Borrowing it
Nothing to install: this file belongs to junghwaYang/oh-my-codex. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/junghwaYang/oh-my-codex/main/.codex/skills/trace/SKILL.mdgit clone --depth 1 https://github.com/junghwaYang/oh-my-codexWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/junghwayang/oh-my-codex/trace)<a href="https://agentmods.dev/skills/junghwayang/oh-my-codex/trace"><img src="https://agentmods.dev/badge/skills/junghwayang/oh-my-codex/trace/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/junghwayang/oh-my-codex/trace"><img src="https://agentmods.dev/badge/skills/junghwayang/oh-my-codex/trace.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00884 |
| Opus 5.5 | $0.00000 | $0.00354 |
| Sonnet 5.5 | $0.00000 | $0.00177 |
| Haiku 4.5 | $0.00000 | $0.00088 |
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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trace Skill
Execution tracing and debugging for orchestration.
When to Use
- Debugging agent behavior
- Understanding decision flow
- Performance profiling
- Troubleshooting failures
Trace Levels
Level 1: Summary
[15:30:01] Task started: "Build auth system"
[15:30:05] Plan created: 5 subtasks
[15:35:22] All tasks completed
[15:35:23] Session ended: SUCCESS
Level 2: Standard
[15:30:01] PM: Received task "Build auth system"
[15:30:02] PM: Analyzing requirements...
[15:30:05] PM: Created plan with 5 subtasks
[15:30:06] PM: Delegating to Frontend (subtask 1)
[15:30:06] PM: Delegating to Backend (subtask 2)
[15:31:15] Frontend: Completed "Login form"
[15:32:30] Backend: Completed "Auth API"
...
Level 3: Verbose
[15:30:01.234] PM: Received task
Input: "Build auth system"
Context: {session: "abc123", mode: "autopilot"}
[15:30:02.456] PM: Calling model
Model: o3
Tokens: 1,234 (prompt) + 567 (completion)
Latency: 2.3s
[15:30:05.789] PM: Plan generated
Plan: {
tasks: [
{id: 1, description: "Login form", agent: "frontend"},
...
]
}
Trace Output
Console
Real-time output to terminal
File
Written to ~/.codex/traces/{session_id}.log
Structured (JSON)
{
"timestamp": "2026-02-13T15:30:01.234Z",
"agent": "pm",
"event": "task_received",
"data": {
"task": "Build auth system",
"mode": "autopilot"
}
}
Trace Events
| Event | Description |
|---|---|
task_received |
Agent received a task |
task_delegated |
Task assigned to another agent |
task_started |
Agent began work |
task_completed |
Agent finished work |
task_failed |
Agent encountered error |
model_call |
LLM API called |
tool_used |
Tool executed |
decision |
Agent made decision |
Analysis
Timeline View
PM ████░░░░░░░░░░░░░░░░░░░░░░
Frontend ░░░░████████░░░░░░░░░░░░░░
Backend ░░░░████████████░░░░░░░░░░
Tester ░░░░░░░░░░░░░░░░████░░░░░░
0s 5s 10s 15s 20s 25s 30s
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.
- 2mo ago First seen · 132 lines · 0 tokens per session scan A ae43693e55f9
trace is a skill published in the GitHub repository junghwaYang/oh-my-codex (5 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 884 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
trace compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| tracejunghwaYang/oh-my-codex | Skill | 5 | 8mo ago | MIT | A | 0 | Codex |
| systematic-debuggingopen-metadata/OpenMetadata | Skill | 16k | today | Apache-2.0 | A | 37 | Claude Code |
| log-error-digestzebbern/claude-code-guide | Skill | 4.7k | today | MIT | A | 71 | Claude Code, Codex |
| cwv-optimizeradobe/skills | Skill | 319 | today | Apache-2.0 | A | 112 | Claude Code |
| ci-fixersipyourdrink-ltd/bernstein | Skill | 1.2k | today | Apache-2.0 | A | 15 | Claude Code, Codex |
| diagnosing-missing-recordingsPostHog/posthog | Skill | 41k | today | none | A | 76 | Claude Code, Codex |
| loop-engineeringhuytieu/COG-second-brain | Skill | 1.3k | 15d ago | MIT | A | 63 | Claude Code |