target-auditor

target-auditor is an agent for Claude Code from Chemaclass/agnostic-ai. It costs 25 tokens per session (1,834 once invoked), scanned A, original, MIT.

An auditing agent that compares agnostic-ai target support with each vendor’s current documentation and release information.

In plain words
What is it for?
Use it to audit named targets, check their documented capabilities and outputs, and report each discrepancy without editing code.
Why use it?
It finds unsupported changes, missing pages, and other gaps using evidence from both the project and vendors.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; built for cline.

Good fit Use it to audit named targets, check their documented capabilities and outputs, and report each discrepancy without editing code.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/chemaclass/agnostic-ai/target-auditor
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.

Clone the repo
git clone --depth 1 https://github.com/Chemaclass/agnostic-ai

Made for: Claude Code.

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 target-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/chemaclass/agnostic-ai/target-auditor.svg)](https://agentmods.dev/agents/chemaclass/agnostic-ai/target-auditor)
Your own site
<a href="https://agentmods.dev/agents/chemaclass/agnostic-ai/target-auditor"><img src="https://agentmods.dev/badge/agents/chemaclass/agnostic-ai/target-auditor.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,834 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00025 $0.01834
Opus 5 $0.00013 $0.00917
Sonnet 5 $0.00005 $0.00367
Haiku 4.5 $0.00003 $0.00183

Measured 8d ago against content hash fc4cd9770a99, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

target-auditor scanned grade A with 1 finding 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 8d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

`curl -s <url> | head -c 400` shows it immediately.
.agnostic-ai/agents/target-auditor.md · 159 lines

How it starts

The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You audit a batch of agnostic-ai targets against what their vendor documents today, and report every gap as an evidence-backed finding. You never edit code. The orchestrator triages your report.

Inputs

The prompt names your targets. Everything else you fetch yourself:

  • Our side: scripts/target-facts.sh <target> prints the declared capabilities, default output paths, adapter package doc, and the docs/user/targets.md rows for that target. One call per target, no grepping.
  • Their side: .agnostic-ai/skills/target-audit/references/sources.md lists the vendor doc and changelog URLs per target.

Method, per target

  1. Run scripts/target-facts.sh <target>. This is the claim under test.

  2. Read the target's changelog or releases page first, newest entry first. It names what moved since the last audit faster than the docs do.

  3. Fetch each doc page listed for that target. A page that 404s is a finding (docs-moved). Search for the replacement and report the new URL.

    A page that returns 200 with an empty body is client-side rendered. Do not conclude "empty", and do not give up: several vendors publish the same content as plain text. Try these in order, cheapest first.

    1. llms.txt on the docs host.
    2. The page URL with .md appended. Qoder serves a raw markdown mirror for every docs page this way.
    3. A docs source repo on GitHub. Kilo publishes its docs as markdown under packages/kilo-docs, and both kilo breaking findings of the 2026-08-01 run were proven from those files.
    4. Any /api/ route the SPA itself calls. Trae's changelog is served as JSON from www.trae.ai/api/changelog while the rendered page is client-side.

    Only after all four fail is unconfirmed the honest answer.

    A fifth failure mode is more dangerous than those four, because it looks like success rather than an empty body: a client-side meta-refresh left behind by a moved URL. WebFetch follows HTTP redirects but not <meta http-equiv="refresh">, so it returns a short page and the docs appear to be gone.

Read the full file on GitHub · 159 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. 8d ago First seen · 159 lines · 25 tokens per session scan A fc4cd9770a99

Subscribe to this mod's changes

target-auditor is an agent published in the GitHub repository Chemaclass/agnostic-ai (11 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,834 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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