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Agent skill

Nano Memory

by agentscope-ai in agentscope-ai/skills

Guidelines and workflows for the agent to maintain persistent memory using native file tools (readfile, writefile, editfile) and standard OS commands for searching.

Apache-2.0Auto-check passedAgent Workflows

Install Nano Memory

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

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

GitHub CLI
$ gh skill install agentscope-ai/skills nano-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/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nano-memory .claude/skills/nano-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
nano-memory
GitHub stars
130
Token cost
~1.2k tokens
SKILL.md length
628 words
Files
1
Skills in repo
4
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guidelines and workflows for the agent to maintain persistent memory using native file tools (readfile, writefile, editfile) and standard OS commands for searching.

  • Works in 4 steps: 🔍 Search (OS-Specific Commands) → 📖 Read (Native read_file) → ✍️ Write (Native write_file) → …
  • Tasks that involve Agent memory
  • SKILL.md covers 🧠 Memory Architecture, 🛠️ Core Memory Operations, 🎯 Proactive Recording - No… and 🔄 Memory Workflows (SOP), plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Nano Memory is an agent skill from agentscope-ai/skills. Guidelines and workflows for the agent to maintain persistent memory using native file tools (readfile, writefile, editfile) and standard OS commands for searching.

Its SKILL.md is about 1.2k 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 PowerShell. The repository describes itself as: A curated collection of skills around AgentScope ecosystem and CoPaw applications. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Agent memory

Example prompts

  • “Use the nano-memory skill to guideline and workflows for the agent to maintain persistent memory using native file tools (readfile, writefile…”
  • “/nano-memory”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 🔍 Search (OS-Specific Commands)
  2. 📖 Read (Native read_file)
  3. ✍️ Write (Native write_file)
  4. 📝 Edit (Native edit_file)

What it can do on your machine

Read from SKILL.md and the folder at commit b533664. 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

Nano Memory loads about 1.2k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 628 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~45
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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/skills at commit b533664, republished under its Apache-2.0 licence (© agentscope-ai). 628 words, ~1,210 tokens.

Download SKILL.mdSave it as .claude/skills/nano-memory/SKILL.md (or your agent's skills folder).
name
nano-memory
description
Guidelines and workflows for the agent to maintain persistent memory using native file tools (read_file, write_file, edit_file) and standard OS commands for searching.
version
1.0.0

🧠 Memory Architecture

Each session is stateless. Your memory lives entirely within the local file system. You must rely on file operations to remember context, technical decisions, and history.

Core Memory Files
  • memory/YYYY-MM-DD.md (Daily Logs): Raw, chronological logs of what happened. Use this for daily tasks, scratchpad thinking, and immediate context.
  • MEMORY.md (Long-Term Memory): Your curated, distilled knowledge base. Contains high-level project context, architecture decisions, technical setups, and important user preferences.

🛠️ Core Memory Operations

You have access to native file tools and standard OS commands. Use them strictly in these patterns to avoid data loss or hallucinations:

1. 🔍 Search (OS-Specific Commands)
  • When to use: ALWAYS use this before answering questions about past work, decisions, or dates to find where information is stored.
  • Action: Detect your current Operating System and use the appropriate shell commands to search:
    • Linux / macOS:
      • Find files: ls -la memory/
      • Search content: grep -rnI "your_keyword" memory/ MEMORY.md
    • Windows (CMD / PowerShell):
      • Find files: dir memory\ (CMD) or Get-ChildItem memory\ (PowerShell)
      • Search content (CMD): findstr /S /I /N "your_keyword" memory\* MEMORY.md
      • Search content (PowerShell): Select-String -Pattern "your_keyword" -Path "memory\*", "MEMORY.md"
2. 📖 Read (Native read_file)
  • When to use: After a successful search to get full context, OR crucially, before using the edit_file tool.
  • Action: Use your native read_file tool to load the exact state of a file. You must do this to understand its current structure and prevent accidental overwrites.
3. ✍️ Write (Native write_file)
  • When to use: When creating new daily logs or saving entirely new files.
  • Action: Use your native write_file tool to save content. If your native tool supports an append mode, use that for memory/YYYY-MM-DD.md. Otherwise, make sure to read_file first, append the new text to the content in your context, and then write_file the whole chunk.
4. 📝 Edit (Native edit_file)
  • When to use: When updating specific sections of MEMORY.md.
  • CRITICAL RULE: NEVER guess the content. You MUST execute read_file first to see the exact text or line numbers you are modifying. Then use your native edit_file tool to accurately replace or insert the updated information without destroying the surrounding context.
Show full SKILL.md (285 more words)Show less

🎯 Proactive Recording - No "Mental Notes"!

  • Memory is limited: "Mental notes" do not survive session restarts. If it is not written to a file, it does not exist.
  • Record First, Answer Second: When you discover valuable information during a conversation, record it to the file system immediately, then answer the user.
  • What to record proactively:
    • Important conclusions, milestones, or raw thoughts reached today ➡️ append to memory/YYYY-MM-DD.md.
    • Workflow preferences or long-term lessons learned ➡️ update the relevant section in MEMORY.md using edit_file.
  • Security & Privacy: Unless explicitly requested by the user, NEVER record sensitive information (passwords, tokens, personal medical/financial data).

🔄 Memory Workflows (SOP)

Workflow A: Retrieving Memory
  1. Trigger: User asks about past context.
  2. Search: Run the appropriate search command for your OS (e.g., grep or findstr) to locate the keyword in memory/ or MEMORY.md.
  3. Read: Run the native read_file tool on the specific file found in step 2.
  4. Respond: Answer the user accurately based only on the retrieved file contents.
Workflow B: Updating Long-Term Knowledge
  1. Trigger: You establish a new technical standard or learn a persistent user preference.
  2. Read: Run the native read_file tool on MEMORY.md to review its current structure and locate the target section.
  3. Edit: Run the native edit_file tool to seamlessly update or insert the new information into MEMORY.md.
  4. Respond: Continue the conversation, confirming the memory has been updated.

🧹 Memory Maintenance (During Heartbeats / Idle)

Periodically act like a human reviewing their journal:

  1. Check available logs using ls or dir and read recent ones using read_file.
  2. Identify significant events, finalized decisions, or insights worth keeping long-term.
  3. Update MEMORY.md with these distilled learnings using edit_file.
  4. (Optional) Clear outdated info from MEMORY.md to keep your context clean.

© 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 skills/nano-memory of agentscope-ai/skills.

Open the folder on GitHubat commit b533664

Compare with similar skills

Nano 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.

Nano Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Nano Memory this skillagentscope-ai/skills130—~1.2kAutomated safety check: PassApache-2.0
Project KnowledgeJanDeDobbeleer/oh-my-posh24k—~748Automated safety check: PassMIT
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Reflect on Session Learningscursor/plugins10k5 repos~1.2kAutomated safety check: PassNone
MemPalace Memory SearchMemPalace/mempalace59k—~1.4kAutomated safety check: PassMIT

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  • Project Knowledge

    JanDeDobbeleer/oh-my-posh

    Accumulated project memory: verified gotchas and prior findings for oh-my-posh work.

    24k GitHub stars~748 tokensUpdated today
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  • Neat-Freak Knowledge Closeout

    KKKKhazix/khazix-skills

    Brings project docs, agent rule files, authorized memory and leftover workspace files back in line with what the code and runtime actually do at the end of a work session.

    21k GitHub stars~1.9k tokensUpdated 7 days ago
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  • Beads Task Memory

    gastownhall/beads

    Tracks multi-session work with dependencies in the bd issue tracker so the agent can find ready tasks and recover its context after conversation compaction.

    28k GitHub stars~1.2k tokensUpdated today
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  • Reflect on Session Learnings

    cursor/plugins

    Official

    Starts three parallel reviewer subagents over the current conversation transcript, then turns their findings into concrete edits to existing skills.

    10k GitHub starsUsed in 5 repos~1.2k tokens
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  • MemPalace Memory Search

    MemPalace/mempalace

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    59k GitHub stars~1.4k tokensUpdated yesterday
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  • Compound Learning Writer

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Works with

Categories

Questions about Nano Memory

What does Nano Memory do?

Guidelines and workflows for the agent to maintain persistent memory using native file tools (readfile, writefile, editfile) and standard OS commands for searching. Nano Memory is an agent skill from agentscope-ai/skills. Guidelines and workflows for the agent to maintain persistent memory using native file tools (readfile, writefile, editfile) and standard OS commands for searching.

When should I use Nano Memory?

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

How do I install Nano Memory in Claude Code?

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

How do I install Nano Memory in Codex?

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

Can I use Nano 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/skills --skill nano-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/nano-memory, .gemini/skills/nano-memory, .github/skills/nano-memory and .opencode/skills/nano-memory in your project.

What does Nano Memory need to run?

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

Does Nano 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 Nano 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 Nano Memory use?

Nano 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 Nano Memory use?

About 1.2k tokens (SKILL.md is roughly 4.8k 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 Nano Memory?

Skills that share tags, products or a category with Nano Memory: Project Knowledge (JanDeDobbeleer/oh-my-posh, 24k stars), Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars), Beads Task Memory (gastownhall/beads, 28k stars) and Reflect on Session Learnings (cursor/plugins, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Nano Memory?

agentscope-ai (a GitHub organization) maintains it in agentscope-ai/skills, which has 130 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on September 10, 2026.

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