securellm-mcp AGENTS.md

Repository instructions that tell coding agents how to make careful, secure, maintainable changes. They emphasize understanding the existing architecture before editing it.

In plain words
What is it for?
Guiding agent work in the VoidNxSEC/securellm-mcp repository, especially when planning, implementing, and verifying code changes.
Why use it?
They reduce accidental conflicts with established code structure and help agents preserve reliability, testability, security, and observability.

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/voidnxsec/securellm-mcp/agents-md
Clone the repo
git clone --depth 1 https://github.com/VoidNxSEC/securellm-mcp

Made for: Codex, OpenCode.

Per session 4,539 This file is loaded in full into every session.
When invoked 4,539 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 $0.04539 $0.04539
Opus 5 $0.02269 $0.02269
Sonnet 5 $0.00908 $0.00908
Haiku 4.5 $0.00454 $0.00454

Measured 2d ago against content hash ee998a311cd1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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 · 1,169 lines

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:

  1. Explicit user request for the current task.
  2. Security, privacy, and safety requirements.
  3. This AGENTS.md.
  4. More specific nested AGENTS.md files.
  5. Existing project conventions.
  6. 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:

Read the full file on GitHub · 1,169 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. 2d ago First seen · 1,169 lines · 4,539 tokens per session scan A ee998a311cd1

Subscribe to this mod's changes

securellm-mcp AGENTS.md is an instructions file published in the GitHub repository VoidNxSEC/securellm-mcp (0 stars, last pushed 27d ago), licensed Apache-2.0. It adds 4,539 tokens to every session, about $0.0227 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.