Borrowing it
Nothing to install: this file belongs to kappa9999/white-hat-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/kappa9999/white-hat-agent/main/AGENTS.mdgit clone --depth 1 https://github.com/kappa9999/white-hat-agentWrote 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/instructions/kappa9999/white-hat-agent/agents-md)<a href="https://agentmods.dev/instructions/kappa9999/white-hat-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/kappa9999/white-hat-agent/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/kappa9999/white-hat-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/kappa9999/white-hat-agent/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00298 | $0.00298 |
| Opus 5.5 | $0.00119 | $0.00119 |
| Sonnet 5.5 | $0.00060 | $0.00060 |
| Haiku 4.5 | $0.00030 | $0.00030 |
Grade A, and why
white-hat-agent 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 1mo 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.
What it actually says
White Hat Agent Core
- Build a model-neutral public application layer for composable, evidence-backed cyber discovery.
- Optimize for novel, causally verified, reproducible discoveries per unit of cost.
- Preserve exact target identity, evidence provenance, negative results, and alternate findings.
- Keep the corpus capable of representing techniques from every cyber domain and perspective. Execution scope is campaign data, not a knowledge-censorship mechanism.
- Keep the core target-neutral and model-neutral. Side effects belong behind explicit adapters; planners emit typed operations rather than tool-specific shell prose.
- Community knowledge must retain original language and source provenance, compile into strict versioned playbooks, and remain reviewable before promotion.
- MCP surfaces are namespaced, bounded, and structured. Prefer stdio and stateless Streamable HTTP; do not add SSE.
- Fleet mutations require explicit campaign, target, lease, and evidence identities.
- Every planning decision must be deterministic from the episode manifest and explain its score and blockers.
- A changed hypothesis revision may justify a new probe; an unchanged failed probe must not be retried blindly.
- Treat apparent success as a hypothesis until causal and differential checks establish the actual path.
- Use bounded replay or synthetic fixtures for routine tests. Adapter-specific integration tests own their environments.
- Use
apply_patchfor hand-authored changes and run corpus/schema validation,pytest,ruff check, package build, and MCP smoke tests before handoff.
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.
- 1mo ago First seen · 20 lines · 298 tokens per session scan A 0215bf68bd1d
white-hat-agent AGENTS.md is an instructions file published in the GitHub repository kappa9999/white-hat-agent (0 stars, last pushed 13d ago), licensed Apache-2.0. It adds 298 tokens to every session, about $0.0012 per session on Opus 5.5. 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 instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.