trace

An evidence-based method for finding why something happened by comparing several possible causes. It separates what was observed from supporting evidence, opposing evidence and tests that could distinguish the causes.

In plain words
What is it for?
Use it for debugging, regression analysis, performance investigations, architecture reviews, postmortems and configuration or routing problems.
Why use it?
It reduces guesswork when a bug, slowdown or unexpected result could have multiple explanations.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jmstar85/oh-my-githubcopilot/trace
Any agent
npx skills add jmstar85/oh-my-githubcopilot --skill trace
Clone the repo
git clone --depth 1 https://github.com/jmstar85/oh-my-githubcopilot

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 350 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00033 $0.00350
Opus 5 $0.00016 $0.00175
Sonnet 5 $0.00007 $0.00070
Haiku 4.5 $0.00003 $0.00035

Measured 3d ago against content hash fb21957a1ad7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

trace scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to trace — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.github/skills/trace/SKILL.md · 54 lines

What it actually says

Trace

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

  1. Restate the observed result precisely
  2. Generate 3 deliberately different hypotheses:
    • Code-path / implementation cause
    • Config / environment / orchestration cause
    • Measurement / artifact / assumption mismatch
  3. Assign @tracer to each hypothesis lane
  4. Each lane: evidence for, evidence against, critical unknown, discriminating probe
  5. Apply lenses: Systems, Premortem, Science
  6. Rebuttal round between top two hypotheses
  7. 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]
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 54 lines · 33 tokens per session scan A fb21957a1ad7

Subscribe to this mod's changes

trace is a skill published in the GitHub repository jmstar85/oh-my-githubcopilot (153 stars, last pushed 3mo ago), licensed MIT. It adds 33 tokens to every session and 350 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to trace, differing in 0 lines, and is treated as a copy.

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