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Agent Carnet

CommunityPopular
yamadashy
agent-carnet

Use this skill when the user asks to save, recall, find, or organize notes. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check the notebook', 'find in carnet'. Also use proactively when discovering findings worth preserving across sessions.

Overview

Publisheryamadashy
Repositoryrepomix
Skill nameagent-carnet
Stars
28.8K
Forks
1.6K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yamadashy on GitHub. Read the source before you install it.

Installation

Install the Agent Carnet AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yamadashy/repomix/tree/main/.agents/skills/agent-carnet
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yamadashy/repomix.git /tmp/repomix
mkdir -p .claude/skills
cp -r /tmp/repomix/.agents/skills/agent-carnet .claude/skills/agent-carnet
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Carnet in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Carnet on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Carnet is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent Carnet

A tiny CLI that gives you a shared markdown notebook on disk under .carnet/<category>/<slug>.md. Notes have a 30-day default lifespan that resets every time they are read or applied; useful ones survive, stale ones drift to .trash/ automatically.

Quick reference

bash
# Save (always pass --summary and --agent claude-code)
echo "body content" | agent-carnet save deps/iconv-issue \
  --summary "iconv-esm v0.7 types broken — pin to v0.6" \
  --agent claude-code \
  --tags compat,esm

# Recall
agent-carnet find iconv               # search summaries (does NOT bump lifespan)
agent-carnet list                     # category-grouped overview, sorted by last_used
agent-carnet list --sort use_count    # most-applied notes first
agent-carnet show deps/iconv-issue    # read full content (bumps last_used; weak use signal)

# Mark as actually applied (strong use signal — bumps last_used + use_count)
agent-carnet used deps/iconv-issue

# Maintain
agent-carnet move <from> <to>
agent-carnet rm <path> --yes

When unsure of a subcommand's full flag set, run agent-carnet <command> -h (e.g. agent-carnet save -h, agent-carnet used -h). Each subcommand prints its own focused help — required arguments, options, and examples — without invoking filesystem operations.

When to save

Save proactively when you discover something worth preserving across sessions:

  • Research findings that took effort to derive
  • Non-obvious patterns / gotchas in the codebase
  • Solutions to tricky problems
  • Architectural decisions and the reasoning behind them
  • In-progress work that may be resumed later

When to recall

Before starting related work or when context might exist:

  • agent-carnet find <topic> — quick scan of summaries
  • agent-carnet list <category> — browse a folder
  • agent-carnet show <path> — actually read (resets last_used; only use when the content matters)

When to call used

Call agent-carnet used <path> after a carnet actually shaped your work:

  • You applied the recorded fix and it solved the bug.
  • You consulted the carnet before retrying a hypothesis and skipped a dead-end.
  • You used the canonical name from a vocab carnet in new code instead of inventing your own.

used increments use_count — a durable importance signal that survives across sessions and lets future readers (and agent-carnet list --sort use_count) surface load-bearing notes.

Reading a carnet does NOT count. show already keeps it alive (weak signal); used records that the note was worth keeping for a real reason (strong signal).

Hard rules

  • --summary is required. Make it decisive — reading the summary in isolation tells the next reader (or the next agent) whether to read further.
  • --agent claude-code is required.
  • find does NOT bump anything. show bumps last_used. used bumps last_used AND increments use_count.
  • updated tracks content modification only (save, save --update). It is independent of last_used and is not the lifespan driver.
  • The 30-day expiry is automatic — do not manually clean up. keep: true pins permanent notes.
  • Auto-prune runs on every CLI invocation; deleted carnets land in .carnet/.trash/ for 7 days before hard delete.

Path conventions

  • <category>/<slug> — kebab-case, no leading slash, no ...
  • Categories are folders; create new ones freely as needed.
  • Subcategories are allowed: deps/esm/iconv-issue works.

When to read references/

This SKILL.md is enough for everyday note-keeping. Open the references/ files only when one of these specific cases applies — they are not always-on context, so do not load them speculatively.

Read this fileWhen
references/cookbook.mdYou are about to use (or are being asked about) a tag-based pattern such as tags: [vocab] for project terminology or tags: [hypothesis] for debugging dead-ends. The file shows the full pattern, including how to structure the body and meta: for that pattern.
references/frontmatter.mdYou need to write or read the meta: extension namespace, set a non-trivial lifespan / keep, or understand why an unfamiliar frontmatter field is or is not preserved on save.

If neither case applies, do not read references/. The base of this file already covers daily save/find/show/touch/move/rm flows.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Agent Carnet AI skill do?

Use this skill when the user asks to save, recall, find, or organize notes. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check the notebook', 'find in carnet'. Also use proactively when discovering findings worth preserving across sessions.

Why use Agent Carnet on TypingMind?

Because you install it once and use it with any model. Agent Carnet is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Carnet in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yamadashy/repomix/tree/main/.agents/skills/agent-carnet. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Agent Carnet?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Carnet?

As many as you like. As long as a model supports skills, you can use Agent Carnet with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Carnet AI skill free?

Yes. It is published on GitHub by yamadashy under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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