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.
npx agentmods add instructions/skynetcmd/m3-memory/agents-mdgit clone --depth 1 https://github.com/skynetcmd/m3-memoryWhat 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 | $0.00509 | $0.00509 |
| Opus 5 | $0.00254 | $0.00254 |
| Sonnet 5 | $0.00102 | $0.00102 |
| Haiku 4.5 | $0.00051 | $0.00051 |
Grade A, and why
m3-memory 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.
How it starts
The opening of the file, as written. The whole thing — 16 lines — stays where its author put it; the contents beside it link to each section on GitHub.
docs/AGENT_INSTRUCTIONS.md
Git Standards
- Commit Messages: Do NOT include "Co-Authored-By" lines in commit messages. Focus on clear, concise descriptions of "why" and "what".
- Pre-push process (MANDATORY, all agents): After cloning, run
python bin/setup_hooks.pyonce to enable the shared pre-push gate. Before any push, the tool-catalog drift check (python bin/check_tool_catalog_drift.py) and bench-data leakage scan must pass. If you changebin/mcp_tool_catalog.py, regenerate the catalog/inventory and update the "N tools" counts in the same change. Full rationale: the "Pre-push process — ALL agents" section indocs/AGENT_INSTRUCTIONS.md. This is enforced by the local hook AND CI, not just convention.
Homecoming Architecture
- Decoupled Roots: Persistent state is split across three roots so databases and configuration can be relocated and secured independently. All three are overridable via the matching env var.
- Data Location:
- Databases + runtime state —
M3_ENGINE_ROOT, default~/.m3/engine:agent_memory.db,agent_chatlog.db,files_database.db, chatlog spill,logs/ - Configs —
M3_CONFIG_ROOT, default~/.m3/config:.chatlog_config.json,.migrate_config.json,.agent_os_salt - Payload / repo clone —
M3_MEMORY_ROOT, default~/.m3-memory
- Databases + runtime state —
- Precedence:
M3_ENGINE_ROOT/M3_CONFIG_ROOT→M3_MEMORY_ROOT/{engine,config}→~/.m3/{engine,config}.M3_MEMORY_ROOTacts as a master override only when the specific vars are unset; a specific root always wins. Canonical implementation:get_m3_engine_root()/get_m3_config_root()inbin/m3_core/paths.py. - Split-brain hazard: the MCP server reads roots from its
envblock in client settings, while hooks inherit the client's process env. PinM3_ENGINE_ROOT+M3_CONFIG_ROOTin both or the server and the chatlog hook will write to different stores. - Migration: Use
bin/homecoming.pyto relocate legacy repo-relative state to the new home root.
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.
- 2d ago First seen · 16 lines · 509 tokens per session scan A 312fc9eb1e22
m3-memory AGENTS.md is an instructions file published in the GitHub repository skynetcmd/m3-memory (22 stars, last pushed 3d ago), licensed Apache-2.0. It adds 509 tokens to every session, about $0.0025 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.
Other instructions, from other repositories
hybridclaw AGENTS.md
Instructions for HybridAIOne/hybridclaw, covering agents.md — hybridclaw engineering protocol, scope, 1) project snapshot, 2) project map and key data flows.
hybridclaw CLAUDE.md
Instructions for HybridAIOne/hybridclaw: Follow AGENTS.md as the canonical repo instruction set for this repository.
obsidian-llm-hub CLAUDE.md
Instructions for takeshy/obsidian-llm-hub, covering claude.md, project overview, build commands, version bumping and architecture.
obsidian-llm-hub AGENTS.md
Instructions for takeshy/obsidian-llm-hub, a project described as: Obsidian plugin for AI chat, workflow automation, and semantic search — supports Gemini, OpenAI, OpenRouter, Grok, Ollama, and CLI backends.
gemini-cli-desktop AGENTS.md
Instructions for Piebald-AI/gemini-cli-desktop, a project described as: Web/desktop UI for Gemini CLI/Qwen Code. Manage projects, switch between tools, search across past conversations, and manage MCP servers, all from one multilingual interface, locally or remotely.
codmate AGENTS.md
Instructions for loocor/codmate, a project described as: CodMate is a macOS SwiftUI app for managing CLI AI sessions: browse, search, organize, resume, and review work produced by Codex, Claude Code, and Gemini CLI. It focuses on speed, a compact three-column UI, and “ship it” workflows like Project Review (Git…