What is adaptive-memory-graph CLAUDE.md?

Project instructions for an adaptive memory graph, a system that stores connected knowledge from past conversations and retrieves relevant context later.

Use them to guide an agent working with the adaptive-memory-graph project and its memory tools.

They define when to load, expand, and update persistent memory while keeping unrelated personal or professional information separate.

How raskolnikovdd/adaptive-memory-graph configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to raskolnikovdd/adaptive-memory-graph. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/raskolnikovdd/adaptive-memory-graph/main/CLAUDE.md

Clone the repo

git clone --depth 1 https://github.com/raskolnikovdd/adaptive-memory-graph

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/raskolnikovdd/adaptive-memory-graph/claude-md/github.svg)](https://agentmods.dev/instructions/raskolnikovdd/adaptive-memory-graph/claude-md)

Your own site

<a href="https://agentmods.dev/instructions/raskolnikovdd/adaptive-memory-graph/claude-md"><img src="https://agentmods.dev/badge/instructions/raskolnikovdd/adaptive-memory-graph/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.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/raskolnikovdd/adaptive-memory-graph/claude-md"><img src="https://agentmods.dev/badge/instructions/raskolnikovdd/adaptive-memory-graph/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 484 This file is loaded in full into every session.

When invoked 484 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00484	$0.00484
Opus 5.5	$0.00194	$0.00194
Sonnet 5.5	$0.00097	$0.00097
Haiku 4.5	$0.00048	$0.00048

Measured 2mo ago against content hash 967f5d0797d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

adaptive-memory-graph 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.

CLAUDE.md · 38 lines

How it starts

The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adaptive Memory Graph — Runtime Instructions

This project is an MCP server plugin that provides Claude with persistent, intelligent memory across sessions via a weighted graph of interconnected knowledge nodes.

Runtime Behaviour

At the start of each conversation, call amg_load_index() to receive a lightweight map of the user's memory graph. Use this map as background awareness only — do not reference it unless contextually relevant.

If the conversation touches a domain or topic that clearly warrants deeper context, call amg_expand_branch() for the relevant node. Be conservative: only expand when it would genuinely improve your response.

Do not surface personal nodes during professional work sessions, and vice versa, unless explicitly relevant.

At the end of each conversation, call amg_log_session() with a summary of which branches were accessed, which were engaged with, and any suggested new nodes. Do this silently — do not narrate this process to the user.

If the user explicitly corrects a memory ("that's not relevant" / "stop bringing that up"), record this as an explicit correction in the session log.

Available Tools

amg_load_index — Load lightweight index at session start
amg_expand_branch — Fetch full node content when contextually relevant
amg_get_connected_nodes — Find related nodes across domains
amg_log_session — Log session summary at conversation end
amg_update_graph — Process pending logs and apply decay
amg_export_report — Generate human-readable graph summary
amg_manual_adjust — Boost, decay, archive, or delete nodes
amg_add_node — Manually add new nodes to the graph
amg_search_nodes — Search nodes by title, summary, tags, or content

Project Structure

src/graph.py — Core graph data model (Node, Graph, SessionLog)
src/crypto.py — AES-256-GCM encryption with macOS Keychain key storage
src/storage.py — Storage abstraction (LocalStorageBackend)
src/update.py — Weight update, decay, and pruning logic
src/server.py — MCP server entry point with all tool definitions
migrations/v1_0.py — Schema migration scripts
tests/test_graph.py — Test suite

Read the full file on GitHub · 38 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.

2mo ago First seen · 38 lines · 484 tokens per session scan A 967f5d0797d4

Subscribe to this mod's changes

adaptive-memory-graph CLAUDE.md is an instructions file published in the GitHub repository raskolnikovdd/adaptive-memory-graph (0 stars, last pushed 8mo ago), licensed MIT. It adds 484 tokens to every session, about $0.0019 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.

Memory and context

adaptive-memory-graph CLAUDE.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
adaptive-memory-graph CLAUDE.mdraskolnikovdd/adaptive-memory-graph	Instructions file	0	8mo ago	MIT	A	484	Claude Code
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

adaptive-memory-graph: Instructions file for Claude Code