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Recall

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ArtemXTech
recall

Load context from vault memory. Temporal queries (yesterday, last week, session history) use native JSONL timeline. Topic queries use QMD BM25 search. "recall graph" generates interactive temporal graph of sessions and files. Every recall ends with "One Thing" - the single highest-leverage next action synthesized from results. Use when user says "recall", "what did we work on", "load context about", "remember when we", "prime context", "yesterday", "what was I doing", "last week", "session history", "recall graph", "session graph".

Overview

PublisherArtemXTech
Repositorypersonal-os-skills
Skill namerecall
Stars
542
Forks
90
Bundled files
4
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • 4 bundled files

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

  • Open source

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

Installation

Install the Recall 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/ArtemXTech/personal-os-skills/tree/main/skills/recall
  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/ArtemXTech/personal-os-skills.git /tmp/personal-os-skills
mkdir -p .claude/skills
cp -r /tmp/personal-os-skills/skills/recall .claude/skills/recall
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Recall 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 Recall 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 Recall 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.

Recall Skill

Three modes: temporal (date-based session timeline), topic (BM25 search across QMD collections), and graph (interactive visualization of session-file relationships). Every recall ends with the One Thing - a concrete, highest-leverage next action synthesized from the results.

What It Does

  • Temporal queries ("yesterday", "last week", "what was I doing"): Scans native Claude Code JSONL files by date. Shows a table of sessions with time, message count, and first message. Expand any session for conversation details.
  • Topic queries ("QMD video", "authentication"): BM25 search across sessions, notes, and daily logs in QMD collections.
  • Graph queries ("graph yesterday", "graph last week"): Generates an interactive HTML graph showing sessions as nodes connected to files they touched. Sessions colored by day, files colored by folder. Clusters reveal related work streams, shared files show cross-session dependencies.
  • One Thing synthesis: After presenting results, synthesizes the single most impactful next action based on what has momentum, what's blocked, and what's closest to done. Not generic - specific and actionable.

No custom setup needed for temporal recall - every Claude Code user has JSONL files.

Auto-Indexing (Optional)

You can auto-index sessions into QMD on every session end via a Claude Code hook. See AGENTS.md for setup instructions.

Usage

/recall yesterday
/recall last week
/recall 2026-02-25
/recall QMD video
/recall authentication work

Graph mode - visualize session relationships over time:

/recall graph yesterday        # what you touched today
/recall graph last week        # week overview - find clusters
/recall graph this week        # current week so far
/recall graph last 3 days      # recent activity window

Graph options: --min-files 5 for cleaner graphs (only sessions touching 5+ files), --all-projects to scan beyond current vault.

Workflow

See workflows/recall.md for routing logic and step-by-step process.

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 Recall AI skill do?

Load context from vault memory. Temporal queries (yesterday, last week, session history) use native JSONL timeline. Topic queries use QMD BM25 search. "recall graph" generates interactive temporal graph of sessions and files. Every recall ends with "One Thing" - the single highest-leverage next action synthesized from results. Use when user says "recall", "what did we work on", "load context about", "remember when we", "prime context", "yesterday", "what was I doing", "last week", "session history", "recall graph", "session graph".

Why use Recall on TypingMind?

Because you install it once and use it with any model. Recall 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 Recall in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArtemXTech/personal-os-skills/tree/main/skills/recall. 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 Recall?

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 Recall?

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

Is the Recall AI skill free?

Yes. It is published on GitHub by ArtemXTech 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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