reme-memory

reme-memory is a skill for Claude Code, Codex from agentscope-ai/ReMe. It costs 37 tokens per session (718 once invoked), scanned A, original, Apache-2.0.

A file-based memory system for recalling information from earlier conversations and stored resources.

In plain words
What is it for?
Use it to search long-term memory, browse related notes, inspect saved documents, and answer questions about previous work when its memory service is running.
Why use it?
It helps recover past decisions, preferences, project history, and other context without searching raw conversation files manually. It uses separate searches for durable knowledge, daily notes, and external materials.

Skill for Claude CodeCodex

Part of the reme plugin — 1 skill, 1 hook, 1 MCP server shipped together

About the project

ReMe is a local-first memory management system that turns conversations and other resources into searchable, editable Markdown knowledge shared across AI agents. It is for users and agent runtimes that need durable, interconnected knowledge they can inspect and maintain. The catalogue add-ons connect coding agents and other agents to ReMe through skills, hooks, plugins, MCP, and related interfaces.

agentscope-ai/ReMe · 3,383 stars · on GitHub

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 skills/agentscope-ai/reme/reme-memory
Any agent
npx skills add agentscope-ai/ReMe --skill reme-memory
Clone the repo
git clone --depth 1 https://github.com/agentscope-ai/ReMe

Made for: Claude Code, Codex.

Or install reme, the plugin that ships this one along with the rest of its 1 skill, 1 hook, 1 MCP server.

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 reme-memory

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentscope-ai/reme/reme-memory.svg)](https://agentmods.dev/skills/agentscope-ai/reme/reme-memory)
Your own site
<a href="https://agentmods.dev/skills/agentscope-ai/reme/reme-memory"><img src="https://agentmods.dev/badge/skills/agentscope-ai/reme/reme-memory.svg" alt="Measured on agentmods" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 718 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00037 $0.00718
Opus 5 $0.00018 $0.00359
Sonnet 5 $0.00007 $0.00144
Haiku 4.5 $0.00004 $0.00072

Measured 5d ago against content hash 2f41c3301090, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

reme-memory 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 5d 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.

integrations/claude_code/reme/skills/reme-memory/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ReMe Memory

ReMe is the persistent, file-native memory layer for this agent. It stores conversations and resources as Markdown files with frontmatter and [[wikilinks]], and consolidates them into long-term digest knowledge. Your job with this plugin is recall.

The recall tools come from the reme MCP server (surfaced as mcp__reme__…): search, traverse, daily_list, frontmatter_read, read. They are only available when the user has the server running:

reme start service.backend=http

If the tools are missing, that server is not running — tell the user the command above instead of guessing answers.

Recall (read long-term memory)

Before answering questions about previous conversations, user preferences, project history, decisions, or long-term context, recall from ReMe first. ReMe answers three independent kinds of question — pick the mode the request needs; don't merge them into one call. Durable knowledge lives under digest/, daily notes under daily/, external materials under resource/.

  1. Semantic (default — "what do we know about X?"): search with query="<question/keywords>", limit=5 (optional min_score). Hybrid vector + BM25 with one-hop wikilink expansion.
  2. Topological ("what links to this node?"): traverse with path="<node>", depth=1 (raise to 2 only when needed), direction=both to walk the [[wikilink]] graph.
  3. State ("what exists / what was recorded on ?"): daily_list with date="YYYY-MM-DD" (empty = today) to list a day's notes, or frontmatter_read with a path to inspect one file's frontmatter — structural lookup, no semantic matching.

Then read the relevant hits by path (optionally start_line/end_line; prefer digest/ paths for durable knowledge) to pull the content behind a hit. Cite the workspace-relative paths you used. If nothing useful comes back, say so plainly rather than guessing.

Server status

To check ReMe is up: call version and health_check, then summarize the version and the health snapshot (components, workspace). If the mcp__reme__… tools are not available at all, the server is not running — tell the user to start it with the command above. The plugin connects at http://127.0.0.1:2333/mcp; a different host/port must match the url in the bundled .mcp.json.

Read the full file on GitHub · 59 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. 5d ago First seen · 59 lines · 37 tokens per session scan A 2f41c3301090

Subscribe to this mod's changes

reme-memory is a skill published in the GitHub repository agentscope-ai/ReMe (3,383 stars, last pushed 3d ago), licensed Apache-2.0. It adds 37 tokens to every session and 718 once invoked, about $0.0002 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.

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