
Use AskUserQuestion for each:
After all gathered, confirm ready to investigate.
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}"
)
If ## ROOT CAUSE FOUND:
If ## CHECKPOINT REACHED:
human-verify:
If ## INVESTIGATION INCONCLUSIVE:
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>
data-ai
Post-mortem investigation for failed GSD workflows — analyzes git history, artifacts, and state to diagnose what went wrong
data-ai
Execute a trivial task inline — no subagents, no planning overhead
tools
Execute all plans in a phase with wave-based parallelization
tools
Route freeform text to the right GSD command automatically