Borrowing it
Nothing to install: this file belongs to tm42/mnemograph. 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/tm42/mnemograph/main/CLAUDE.mdgit clone --depth 1 https://github.com/tm42/mnemographWrote 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/tm42/mnemograph/claude-md)<a href="https://agentmods.dev/instructions/tm42/mnemograph/claude-md"><img src="https://agentmods.dev/badge/instructions/tm42/mnemograph/claude-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/tm42/mnemograph/claude-md"><img src="https://agentmods.dev/badge/instructions/tm42/mnemograph/claude-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 | $0.02810 | $0.02810 |
| Opus 5.5 | $0.01124 | $0.01124 |
| Sonnet 5.5 | $0.00562 | $0.00562 |
| Haiku 4.5 | $0.00281 | $0.00281 |
Grade A, and why
mnemograph CLAUDE.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 2mo 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 — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Code Memory System — Project Brief
For: Claude Code instance working on this project From: Claude (claude.ai session) + M (the human) Date: January 2025
What We're Building
A graph-based long-term memory system for Claude Code that:
- Persists knowledge across sessions (projects, decisions, patterns, learnings)
- Uses event sourcing for full history (branch, revert, review changes)
- Supports tiered retrieval (shallow context → deep subgraph → synthesized)
- Enables partnership learning — not just "user preferences" but collaborative knowledge
- Runs as an MCP server that CC can query naturally
This is NOT another "remember user likes dark mode" system. This is a shared knowledge graph between human and Claude that grows over time, capturing architectural decisions, learned patterns, open questions, and project understanding.
Architecture Overview
Language: Pure Python with MCP SDK. TypeScript adapter optional for ecosystem compatibility.
Layers:
- MCP Server (
server.py): Handles stdio transport, defines tool schemas - Memory Engine (
engine.py): Orchestrates all modules - Query Service (
query.py): Read-only queries — recall, search, health checks, weight inspection - Event Store (
events.py): SQLite-backed append-only event log (source of truth) - State (
state.py): Materialized graph computed from events - Vectors (
vectors.py): sqlite-vec embeddings in same database - Retrieval (
retrieval.py): Tiered context (shallow/medium/deep) - Time Travel (
time_travel.py): Event rewind and state restoration - Similarity (
similarity.py): Duplicate detection and entity matching - Branches (
branches.py): Filtered views of the knowledge graph - Constants (
constants.py): Centralized tunable parameters (weights, limits, time constants) - Weights (
weights.py): Edge weight computation and weighted traversal
Storage (<project>/.claude/memory/):
mnemograph.db— SQLite database (events + vectors in one file)state.json— Cached materialized state
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.
- 2mo ago First seen · 274 lines · 2,810 tokens per session scan A 5a3f24a6f7f5
mnemograph CLAUDE.md is an instructions file published in the GitHub repository tm42/mnemograph (2 stars, last pushed 8mo ago), licensed MIT. It adds 2,810 tokens to every session, about $0.0112 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
repobrain copilot-instructions.md
Copilot instructions for study8677/repobrain, covering github copilot bootstrap instructions and hard rule — query the repobrain hub first.
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).