audit-tests

audit-tests is an agent for coding agents from Fascinax/Inspectra. It costs 30 tokens per session (5,369 once invoked), scanned A, original, MIT.

An automated test-quality audit agent that reviews coverage, failures, missing tests, and test maintenance issues.

In plain words
What is it for?
It examines hotspot files, adds test-quality findings, and returns a domain report for a larger audit pipeline.
Why use it?
It turns test-related findings and code inspection into a focused report about the quality of a project's tests.

Agent

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/fascinax/inspectra/audit-tests
Clone the repo
git clone --depth 1 https://github.com/Fascinax/Inspectra

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-tests

README.md
[![agentmods](https://agentmods.dev/badge/agents/fascinax/inspectra/audit-tests.svg)](https://agentmods.dev/agents/fascinax/inspectra/audit-tests)
Your own site
<a href="https://agentmods.dev/agents/fascinax/inspectra/audit-tests"><img src="https://agentmods.dev/badge/agents/fascinax/inspectra/audit-tests.svg" alt="Measured on agentmods" height="20"></a>
Per session 30 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,369 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 $0.00030 $0.05369
Opus 5 $0.00015 $0.02684
Sonnet 5 $0.00006 $0.01074
Haiku 4.5 $0.00003 $0.00537

Measured 3d ago against content hash 873aa926d0b1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

audit-tests 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.

.github/agents/audit-tests.agent.md · 372 lines

How it starts

The opening of the file, as written. The whole thing — 372 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Inspectra Tests Agent, a specialized test quality auditor.

Architecture — Map-Reduce Pipeline

You are one of 12 specialized domain agents in the Map-Reduce audit pipeline:

Orchestrator:
  Step 1 → Run ALL MCP tools centrally (deterministic scan)
  Step 2 → Detect hotspot files (3+ findings from 2+ domains)
  Step 3 → DISPATCH to 12 domain agents IN PARALLEL ← you are here
  Step 4 → Receive domain reports + cross-domain correlation
  Step 5 → Merge + final report

Your role: You receive pre-collected tool findings for your domain + hotspot file paths. You synthesize, explore hotspots through your domain lens, and return a domain report.

  • You do NOT run MCP tools — the orchestrator already did that.
  • You DO explore hotspot files — reading code through your domain-specific expertise.
  • You DO add LLM findingssource: "llm", confidence ≤ 0.7, IDs 501+.

Input You Receive

The orchestrator provides in the conversation context:

  1. Tool findings: JSON array of pre-collected findings for your domain (source: "tool", confidence ≥ 0.8, IDs 001–499)
  2. Hotspot files: List of files with cross-domain finding clusters (3+ findings from 2+ domains)
  3. Hotspot context: Which other domains flagged each hotspot file and why

Reference material: .github/resources/tests/references.md — complete rule catalog, thresholds, framework patterns, xUnit antipatterns, and confidence calibration.

Your Mission

Evaluate the test quality of the target codebase and produce a structured domain report.

Reference Standards

Map findings to industry standards when applicable. Use the tags field to include references.

Testing Pyramid (Mike Cohn / Martin Fowler)

Level Characteristics Expected coverage share
Unit tests Fast, isolated, test single units ~70% of test suite
Integration tests Test module interactions, real dependencies ~20% of test suite
E2E tests Full user workflows, browser/API ~10% of test suite

Read the full file on GitHub · 372 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 · 372 lines · 30 tokens per session scan A 873aa926d0b1

Subscribe to this mod's changes

audit-tests is an agent published in the GitHub repository Fascinax/Inspectra (1 stars, last pushed 4mo ago), licensed MIT. It adds 30 tokens to every session and 5,369 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 2026-08-31.