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Agent skill

Reme Memory

by agentscope-ai in agentscope-ai/ReMe

Use ReMe as file-native long-term memory in Claude Code. An agent skill from agentscope-ai/ReMe.

Apache-2.0Auto-check passedAgent Workflows

Install Reme Memory

skills CLI
$ npx skills add agentscope-ai/ReMe --skill reme-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agentscope-ai/ReMe reme-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agentscope-ai/ReMe.git skills-src && mkdir -p .claude/skills && cp -r skills-src/integrations/claude_code/reme/skills/reme-memory .claude/skills/reme-memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
reme-memory
GitHub stars
3.6k
Token cost
~740 tokens
SKILL.md length
346 words
Files
1
Skills in repo
3
Repo updated
First seen
Licence
Apache-2.0

At a glance

Use ReMe as file-native long-term memory in Claude Code. An agent skill from agentscope-ai/ReMe.

  • Works in 3 steps: Semantic (default — "what do we know… → Topological ("what links to this… → State ("what exists / what was recorded…
  • Tasks that involve Agent memory
  • SKILL.md covers Recall (read long-term memory), Server status and Workspace model
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Reme Memory is an agent skill from agentscope-ai/ReMe. Use ReMe as file-native long-term memory in Claude Code. RECALL — search ReMe before answering questions about past conversations, preferences, project history, or decisions.

Its SKILL.md is about 740 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Agent memory. It works with Model Context Protocol. The repository describes itself as: ReMe: Memory Management Kit for Agents - Remember Me, Refine Me. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Agent memory

Example prompts

  • “/reme-memory”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Semantic (default — "what do we know about X?"): search with query="",
  2. Topological ("what links to this node?"): traverse with path="", depth=1
  3. State ("what exists / what was recorded on ?"): daily_list with date="YYYY-MM-DD"

What it can do on your machine

Read from SKILL.md and the folder at commit 084c02e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Reme Memory loads about 740 tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 346 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~740

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from agentscope-ai/ReMe at commit 084c02e, republished under its Apache-2.0 licence (© agentscope-ai). 346 words, ~740 tokens.

Download SKILL.mdSave it as .claude/skills/reme-memory/SKILL.md (or your agent's skills folder).
name
reme-memory
description
Use ReMe as file-native long-term memory in Claude Code. RECALL — search ReMe before answering questions about past conversations, preferences, project history, or decisions.

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 <date>?"): 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.

Workspace model

daily/    lightly-processed memory: daily facts, conversation summaries
digest/   long-term consolidated knowledge (what recall mainly surfaces)
resource/ external raw materials

Consolidation of daily/ into digest/ and proactive interest extraction run server-side in the ReMe process (background watchers + dream cron). The plugin does not drive them.

© agentscope-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in integrations/claude_code/reme/skills/reme-memory of agentscope-ai/ReMe.

Open the folder on GitHubat commit 084c02e

Compare with similar skills

Reme Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Reme Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Reme Memory this skillagentscope-ai/ReMe3.6k—~740Automated safety check: PassApache-2.0
MemPalace Memory SearchMemPalace/mempalace59k—~1.4kAutomated safety check: PassMIT
MemPalace Setup and OperationMemPalace/mempalace59k—~2.2kAutomated safety check: PassMIT
agentmemory Setup and Diagnosticsrohitg00/agentmemory29k—~1kAutomated safety check: NotesApache-2.0
Claude-Mem Install for Grok Botthedotmack/claude-mem99k—~440Automated safety check: PassApache-2.0
Qmdbreferrari/obsidian-mind5k—~1.7kAutomated safety check: PassMIT

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Works with

Categories

Questions about Reme Memory

What does Reme Memory do?

Use ReMe as file-native long-term memory in Claude Code. An agent skill from agentscope-ai/ReMe. Reme Memory is an agent skill from agentscope-ai/ReMe. Use ReMe as file-native long-term memory in Claude Code.

When should I use Reme Memory?

Reme Memory fits situations like: tasks that involve Agent memory.

How do I install Reme Memory in Claude Code?

Run `npx skills add agentscope-ai/ReMe --skill reme-memory -a claude-code`. Or copy the skill folder (integrations/claude_code/reme/skills/reme-memory in agentscope-ai/ReMe) into .claude/skills/reme-memory in your project. Claude Code loads it when a task matches its description.

How do I install Reme Memory in Codex?

Run `npx skills add agentscope-ai/ReMe --skill reme-memory -a codex`. Or copy the skill folder (integrations/claude_code/reme/skills/reme-memory in agentscope-ai/ReMe) into .agents/skills/reme-memory in your project. Codex loads it when a task matches its description.

Can I use Reme Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agentscope-ai/ReMe --skill reme-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reme-memory, .gemini/skills/reme-memory, .github/skills/reme-memory and .opencode/skills/reme-memory in your project.

What does Reme Memory need to run?

SKILL.md names no scripts, command-line tools or credentials: Reme Memory is instructions for the agent only.

Does Reme Memory access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Reme Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Reme Memory use?

Reme Memory is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Reme Memory use?

About 740 tokens (SKILL.md is roughly 3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Reme Memory?

Skills that share tags, products or a category with Reme Memory: MemPalace Memory Search (MemPalace/mempalace, 59k stars), MemPalace Setup and Operation (MemPalace/mempalace, 59k stars), agentmemory Setup and Diagnostics (rohitg00/agentmemory, 29k stars) and Claude-Mem Install for Grok Bot (thedotmack/claude-mem, 99k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Reme Memory?

agentscope-ai (a GitHub organization) maintains it in agentscope-ai/ReMe, which has 3,565 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on October 6, 2026.

Source: agentscope-ai/ReMe on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.