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Session Search

Organization
techwolf-ai
session-search

Find context from past Claude Code (CLI) and Claude Cowork (desktop) sessions on this Mac. Use when the user wants to recall something they did before but can't find it , phrasings like "where did I work on X", "find that session where I…", "when did I last do Y", "pull up the conversation about Z", "that time I built/tried/discussed …". Searches by kind (code/cowork), time range, title, working directory, or free-text content across all transcripts.

Overview

Publishertechwolf-ai
Repositoryai-first-toolkit
Skill namesession-search
Stars
138
Forks
7
Bundled files
4
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.

  • 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 techwolf-ai on GitHub. Read the source before you install it.

Installation

Install the Session Search 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/techwolf-ai/ai-first-toolkit/tree/main/plugins/session-tools/skills/session-search
  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/techwolf-ai/ai-first-toolkit.git /tmp/ai-first-toolkit
mkdir -p .claude/skills
cp -r /tmp/ai-first-toolkit/plugins/session-tools/skills/session-search .claude/skills/session-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Session Search 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 Session Search 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 Session Search 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.

session-search

Platforms: Claude Code / Cowork and Codex. find_sessions.py and show_session.py detect the host (via the platform stamp install.sh writes, or AI_FIRST_PLATFORM) and route to the right store: Claude Code (~/.claude/projects) + Cowork transcripts, or Codex rollouts (~/.codex/sessions/**/rollout-*.jsonl). Both support list, time/cwd/title filters, and full-text --grep. Antigravity is not supported: its IDE conversations are AEAD-encrypted at rest (~/.gemini/antigravity/conversations/*.pb) and its unencrypted CLI store carries no parseable turn content, so the skill prints a clear "not available" message and exits.

Two scripts in scripts/ locate past sessions and dump their content:

  • find_sessions.py , discover + filter sessions (metadata + optional full-text grep).
  • show_session.py , print a single session's conversation (user/assistant turns) in readable form.

Both read directly from disk , no API calls, no auth. They resolve paths from $HOME so they work for any macOS user:

  • Claude Code CLI: ~/.claude/projects/*/\*.jsonl
  • Claude Cowork: ~/Library/Application Support/Claude/local-agent-mode-sessions/*/*/local_*/audit.jsonl (sibling local_*.json holds title/metadata)

How to use

Start narrow, widen if needed. Prefer --grep for content recall; use metadata filters to scope.

Step 1 , find candidate sessions

bash
scripts/find_sessions.py --grep "recruitee logo api"      # content search
scripts/find_sessions.py --title "rippling"              # title substring
scripts/find_sessions.py --cwd "Recruitee"               # Code sessions under matching cwd
scripts/find_sessions.py --since 2026-03-01 --until 2026-03-31
scripts/find_sessions.py --kind cowork -n 30             # 30 most recent Cowork

Combine freely. Output is a table by default; add --json for structured piping.

--grep PATTERN is a regex (case-insensitive). It searches message text inside every transcript and prints 1-2 matching snippets per session along with the session row. Use this when the user remembers a phrase or topic, not a title.

Step 2 , pull full context from a specific session

bash
scripts/show_session.py <path-from-step-1>       # full conversation
scripts/show_session.py <path> --grep "logo"     # only turns mentioning "logo" (with ±1 surrounding turn)
scripts/show_session.py <path> --tail 20         # last 20 turns

The script strips tool calls/results and renders user + assistant text only. Output is markdown-ish; pipe to a pager if long.

Filter reference

find_sessions.py flags:

  • --kind {code,cowork,all} , default all
  • --since YYYY-MM-DD, --until YYYY-MM-DD , by last-activity mtime
  • --title TEXT , substring, case-insensitive (Cowork uses the stored title; Code uses the first user message)
  • --cwd TEXT , substring match against the working directory recorded in Code transcripts
  • --grep PATTERN , regex across transcript body
  • -n, --limit N , cap results (default 50, 0 = all)
  • --snippets N , how many matching lines to show per session under --grep (default 2)
  • --json , machine-readable output

Tips

  • If the user's description is vague, run --grep with 2–3 alternative phrasings in parallel before narrowing.
  • For Code sessions the "title" is a best-effort extraction of the first user message; for Cowork it comes from the .json sidecar written by the desktop app.
  • A session can have many transcripts (resumes, forks). find_sessions.py lists each transcript separately; that's usually what you want , the most recent one is the live thread.
  • Transcripts can be large (several MB). When dumping content to the user, prefer show_session.py --grep or --tail over the full file.

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 Session Search AI skill do?

Find context from past Claude Code (CLI) and Claude Cowork (desktop) sessions on this Mac. Use when the user wants to recall something they did before but can't find it , phrasings like "where did I work on X", "find that session where I…", "when did I last do Y", "pull up the conversation about Z", "that time I built/tried/discussed …". Searches by kind (code/cowork), time range, title, working directory, or free-text content across all transcripts.

Why use Session Search on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/session-tools/skills/session-search. 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 Session Search?

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 Session Search?

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

Is the Session Search AI skill free?

Yes. It is published on GitHub by techwolf-ai 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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