Generate Handover logo

Generate Handover

Organization
DasDigitaleMomentum
generate-handover

Generate a session handover document that captures progress, decisions, and context for seamless session continuity. This documentation shall serve Agents and Humans when working in consecutive sessions with the project. Use this skill at the end of a work session or when context transfer to a new session is needed.

Overview

PublisherDasDigitaleMomentum
Repositoryopencode-processing-skills
Skill namegenerate-handover
Stars
61
Forks
3
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Generate Handover 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/DasDigitaleMomentum/opencode-processing-skills/tree/main/skills/generate-handover
  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/DasDigitaleMomentum/opencode-processing-skills.git /tmp/opencode-processing-skills
mkdir -p .claude/skills
cp -r /tmp/opencode-processing-skills/skills/generate-handover .claude/skills/generate-handover
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Generate Handover 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 Generate Handover 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 Generate Handover 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.

Skill: Generate Handover

What This Skill Does

This documentation shall serve Agents and Humans when working in consecutive sessions with the project. Creates a session handover document (plans/<name>/handovers/session-<date>.md) that captures everything a new session needs to continue work seamlessly:

  • What was accomplished in this session
  • What is in progress (interrupted work)
  • Key decisions made and their rationale
  • Current state of modified files
  • Blockers and issues discovered
  • Concrete next steps
  • Context that would be lost without the handover

When to Use

  • When the user asks to "create a handover" or "save session state"
  • When ending a work session on a multi-phase plan
  • When work is interrupted and will be continued later
  • When switching between team members or agents

Do NOT generate handovers automatically. This skill is invoked manually by the user.

Execution Model (Recommended)

  • Preferred: the primary agent runs this skill and writes the handover under plans/<name>/handovers/.
  • Rationale: a handover is a distilled session narrative (decisions, rationale, state). It should be authored where the session context lives.
  • Optional: delegate git status/git diff --stat interpretation or bulk file listing to doc-explorer, but keep narrative/decisions in the primary.

Workflow

Step 1: Identify the Context

Determine what to capture:

  • Which plan is being worked on? Check plans/ directory
  • What phase is active? Read plan.md and todo.md
  • If no formal plan exists, create a standalone handover (see below)

Step 2: Gather Session Information

Collect from the current session context:

Progress:

  • What tasks were completed? (from todo list changes, commits, conversation)
  • What is currently in progress? (incomplete work, partial implementations)
  • What was planned but not started? (remaining todo items)

Decisions:

  • What technical decisions were made? (architecture, library choices, approach)
  • What alternatives were considered? (and why they were rejected)
  • What trade-offs were accepted?

Implementation State:

  • Which files were modified? Use git diff --stat or git status
  • Are there uncommitted changes?
  • What tests are pending?

Issues:

  • Are there blockers? (dependencies, unclear requirements, technical issues)
  • Were workarounds applied that need revisiting?

Step 3: Write the Handover Document

Create plans/<name>/handovers/session-<YYYY-MM-DD>.md:

If multiple handovers on the same day, append a counter: session-2025-02-14-2.md.

Fill in all sections from the template:

  1. Session Summary: 2-3 sentences describing what this session was about
  2. Progress: Organized by completed / in-progress / not-started
  3. Key Decisions: Table with decision, alternatives considered, and rationale
  4. Current State: Modified files with what changed, pending tests
  5. Blockers & Issues: What prevents progress, with potential solutions if known
  6. Next Steps: Ordered list of what the next session should do first
  7. Context for Next Session: Free-form section for anything that would be lost - partial reasoning, important constraints discovered, "watch out for" notes

Step 4: Update the Todo List

After creating the handover:

  • Ensure todo.md reflects the actual current state
  • Mark completed items
  • Add any newly discovered items
  • Note blockers

Step 5: Confirm with User

Use the question tool to ask:

  • Is anything missing from the handover?
  • Are the next steps correctly prioritized?

Standalone Handovers (No Plan)

If there is no formal plan but a handover is needed:

  • Create docs/handovers/session-<date>.md (in the docs directory instead of plans)
  • Omit plan/phase references from the frontmatter
  • Focus on the general session context, decisions, and next steps

Rules

  1. Accuracy over completeness: Only document what actually happened. Don't invent or assume progress.
  2. Concrete next steps: "Continue working on auth" is useless. "Implement the JWT refresh token rotation in src/auth/refresh.ts, starting from the rotateToken function stub" is actionable.
  3. Decision rationale matters: Capture why decisions were made, not just what was decided. The next session needs the reasoning to avoid re-evaluating the same options.
  4. File-based interface: The handover document is the interface. All context goes into the file, not into chat messages.
  5. Don't duplicate the todo list: Reference todo.md for task status. The handover captures session context (decisions, state, blockers), not a repeat of the task list.
  6. Use git for file state: Use git status and git diff --stat to identify modified files rather than relying on memory.
  7. Multiple handovers are normal: Each session can produce its own handover. They are additive, not replacements.
  8. Keep it scannable: The next session's agent will read this to bootstrap context. Use clear headings, short bullet points, and tables where appropriate.
  9. Todo updates stay lightweight: When updating todo.md in Step 4, make simple status changes directly. For complex plan restructuring, the update-plan skill should be used instead.

Templates

This skill includes a normative template as a bundled file. Only read the templates when processing them. Output MUST follow the template headings and frontmatter keys:

  • tpl-session-handover.md - Structure for handover documents

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 Generate Handover AI skill do?

Generate a session handover document that captures progress, decisions, and context for seamless session continuity. This documentation shall serve Agents and Humans when working in consecutive sessions with the project. Use this skill at the end of a work session or when context transfer to a new session is needed.

Why use Generate Handover on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/DasDigitaleMomentum/opencode-processing-skills/tree/main/skills/generate-handover. 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 Generate Handover?

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 Generate Handover?

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

Is the Generate Handover AI skill free?

Yes. It is published on GitHub by DasDigitaleMomentum 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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