mem-graph AGENTS.md

Repository-specific instructions for working on the GoVanAI/mem-graph project and its Cognitive OS framework. They define which project scope to use, require a startup process for substantial work, and describe safety and collaboration rules.

In plain words
What is it for?
Guiding coding-agent work on mem-graph, including Cognitive OS governance, project tracking, repository maintenance, releases, and safe collaboration.
Why use it?
They reduce mistakes caused by using the wrong project context, editing generated files, or changing shared progress records incorrectly.

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/govanai/mem-graph/agents-md
Clone the repo
git clone --depth 1 https://github.com/GoVanAI/mem-graph

Made for: Codex, OpenCode.

Per session 811 This file is loaded in full into every session.
When invoked 811 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 $0.00811 $0.00811
Opus 5 $0.00405 $0.00405
Sonnet 5 $0.00162 $0.00162
Haiku 4.5 $0.00081 $0.00081

Measured 2d ago against content hash 181dd9cad35e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mem-graph 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 · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Mem-Graph Project Instructions for Codex

This file adds repository-specific routing to the global agent rules. It is a bootstrap contract, not a duplicate project-status document.

Use the repo-scoped $mem-graph-practice skill for any non-trivial mem-graph or Cognitive OS task. The vendor-neutral source contract is cognitive-os/agent-practice/practice.v1.json; generated host adapters must not be edited by hand.

Scope

Cognitive OS is a global, cross-project agent framework. This repository is its current additive proving ground and persistence substrate; it is not the framework's architectural boundary. Canonical tracker and scope-boundary IDs are deployment-local and must come from operator or project configuration, not from this repository.

Keep scopes distinct:

  • use project_id=cognitive-os for Cognitive OS governance, experiments, policies, event evidence, roadmap work, and program state;
  • use the applicable mem-graph project scope for substrate maintenance, releases, and unrelated runtime work; and
  • never treat cross-project availability as automatic applicability.

Mandatory Cognitive OS Bootstrap

Before non-trivial Cognitive OS work:

  1. Prefer cognitive_agent_bootstrap with project_id=cognitive-os, a narrow task query, include_canonical_content=true, and include_global=false unless global guidance is explicitly required. Supply canonical_ids only when the operator or project has configured them; otherwise omit the field and use the governing lane to discover candidates. This tool is strictly read-only and does not touch access tracking or append a receipt.
  2. Directly verify any candidate tracker, scope boundary, or role record before using it. When a canonical tracker is resolved, read the roadmap and active artifacts it references before changing implementation or making a milestone claim.
  3. Fetch selected known records directly when their full content or authority still needs verification.
  4. If the bootstrap tool is unavailable, use the dynamic fallback sequence: resolve deployment-local canonical IDs from operator/project configuration or exact-project governing guidance; memory_get each resolved record; then read referenced roadmap/artifacts and run cognitive_policy_lookup using request_type/current_canonical_guidance, exact-project cognitive_current_guidance_search or diagnosis, and direct fetch of each selected record.

Read the full file on GitHub · 85 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 · 85 lines · 811 tokens per session scan A 181dd9cad35e

Subscribe to this mod's changes

mem-graph AGENTS.md is an instructions file published in the GitHub repository GoVanAI/mem-graph (0 stars, last pushed 24d ago), licensed MIT. It adds 811 tokens to every session, about $0.0041 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.

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