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.
npx agentmods add commands/phazurlabs/install-labs/agent-auditgit clone --depth 1 https://github.com/phazurlabs/install-labsWrote 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/commands/phazurlabs/install-labs/agent-audit)<a href="https://agentmods.dev/commands/phazurlabs/install-labs/agent-audit"><img src="https://agentmods.dev/badge/commands/phazurlabs/install-labs/agent-audit.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.03511 |
| Opus 5 | $0.00008 | $0.01755 |
| Sonnet 5 | $0.00003 | $0.00702 |
| Haiku 4.5 | $0.00002 | $0.00351 |
Grade A, and why
agent-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 4d 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/agent-audit — Packaging Readiness Audit
Purpose
Audit an AI agent or automation for packaging readiness BEFORE generating any packaging files. Identifies structural blockers, dependency gaps, configuration problems, and documentation holes that would cause install failures if shipped as-is.
Protocol
When the user invokes /agent-audit, follow this process exactly:
Step 1: Identify the Agent to Audit
Ask the user to point to their agent. Accept any of these:
- A local directory path — Read the directory structure, key files (
requirements.txt,package.json,pyproject.toml,Dockerfile,.env.example,README.md, entry point files), and infer the agent's architecture. - A GitHub repository URL — Clone or browse the repo to examine the same files.
- A verbal description — If the user describes their agent without pointing to code, audit based on what they describe. Flag anything you cannot verify as "Unable to assess — no code provided."
- Context from a prior
/agent-guideconversation — If the user already ran/agent-guidein this session, use the assessment from that step. Do not re-ask questions already answered.
If examining code, look for these files to understand the agent:
| File | What It Tells You |
|---|---|
requirements.txt / pyproject.toml / Pipfile |
Python dependencies, version pinning |
package.json / package-lock.json |
Node.js dependencies, scripts, entry point |
Dockerfile / docker-compose.yml |
Containerization strategy |
.env / .env.example |
Configuration and secrets pattern |
.gitignore |
Whether secrets and build artifacts are excluded |
README.md |
Documentation quality |
crew.yaml / agents.yaml / tasks.yaml |
CrewAI configuration |
langgraph.json |
LangGraph configuration |
main.py / app.py / index.ts / server.ts |
Entry point clarity |
tests/ directory |
Test coverage |
Makefile / justfile / taskfile.yml |
Task runner / build system |
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.
- 4d ago First seen · 285 lines · 15 tokens per session scan A ad19f38d019f
agent-audit is a command published in the GitHub repository phazurlabs/install-labs (3 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 15 tokens to every session and 3,511 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
build
Run full verification pipeline.
quality
Review code for quality improvements.
refactor
Suggest refactoring opportunities.
security-review
Review code for security vulnerabilities.
test-coverage
Analyze test coverage and suggest improvements.
test-e2e
Write end-to-end tests for critical user journeys.