trace
Use to surface what AI did during a session — actions taken, alternatives considered, why choices were made. "Show me the trace", "what did you do and why".
What this skill does
# trace
Execution trace. What was done; what was considered; why this option won.
## Method
1. **Span.** Last N turns / last task / last session.
2. **Walk the conversation.** Per assistant turn:
- Tool calls + outcomes
- Memory queries
- Subagent dispatches
- User-visible output
3. **Annotate decisions.** Where the assistant chose between options:
- What were the options?
- Why this one?
- Memory hit / pattern recall / heuristic?
4. **Surface "alternative paths"** the assistant rejected and why.
## Output shape
```
Trace span: <last 20 turns>
Sequence:
T1 user said "fix the auth bug"
→ mem_search { "auth bug" } → 2 hits
→ invoked `investigate` skill (chose over `fix` because user said "look into" not "fix")
→ produced hypothesis tree
T2 user said "go with H1"
→ invoked `fix` skill on H1
→ applied patch to src/auth/middleware.ts:42
→ ran tests → green
T3 user said "what else?"
→ mem_search { "auth middleware adjacent" } → 1 hit
→ flagged related issue (NOT fixed — out of fix scope)
Decision points:
D1: investigate vs fix at T1
Chose: investigate
Reason: phrasing "look into" implies diagnostic, not action
D2: stop at T2 vs expand
Chose: stop and report
Reason: `fix` skill anti-pattern — no scope creep
Memory written:
- <id>: investigation report
- <id>: fix capture
- <id>: out-of-scope adjacent issue (for follow-up)
```
## Rules
- **Decisions surfaced explicitly.** Not just what happened — why.
- **Alternatives named.** "Chose X over Y because Z."
- **Tool calls + outcomes paired.** Not just "called X" but "X returned Y".
- **Memory writes listed.** Audit-trail.
## Anti-patterns
- Long flat narrative without decision callouts
- Hiding tool failures
- Glossing over alternatives
- Trace that's longer than the original session
## When NOT to use
- Session was trivial (one tool call) — overkill
- Active session — disrupts flow; use post-hoc
## Subagent dispatch
- None — synthesis of conversation
- Memory MCP for the writes ledger
## Value over native CC
CC executes; tracing isn't natural to its output. This skill produces the post-hoc audit. Useful for: trust-building with users new to AI dev, post-incident review, training data.
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