Borrowing it
Nothing to install: this file belongs to VoidNxSEC/securellm-mcp. 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/VoidNxSEC/securellm-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/VoidNxSEC/securellm-mcpWrote 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/voidnxsec/securellm-mcp/agents-md)<a href="https://agentmods.dev/instructions/voidnxsec/securellm-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/voidnxsec/securellm-mcp/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/voidnxsec/securellm-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/voidnxsec/securellm-mcp/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 | $0.04539 | $0.04539 |
| Opus 5.5 | $0.01816 | $0.01816 |
| Sonnet 5.5 | $0.00908 | $0.00908 |
| Haiku 4.5 | $0.00454 | $0.00454 |
Grade A, and why
securellm-mcp 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.
How it starts
The opening of the file, as written. The whole thing — 1,169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Purpose
This file defines how AI agents should operate inside this repository.
The goal is to produce reliable, auditable, secure, and maintainable changes with minimal noise and maximum respect for the existing architecture.
Agents should act like careful engineering collaborators: understand the system first, make scoped changes, verify their work, and leave a clear handoff.
1. Core Operating Principles
1.1 Respect the Existing System
Before changing code, understand:
- What the current architecture is trying to preserve.
- Which conventions are already present.
- Which modules own which responsibilities.
- Which abstractions are stable and which are still experimental.
- Which files are generated, vendored, or externally managed.
Prefer extending existing patterns over introducing isolated new ones.
1.2 Optimize for Coherence
Every change should improve or preserve:
- Architectural coherence.
- Security posture.
- Operational reliability.
- Testability.
- Reproducibility.
- Observability.
- Developer experience.
A technically clever solution that breaks the shape of the system is usually worse than a smaller coherent change.
1.3 Work in Small, Auditable Steps
Prefer small, reviewable patches.
Each meaningful change should have:
- A clear reason.
- A clear scope.
- A clear verification path.
- A clear rollback path when possible.
1.4 Treat Instructions as a Hierarchy
When instructions conflict, follow this priority order:
- Explicit user request for the current task.
- Security, privacy, and safety requirements.
- This
AGENTS.md. - More specific nested
AGENTS.mdfiles. - Existing project conventions.
- General best practices.
Nested AGENTS.md files apply to their directory subtree.
2. Agentic Workflow
Use this loop for every non-trivial task:
INTAKE
↓
UNDERSTAND CONTEXT
↓
MAP CURRENT STATE
↓
PLAN
↓
IMPLEMENT
↓
VERIFY
↓
DOCUMENT / HANDOFF
2.1 Intake
Clarify internally:
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 · 1,169 lines · 4,539 tokens per session scan A ee998a311cd1
securellm-mcp AGENTS.md is an instructions file published in the GitHub repository VoidNxSEC/securellm-mcp (0 stars, last pushed 24d ago), licensed Apache-2.0. It adds 4,539 tokens to every session, about $0.0182 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.
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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.