AgentCheck AGENTS.md

AgentCheck AGENTS.md is an instructions file for Codex, OpenCode from WaseemGhanem98/AgentCheck. It costs 1,617 tokens per session, scanned A, original, Apache-2.0.

Repository instructions for AgentCheck, a tool that tests AI-agent behavior in simulated child processes and produces verdicts, reports, and replay data.

In plain words
What is it for?
Use them when changing AgentCheck code, its evaluation rules, serialized data, or HTML-report and replay outputs.
Why use it?
They preserve the evidence and safety rules needed for trustworthy test results, including preventing the original tool handler from running.

Instructions file for CodexOpenCode

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 instructions/waseemghanem98/agentcheck/agents-md
Clone the repo
git clone --depth 1 https://github.com/WaseemGhanem98/AgentCheck

Made for: Codex, OpenCode.

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 AgentCheck AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/waseemghanem98/agentcheck/agents-md.svg)](https://agentmods.dev/instructions/waseemghanem98/agentcheck/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/waseemghanem98/agentcheck/agents-md"><img src="https://agentmods.dev/badge/instructions/waseemghanem98/agentcheck/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,617 This file is loaded in full into every session.
When invoked 1,617 The same file — it is already loaded in full.
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 $0.01617 $0.01617
Opus 5 $0.00809 $0.00809
Sonnet 5 $0.00323 $0.00323
Haiku 4.5 $0.00162 $0.00162

Measured 4d ago against content hash aad7113d5e40, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

AgentCheck AGENTS.md 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.

AGENTS.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — working on AgentCheck

Instructions for AI coding agents and new contributors working in this repository. Read this before changing anything under agentcheck/.

What this project is

AgentCheck is an evidence authority for AI-agent behavior, not a framework compatibility layer. It imports a trusted local agent, derives adversarial scenarios from what it finds, and runs them in same-user child processes where declared tool calls are simulated. It emits PASS / FAIL / INCONCLUSIVE / INFRA_ERROR, an HTML report, and a replay manifest.

The product's value is that its verdicts can be trusted. Every rule below exists to protect that.

Keep four evidence dimensions separate: contained, observed, semantically understood, and policy-verifiable. One never implies the next. A blocked and observed runtime action with unknown semantics remains INCONCLUSIVE, never a PASS. Static discovery is lower-bounded, not exhaustive.

Non-negotiable invariants

Breaking any of these is a correctness bug, not a style issue:

  1. The original tool handler never executes during a simulated evaluation. Interception replaces the invoker before the handler is reached.
  2. Unknown tools fail closed. Never synthesize a tool result.
  3. No real mutations. Only the simulated world changes.
  4. Worker isolation. Scenarios run in child processes; the environment allowlist is empty by default. This is trusted-code process isolation, not a hostile-code sandbox.
  5. Network denied by default, and containment failures surface. The current Python guard is not a kernel security boundary and must not be described as one.
  6. INCONCLUSIVE and INFRA_ERROR never collapse into PASS.
  7. Redaction at the artifact and log boundary, before writing or printing.
  8. Never overstate replay. It reproduces inputs and harness behavior, not model determinism.

Layout

Path Role
agentcheck/domain/ Contract models: scenarios, specs, runs, verdicts, findings. Fingerprinted and versioned.
agentcheck/adapters/ The only layer allowed to import a framework SDK.
agentcheck/inspect/ Import a target and extract an AgentSpec without running a turn.
agentcheck/generate/ Derive, lint, select, and freeze suites.
agentcheck/coverage/ Derived behavioral coverage over a spec and a scenario set. Pure contract analysis; imports no target.
agentcheck/runner/ Orchestrator, worker, tool gateway, simulated world, budgets, network guard.
agentcheck/evaluate/ Oracle evaluation and verdict assignment.
agentcheck/replay/ Manifests, source binding, filesets.
agentcheck/report/, agentcheck/baseline/, agentcheck/review/ Reporting, CI gating, human decisions on findings.
agentcheck/regression/ Run-to-run behavioral comparison over stored artifacts. Executes nothing.
agentcheck/gate.py The CI decision: runs the suite, compares the baseline, and answers whether a change blocks the build. Orchestrates the above; decides no verdicts of its own.
agentcheck/identity.py Portable target identity and its bounded legacy compatibility path.
agentcheck/redaction.py, agentcheck/privacy.py Credential redaction for artifacts and logs.
agentcheck/cli.py The agentcheck command.
spikes/environment_containment/ Repository-only, provider-neutral research contracts. Control metadata stays outside its minimal target leaves and never ships in distributions.

Read the full file on GitHub · 131 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. 4d ago First seen · 131 lines · 1,617 tokens per session scan A aad7113d5e40

Subscribe to this mod's changes

AgentCheck AGENTS.md is an instructions file published in the GitHub repository WaseemGhanem98/AgentCheck (19 stars, last pushed today), licensed Apache-2.0. It adds 1,617 tokens to every session, about $0.0081 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.