memroach CLAUDE.md

memroach CLAUDE.md is an instructions file for coding agents from biplav-crl/memroach. It costs 863 tokens per session, scanned A, original, MIT.

A set of instructions for Claude Code when working on MemRoach, a system that stores and synchronizes AI-agent memories using CockroachDB, a distributed database.

In plain words
What is it for?
Use it when developing or maintaining MemRoach’s Python scripts, memory search, file synchronization, background syncing, or database schema.
Why use it?
It gives the coding agent the repository’s structure, database layout, configuration details, and coding patterns so it can make changes with the right context.

Instructions file

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/biplav-crl/memroach/claude-md
Clone the repo
git clone --depth 1 https://github.com/biplav-crl/memroach

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.

agentmods badge for memroach CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/biplav-crl/memroach/claude-md.svg)](https://agentmods.dev/instructions/biplav-crl/memroach/claude-md)
Your own site
<a href="https://agentmods.dev/instructions/biplav-crl/memroach/claude-md"><img src="https://agentmods.dev/badge/instructions/biplav-crl/memroach/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 863 This file is loaded in full into every session.
When invoked 863 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 $0.00863 $0.00863
Opus 5 $0.00432 $0.00432
Sonnet 5 $0.00173 $0.00173
Haiku 4.5 $0.00086 $0.00086

Measured 4d ago against content hash d3aaacf3eda5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memroach 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 4d 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 · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MemRoach — Instructions for Claude Code

What is this repo?

MemRoach is a CockroachDB-backed memory sync system for AI agents. It has three main components:

  1. memroach_mcp_server.py — MCP server (primary interface, 16 tools)
  2. memroach_sync.py — File sync client + CLI + hook handler. Syncs ~/.claude/ to/from CockroachDB.
  3. memroach_daemon.py — Background sync daemon for real-time cross-machine updates.

Key patterns

  • Single-file Python scripts using FastMCP and pg8000
  • Direct CockroachDB connection (no Cloud Function intermediary)
  • Content-addressable blob storage with gzip compression
  • Hybrid search: vector embeddings (OpenAI text-embedding-3-small) + keyword matching
  • Per-memory visibility: private (default) or team
  • Optimistic concurrency via version column
  • Knowledge graph with typed links (relates_to, duplicates, supersedes, caused_by, refines)
  • Memory decay via access tracking

Database

All tables prefixed with memroach_. Schema in schema/memroach_schema.sql.

  • memroach_blobs — deduplicated content store
  • memroach_files — file metadata per user+machine
  • memroach_embeddings — vector embeddings for search
  • memroach_history — version changelog
  • memroach_links — knowledge graph edges
  • memroach_access — read tracking for decay scoring
  • memroach_log — audit trail

Config

memroach_config.json (gitignored) — DB credentials, embedding API key, sync preferences.

How Claude Should Use MemRoach

Memory saving: files first, MCP for extras

Default behavior — no change needed. Continue saving memories to ~/.claude/memory/ files as normal. The sync hooks automatically push these to CockroachDB on Stop/SessionEnd. This is the primary path.

Use MCP tools when you need something files can't do:

  • memroach_store — Write a memory directly to DB (useful from non-Claude-Code clients like Cursor)
  • memroach_share(path, "team") — Make a memory visible to teammates
  • memroach_link(from, to, type) — Create knowledge graph connections between related memories
  • memroach_merge(paths, content) — Consolidate duplicate memories into one

Read the full file on GitHub · 80 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. 4d ago First seen · 80 lines · 863 tokens per session scan A d3aaacf3eda5

Subscribe to this mod's changes

memroach CLAUDE.md is an instructions file published in the GitHub repository biplav-crl/memroach (1 stars, last pushed 5mo ago), licensed MIT. It adds 863 tokens to every session, about $0.0043 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.