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Session Save

CommunityPopular
FlorianBruniaux
session-save

Save the current session state (decisions, modified files, current status, and next steps) to a handoff file for later resume.

Overview

PublisherFlorianBruniaux
Repositoryclaude-code-ultimate-guide
Skill namesession-save
Stars
6.1K
Forks
807
Bundled files
Instructions only
LicenseCC-BY-SA-4.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Session Save 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/FlorianBruniaux/claude-code-ultimate-guide/tree/main/examples/skills/session-save
  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/FlorianBruniaux/claude-code-ultimate-guide.git /tmp/claude-code-ultimate-guide
mkdir -p .claude/skills
cp -r /tmp/claude-code-ultimate-guide/examples/skills/session-save .claude/skills/session-save
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Session Save 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 Save 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 Save 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-save

Capture the current session into a structured handoff file so you (or another instance) can resume with full context. Creates a timestamped Markdown file in .claude/sessions/.

When to use

  • Before ending a session that isn't complete
  • Before switching to a different task
  • Before context reaches 75%+ (to preserve the important parts)
  • At natural milestones in a long task (after each phase)
  • To hand off to a second Claude instance

Instructions

Produce a handoff document with the following structure:


Session handoff: [TIMESTAMP]

What was being done

[One paragraph: the goal, the approach, where things stand right now]

Files modified this session

[List every file that was created, edited, or deleted, with the nature of the change]

path/to/file.ts      - [what changed and why]
path/to/other.ts     - [what changed and why]

Key decisions made

[Architectural choices, tradeoffs accepted, approaches rejected and why]

  • Decision: [What was decided]
    • Rationale: [Why]
    • Alternatives rejected: [What else was considered]

Current status

[Where things are right now: what's working, what's broken, what's in-progress]

  • Working: [...]
  • In-progress: [...]
  • Known issues: [...]

Next steps (ordered)

[The exact next actions to take to continue, specific enough that a fresh context can pick up without re-reading everything]

  1. [First action]: path/to/file.ts - [what to do]
  2. [...]

Context to reload

[Files that must be read to resume with full understanding, keep this list short]

  • path/to/key-file.ts: [why it matters]
  • CLAUDE.md: project rules

Blockers / open questions

[Anything unresolved that needs a decision or external input before proceeding]

  • [Question or blocker]: [who/what can resolve it]

Implementation

Save the handoff to .claude/sessions/handoff-[YYYY-MM-DD-HHMM].md. Then output the file path so the user knows where to find it.

Resume pattern

To resume from a handoff:

/session-resume .claude/sessions/handoff-YYYY-MM-DD-HHMM.md

Or manually: read the handoff file, then read the files listed in "Context to Reload" before continuing.

Examples

Example 1: Mid-Feature save

/session-save

Claude captures:

  • Auth middleware was being refactored (files: src/middleware/auth.ts, src/middleware/jwt.ts)
  • Decision: switched from session tokens to JWTs (rationale: scales better across services)
  • Status: JWT validation working, refresh logic in-progress
  • Next: implement refreshToken() in src/services/auth.service.ts, then update tests

Example 2: Context-Pressure save

When context hits 70%, run /session-save before /compact to preserve decision context that compaction might lose.

Notes

  • Keep "Context to Reload" to 5 files max. The goal is a fast resume, not a full re-read.
  • "Next Steps" should be specific enough that a cold-start Claude can execute step 1 without asking questions
  • Don't save tool output or code snippets in the handoff; reference file paths instead.

See also:

Frequently asked questions

What does the Session Save AI skill do?

Save the current session state (decisions, modified files, current status, and next steps) to a handoff file for later resume.

Why use Session Save on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/FlorianBruniaux/claude-code-ultimate-guide/tree/main/examples/skills/session-save. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Session Save?

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 Save?

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

Is the Session Save AI skill free?

Yes. It is published on GitHub by FlorianBruniaux under the CC-BY-SA-4.0 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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