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Session Done

Community
vincentkoc
session-done

Prepare a concise session handoff when the user asks to wrap up, capture continuation context, or use /done. Retain a Markdown file only when requested.

Overview

Publishervincentkoc
Repositorydotskills
Skill namesession-done
Stars
112
Forks
9
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Session Done 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/vincentkoc/dotskills/tree/main/skills/session-done
  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/vincentkoc/dotskills.git /tmp/dotskills
mkdir -p .claude/skills
cp -r /tmp/dotskills/skills/session-done .claude/skills/session-done
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Session Done 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 Done 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 Done 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 Done

Purpose

Capture the outcome, evidence, unresolved work, and next action without making session completion a cleanup or memory-write command.

When to use

  • The user asks for a session handoff, continuation summary, or /done.
  • The user requests a durable Markdown handoff, including a note in a PKM/Obsidian folder.

Workflow

  1. Use the current task's evidence. Record completed work, validation and its limits, blockers, and the next owner/action. Do not scan unrelated sessions or copy credentials, private logs, or raw transcripts.
  2. Include known session, branch, commit/PR, and retained-checkout identities when relevant. Mark unknown facts as unknown. Completion does not terminate sessions, remove worktrees, release owners, or rerun cleanup.
  3. Return the handoff in chat by default. For deterministic Markdown, run python3 scripts/session-done --summary "..." --state "..." --follow-ups "..."; it writes only stdout.
  4. If the user explicitly requested retention, use one named destination with --output <new-path>. The parent must already exist; existing files and symlinks are refused. A PKM/Obsidian folder can be that destination, without a second copy or sync service.
  5. Report the created path or exact failure. A failed write is not saved evidence. Preserve existing notes and recovery material; do not retry under new filenames automatically.
  6. Update memory only when the user directly requests it, through the environment's existing memory workflow. This writer never appends to shared memory or edits agent-managed memory files. Report that separate action's outcome.

Inputs

  • At least one content flag: --summary, --decisions, --questions, --follow-ups, --state, --reflection, or --flashcards.
  • Optional --session-id and --branch: verified values; both default to unknown.
  • Optional --output: the explicitly requested new Markdown file. No environment variable enables retention, copying, or memory writes.

Outputs

  • Structured Markdown on stdout by default, containing only supplied sections plus metadata.
  • With --output, one UTF-8 file published from complete staged bytes without overwriting another note; success is reported on stderr. Temporary staging is confined to the destination directory and removed when the command exits normally or handles a write failure.
  • Atomic publication applies to that one file, not a multi-file transaction or power-loss durability guarantee. An interrupted process can leave its staging file; preserve unknown files instead of sweeping the directory.

Flow

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 Done AI skill do?

Prepare a concise session handoff when the user asks to wrap up, capture continuation context, or use /done. Retain a Markdown file only when requested.

Why use Session Done on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vincentkoc/dotskills/tree/main/skills/session-done. 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 Done?

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 Done?

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

Is the Session Done AI skill free?

Yes. It is published on GitHub by vincentkoc 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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