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Agent skill

Agenttrace Session Audit

by majiayu000 in majiayu000/claude-skill-registry

Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

MITAuto-check passed

Install Agenttrace Session Audit

skills CLI
$ npx skills add majiayu000/claude-skill-registry --skill agenttrace-session-audit -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/claude-skill-registry agenttrace-session-audit --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-llm/agenttrace-session-audit .claude/skills/agenttrace-session-audit && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agenttrace-session-audit
GitHub stars
666
Used in
2 other repos
Token cost
~1.4k tokens
SKILL.md length
695 words
Files
2
Skills in repo
971
Repo updated
First seen
Licence
MIT

At a glance

Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

  • Works in 5 steps: Discover Available Sessions → Produce a Human-Readable Audit → Inspect One Session or Directory → …
  • SKILL.md covers Overview, When to Use This Skill, How It Works and Examples, plus 5 more sections
  • Calls go

What it does

Agenttrace Session Audit is an agent skill from majiayu000/claude-skill-registry. Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

Example prompts

  • “/agenttrace-session-audit”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Discover Available Sessions
  2. Produce a Human-Readable Audit
  3. Inspect One Session or Directory
  4. Compare Attempts When Semantics Matter
  5. Add Automation Gates

What it can do on your machine

Read from SKILL.md and the folder at commit 000116a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • go

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agenttrace Session Audit loads about 1.4k tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 695 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~38
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 000116a, republished under its MIT licence (© majiayu000). 695 words, ~1,447 tokens.

Download SKILL.mdSave it as .claude/skills/agenttrace-session-audit/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
agenttrace-session-audit
description
Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.
category
development
risk
safe
source
community
source_repo
luoyuctl/agenttrace
source_type
community
date_added
2026-05-10
author
luoyuctl
tags
ai-coding, observability, cost-tracking, session-analysis
tools
claude, cursor, gemini, codex-cli
license
MIT

agenttrace Session Audit

Overview

Use this skill to inspect local AI coding-agent sessions with agenttrace. It focuses on the process behind a run: token and cost spikes, tool failures, retry loops, latency gaps, anomalies, health scores, and session-to-session diffs.

agenttrace is local-first and reads session logs from tools such as Claude Code, Codex CLI, Gemini CLI, Aider, Cursor exports, OpenCode, Qwen Code, Kimi, and generic JSON or JSONL traces.

When to Use This Skill

  • Use when a user asks why an AI coding run was slow, expensive, shallow, or unreliable.
  • Use when reviewing local agent logs before retrying a failed or suspicious task.
  • Use when building a lightweight CI health gate for AI-assisted coding sessions.
  • Use when comparing two attempts and looking for changed tool paths, retries, or cost patterns.

How It Works

Step 1: Discover Available Sessions

Prefer an installed agenttrace binary when it is available on PATH. If the current repository is luoyuctl/agenttrace, use go run ./cmd/agenttrace instead.

bash
agenttrace --doctor
agenttrace --overview

If no sessions are detected, report the directories checked by --doctor and ask for the exported session file or log directory.

Step 2: Produce a Human-Readable Audit

Use Markdown when the user wants a concise report they can inspect or share.

bash
agenttrace --overview -f markdown -o agenttrace-overview.md

In the report, lead with the highest-risk sessions and explain why they matter: critical anomalies, repeated tool failures, token or cost waste, long latency gaps, low health scores, and suspiciously shallow sessions.

Step 3: Inspect One Session or Directory

Use the latest session for a quick check, or pass an explicit export path when the user provides one.

bash
agenttrace --latest
agenttrace --latest -f json
agenttrace path/to/session-or-export.json
agenttrace --overview -d path/to/session-dir
Step 4: Compare Attempts When Semantics Matter

Token and latency metrics can look healthy even when an agent confidently takes the wrong implementation path. When the risk is semantic drift, pair the trace audit with a diff against a previous or known-good attempt.

Look for:

  • changed files or commands that diverge from the intended task
  • missing tests or verification steps compared with the reference attempt
  • repeated edits around the same files without a clear reason
  • lower cost that came from skipping necessary exploration
Step 5: Add Automation Gates

For CI or repeatable team workflows, use JSON output or health thresholds.

bash
agenttrace --overview -f json -o agenttrace-overview.json
agenttrace --overview --fail-under-health 80 --fail-on-critical --max-tool-fail-rate 15

Tune thresholds to the project. A strict gate is useful for critical workflows; a reporting-only command is better while the team is learning its baseline.

Examples

Quick Local Review
bash
agenttrace --overview
agenttrace --latest

Use this after a long coding-agent run to decide whether the next prompt should split the task, avoid a failing tool path, add missing tests, or reset context.

Show full SKILL.md (279 more words)Show less
CI Health Check
bash
agenttrace --overview --fail-under-health 80 --fail-on-critical

Use this when agent session logs are available in CI and the team wants a simple guard against critical anomalies or unhealthy runs.

Best Practices

  • Start with --doctor when session discovery is uncertain.
  • Report missing fields plainly; do not invent cost, model, latency, or health data.
  • Treat prompts, code, and session contents as private local data.
  • Prefer JSON output for automation and Markdown output for human review.
  • Use trace metrics for process failures and diff/reference review for semantic drift.

Limitations

  • agenttrace can only analyze logs that are present locally or provided as exports.
  • Some agents do not expose enough fields to infer cost, model, cache use, or latency.
  • Healthy trace metrics do not prove the final code is correct; still run tests and review diffs.
  • CI gates should start as advisory until the team understands normal baseline behavior.

Security & Safety Notes

  • Do not upload private session logs to external services unless the user explicitly approves it.
  • Do not overwrite user reports unless they requested that exact output path.
  • Avoid printing secrets found in prompts, tool output, environment variables, or logs.

Common Pitfalls

  • Problem: No sessions are found. Solution: Run agenttrace --doctor, then point agenttrace at the exported file or log directory.

  • Problem: A run looks cheap and fast but produced the wrong refactor. Solution: Compare the session against a prior attempt or known-good diff; cost metrics alone will miss semantic drift.

  • Problem: CI fails too often after adding a health gate. Solution: Start with JSON or Markdown reporting, inspect normal baselines, then tighten thresholds gradually.

  • @langfuse - Use for production LLM application tracing and evaluation.
  • @observability-engineer - Use for broader service monitoring, SLOs, and incident workflows.

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/ai-llm/agenttrace-session-audit of majiayu000/claude-skill-registry.

  • SKILL.md
  • metadata.json

Open the folder on GitHubat commit 000116a

Used in 2 other repositories

We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Agenttrace Session Audit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agenttrace Session Audit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agenttrace Session Audit this skillmajiayu000/claude-skill-registry6662 repos~1.4kAutomated safety check: PassMIT
Cost Sessionruvnet/ruflo74k—~781Automated safety check: NotesMIT
Cost Conversationruvnet/ruflo74k—~407Automated safety check: NotesMIT
Cost Trackruvnet/ruflo74k—~773Automated safety check: NotesMIT
Cost Trackingaffaan-m/ECC274k1 repos~1.3kAutomated safety check: PassMIT
Cost Summaryruvnet/ruflo74k—~594Automated safety check: NotesMIT

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Questions about Agenttrace Session Audit

What does Agenttrace Session Audit do?

Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates. Agenttrace Session Audit is an agent skill from majiayu000/claude-skill-registry. Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

How do I install Agenttrace Session Audit in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill agenttrace-session-audit -a claude-code`. Or copy the skill folder (skills/ai-llm/agenttrace-session-audit in majiayu000/claude-skill-registry) into .claude/skills/agenttrace-session-audit in your project. Claude Code loads it when a task matches its description.

How do I install Agenttrace Session Audit in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill agenttrace-session-audit -a codex`. Or copy the skill folder (skills/ai-llm/agenttrace-session-audit in majiayu000/claude-skill-registry) into .agents/skills/agenttrace-session-audit in your project. Codex loads it when a task matches its description.

Can I use Agenttrace Session Audit in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill agenttrace-session-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agenttrace-session-audit, .gemini/skills/agenttrace-session-audit, .github/skills/agenttrace-session-audit and .opencode/skills/agenttrace-session-audit in your project.

What does Agenttrace Session Audit need to run?

Going by SKILL.md and its folder, Agenttrace Session Audit needs the command-line tools its instructions call (go).

Does Agenttrace Session Audit access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Agenttrace Session Audit safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agenttrace Session Audit use?

Agenttrace Session Audit is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agenttrace Session Audit use?

About 1.4k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Agenttrace Session Audit?

Skills that share tags, products or a category with Agenttrace Session Audit: Cost Session (ruvnet/ruflo, 74k stars), Cost Conversation (ruvnet/ruflo, 74k stars), Cost Track (ruvnet/ruflo, 74k stars) and Cost Tracking (affaan-m/ECC, 274k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agenttrace Session Audit?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 971 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.