audit

audit is a skill for Claude Code, Codex from ai-analyst-lab/agentxp. It costs 32 tokens per session (772 once invoked), scanned A, original, Apache-2.0.

A workflow for reconstructing the decision history of an experiment from its human-readable log and Git history. An experiment is a controlled test used to compare a product change or decision.

In plain words
What is it for?
Use it to inspect why an experiment halted, compare experiments, review recorded dispatches, or create a self-contained audit for sharing.
Why use it?
It makes the reasoning, changes, dispatches, and recorded actions behind an experiment easier to review. It can also show differences between two experiments or produce an HTML report.

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/ai-analyst-lab/agentxp/audit
Any agent
npx skills add ai-analyst-lab/agentxp --skill audit
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/agentxp

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai-analyst-lab/agentxp/audit.svg)](https://agentmods.dev/skills/ai-analyst-lab/agentxp/audit)
Your own site
<a href="https://agentmods.dev/skills/ai-analyst-lab/agentxp/audit"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/agentxp/audit.svg" alt="Measured on agentmods" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 772 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00032 $0.00772
Opus 5 $0.00016 $0.00386
Sonnet 5 $0.00006 $0.00154
Haiku 4.5 $0.00003 $0.00077

Measured 3d ago against content hash 89c540b18686, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

audit 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.

.claude/skills/audit/SKILL.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: /audit

Purpose

The audit surface is two things: experiments/<id>/log.md (append-only human-readable log) and git log (every commit_artifact runs a git commit). This skill walks both, optionally diffs two experiments, and optionally renders HTML.

There is no separate event log in v2 — git is the chain.

When to invoke

Direct:

  • /audit <exp_id> — text timeline
  • /audit <exp_id> --diff <other_exp_id> — pairwise diff
  • /audit <exp_id> --html — self-contained HTML

Plain-English routing:

Phrase What to do
"Why did exp_007 halt?" /audit exp_007 then look for halt-related entries
"Compare exp_001 to exp_007" /audit exp_001 --diff exp_007
"Send the audit to my director" /audit <id> --html and surface the file path
"What dispatches landed for exp_004" /audit exp_004 then filter for dispatch entries

Procedure

Text mode (default)

from pathlib import Path
from agentxp.workflows.audit import walk_log

for entry in walk_log(Path.cwd() / "experiments" / args.exp_id):
    print(f"{entry.timestamp}  {entry.message}")

Optionally interleave git log --oneline -- experiments/<id>/ so each commit SHA appears next to its log entry. The two are kept in sync by commit_artifact.

Diff mode

from agentxp.workflows.audit import diff_logs

for d in diff_logs(exp_a, exp_b):
    if d.kind == "changed":
        print(f"line {d.line_no}: {d.a.message}  ->  {d.b.message}")
    elif d.kind == "only_in_a":
        print(f"only in {exp_a.name}: {d.a.message}")
    elif d.kind == "only_in_b":
        print(f"only in {exp_b.name}: {d.b.message}")

HTML mode

Render a self-contained HTML page that includes the log timeline + the renders catalog summary + the integrity-lock receipt from brief.sealed.yaml. Use agentxp.render.report for the HTML adapter; the data comes from walk_log and list_catalog.

Tools you call

  • walk_log / diff_logs from agentxp.workflows.audit
  • list_catalog from agentxp.workflows.readouts (for the renders catalog summary in HTML mode)
  • git log --oneline -- experiments/<id>/ via Bash for commit SHAs

Read the full file on GitHub · 84 lines

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 · 84 lines · 32 tokens per session scan A 89c540b18686

Subscribe to this mod's changes

audit is a skill published in the GitHub repository ai-analyst-lab/agentxp (11 stars, last pushed 6d ago), licensed Apache-2.0. It adds 32 tokens to every session and 772 once invoked, about $0.0002 per session on Opus 5. 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 2026-08-30.

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