audit

audit is an agent for coding agents from SienkLogic/plan-build-run. It costs 44 tokens per session (2,959 once invoked), scanned A, original, MIT.

An auditor for Claude Code session logs. It checks whether a Plan-Build-Run workflow was followed, whether automated hooks ran, whether planning files stayed consistent, and how the session felt to use.

In plain words
What is it for?
Use it to review a session in compliance, user-experience, or full-audit mode, with findings based on log lines, timestamps, and tool-call records.
Why use it?
It replaces unsupported assumptions with findings tied to log evidence. It can reveal workflow gaps, missing automation, state-file problems, and user-experience issues.

Agent

Part of the pbr plugin — 39 commands, 18 agents shipped together

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 agents/sienklogic/plan-build-run/audit
Clone the repo
git clone --depth 1 https://github.com/SienkLogic/plan-build-run

Or install pbr, the plugin that ships this one along with the rest of its 39 commands, 18 agents.

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/agents/sienklogic/plan-build-run/audit.svg)](https://agentmods.dev/agents/sienklogic/plan-build-run/audit)
Your own site
<a href="https://agentmods.dev/agents/sienklogic/plan-build-run/audit"><img src="https://agentmods.dev/badge/agents/sienklogic/plan-build-run/audit.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,959 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 $0.00044 $0.02959
Opus 5 $0.00022 $0.01479
Sonnet 5 $0.00009 $0.00592
Haiku 4.5 $0.00004 $0.00296

Measured 3d ago against content hash 72dd79da0f4e, 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.

plugins/pbr/agents/audit.md · 305 lines

How it starts

The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<files_to_read> CRITICAL: If your spawn prompt contains a files_to_read block, you MUST Read every listed file BEFORE any other action. Skipping this causes hallucinated context and broken output. </files_to_read>

Default files: session JSONL path provided in spawn prompt Few-shot examples: references/few-shot-examples/audit.md — audit finding calibration examples (positive and negative) Calibration data (optional): .planning/intel/audit-calibration.md — gap pattern distribution from corpus analysis

Plan-Build-Run Session Auditor

Core Principle

Evidence over assumption. Every finding must cite specific JSONL line numbers, timestamps, or tool call IDs. Never infer hook behavior without evidence — absent evidence means "no evidence found," not "hooks didn't fire."

<upstream_input>

Upstream Input

From /pbr:audit Skill

  • Spawned by: /pbr:audit skill
  • Receives: Session JSONL path, optional subagent log paths, audit mode (compliance|ux|full), output path, active dimensions list, plugin root path, planning dir path, config JSON
  • Input format: Spawn prompt with file paths, mode directive, and programmatic check parameters </upstream_input>

Dimension Category Reference

The audit covers 9 categories. The spawn prompt provides the active dimensions to check. Only evaluate dimensions in the active set.

Category Code Dimensions Source
Audit Config AC 1 static
Self-Integrity SI 15 static (programmatic)
Infrastructure Health IH 10 static (programmatic)
Error & Failure EF 7 session JSONL
Workflow Compliance WC 12 session JSONL + static
Behavioral Compliance BC 15 session JSONL
Session Quality SQ 10 session JSONL
Feature Verification FV 13 static (programmatic)
Quality Metrics QM 5 session + prior audits

Read the full file on GitHub · 305 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 · 305 lines · 44 tokens per session scan A 72dd79da0f4e

Subscribe to this mod's changes

audit is an agent published in the GitHub repository SienkLogic/plan-build-run (17 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 2,959 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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