Borrowing it
Nothing to install: this file belongs to elViRafa/agentic-memory. 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/elViRafa/agentic-memory/main/CLAUDE.mdgit clone --depth 1 https://github.com/elViRafa/agentic-memoryWrote 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/elvirafa/agentic-memory/claude-md)<a href="https://agentmods.dev/instructions/elvirafa/agentic-memory/claude-md"><img src="https://agentmods.dev/badge/instructions/elvirafa/agentic-memory/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/elvirafa/agentic-memory/claude-md"><img src="https://agentmods.dev/badge/instructions/elvirafa/agentic-memory/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 | $0.01128 | $0.01128 |
| Opus 5.5 | $0.00451 | $0.00451 |
| Sonnet 5.5 | $0.00226 | $0.00226 |
| Haiku 4.5 | $0.00113 | $0.00113 |
Grade A, and why
agentic-memory 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Directives — Memory Fabric
Hand-curated development guidelines shared by every AI agent working on this repo.
Source of truth: the role: steering section files in .ai-memory/. Edit those
files (review via MR), then run ai-memory sync-agents — never edit this
generated copy in place.
Framework Rules Map
This section provides the high-level system requirements and CLI usage overview for the memory-fabric package.
1. System Requirements
- Python Version:
Python >= 3.11 - Core Dependencies:
mcp >= 1.0.0(optional; required only if running as an MCP server).ripgrep(rg): optional but highly recommended to speed up searches.
2. Installation Conventions
# CLI only
pip install "git+https://github.com/elViRafa/agentic-memory.git"
# CLI + MCP Server
pip install "memory-fabric[mcp] @ git+https://github.com/elViRafa/agentic-memory.git"
3. Command Line Interface (CLI)
The package installs a global executable ai-memory:
ai-memory [--cwd <path>] [--json] <command>
Supported Commands Overview:
init,status,doctor,eval,dream,query,sync-global,rollback.
(For detailed schemas returned by these CLI commands, see the CLI Contracts Map)
4. Testing Conventions
- Use standard
pytestfor all unit and integration testing. Runpytest tests/from the root directory.
Granular Rules
Specific rule sets and agent instructions are stored in the granular memory store:
MCP Agent Instructions
Strict rules on how AI Agents should interact with the .ai-memory/ directory using MCP tools rather than standard OS filesystem tools.
👉 View Agent Instructions
Ubiquitous Language
A shared glossary of domain terms utilized in the development, testing, and operation of Memory Fabric.
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 · 125 lines · 1,128 tokens per session scan A 6f2684f1871f
agentic-memory CLAUDE.md is an instructions file published in the GitHub repository elViRafa/agentic-memory (1 stars, last pushed 20d ago), licensed MIT. It adds 1,128 tokens to every session, about $0.0045 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
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).
generative-ai-for-beginners AGENTS.md
AGENTS.md instructions for microsoft/generative-ai-for-beginners, covering agents.md, project overview, setup commands, initial repository setup and clone the repository.