About trace
Trace is a skill for investigating ambiguous, evidence-heavy causal questions. It guides analysts through competing explanations and probes to identify why an outcome occurred.
Key features
- 01Competing causal hypotheses
- 02Evidence for and against
- 03Critical unknowns and probes
- 04Rebuttal between leading hypotheses
- 05Ranked explanation output
Use cases
- 01Tracing runtime bugs and regressions
- 02Explaining performance or latency behavior
- 03Analyzing architecture and incidents
- 04Investigating config or orchestration behavior
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ zereight/ gitlab-mcp --skill traceAfter installing, type/tracein Claude Code to confirm it loaded.
Details
From the project READMETrace
Evidence-driven causal tracing using competing hypotheses. Use for ambiguous, causal, evidence-heavy questions where the goal is to explain WHY something happened.
Good Entry Cases
- Runtime bugs and regressions
- Performance / latency behavior
- Architecture / premortem / postmortem analysis
- Config / routing / orchestration behavior
- "Given this output, trace back the likely causes"
Core Contract
Always preserve: Observation → Hypotheses → Evidence For → Evidence Against → Best Explanation → Critical Unknown → Discriminating Probe
Workflow
- Restate the observed result precisely
- Generate 3 deliberately different hypotheses:
- Code-path / implementation cause
- Config / environment / orchestration cause
- Measurement / artifact / assumption mismatch
- Assign @tracer to each hypothesis lane
- Each lane: evidence for, evidence against, critical unknown, discriminating probe
- Apply lenses: Systems, Premortem, Science
- Rebuttal round between top two hypotheses
- Rank, detect convergence, synthesize
Output
### Observed Result
[What happened]
### Ranked Hypotheses
| Rank | Hypothesis | Confidence | Evidence Strength |
|------|------------|------------|-------------------|
### Most Likely Explanation
[Current best explanation]
### Critical Unknown
[Single missing fact]
### Recommended Discriminating Probe
[Single next probe]
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