Cowork Calendar Defrag logo

Cowork Calendar Defrag

Organization
OneWave-AI
cowork-calendar-defrag

Audit your calendar with Cowork's calendar tools -- measure meeting load and fragmentation, identify which recurring meetings earn their slot, propose consolidations and focus blocks, and draft the diplomatic messages that reclaim your week.

Overview

PublisherOneWave-AI
Repositoryclaude-skills
Skill namecowork-calendar-defrag
Stars
293
Forks
49
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Cowork Calendar Defrag 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.
  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/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/cowork-calendar-defrag .claude/skills/cowork-calendar-defrag
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cowork Calendar Defrag 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 Cowork Calendar Defrag 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 Cowork Calendar Defrag 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.

Cowork Calendar Defrag

Treat the calendar like a disk that needs defragmenting: measure what is actually there, identify waste, consolidate, and carve out contiguous space for real work. Uses the connected calendar tools (Microsoft 365 / Google Calendar) to read events; every change is proposed, and the human approves before anything is created, moved, or declined.

Workflow

  1. Measure. Pull the last 4 weeks and the next 2. Compute: hours in meetings per week, longest uninterrupted block per day, fragmentation score (count of gaps under 45 minutes -- too short to do real work, long enough to lose), meetings by type (recurring vs. ad hoc, internal vs. external), and after-hours creep.
  2. Score the recurring load. For each recurring meeting: duration x frequency x attendee count = weekly cost. Flag candidates against the classic tells -- no agenda in the invite, attendance optional-in-practice, could-be-async status updates, double-booked slots the user routinely skips. External and client meetings are measured but never flagged for cuts without explicit instruction.
  3. Propose the defrag. A specific plan, not principles: which recurrings to shorten (60 -> 25), consolidate (three 1:1s into office hours), make async, or leave alone; where the 2-3 weekly focus blocks go (matched to when the calendar shows the user actually has energy-adjacent free space, e.g. mornings); and which small gaps to close by nudging meetings adjacent.
  4. Draft the messages. For each proposed change involving other people: a short, warm, blame-free draft ("I'm consolidating my recurring syncs -- can we fold this into..."). The awkward message is the real barrier to a better calendar; remove it.
  5. Execute on approval. Create the focus blocks (marked busy, named for the work), send nothing -- updated invites and messages remain drafts for the human to send. Output calendar-defrag-report.md with before/after metrics: meeting hours reclaimed, longest block gained.

Rules

  • Read freely, write only what was approved, send nothing. Calendars are shared surfaces; a wrong move is publicly visible.
  • Never propose cutting external, client, or 1:1-with-manager meetings unless the user asked for a full-scope review.
  • Fragmentation is the enemy, not meetings. Six hours of meetings in two blocks beats four hours scattered across nine slots.
  • Focus blocks get names ("Proposal writing") -- anonymous "Busy" blocks get scheduled over within two weeks.
  • Respect the user's stated no-touch zones (school pickup, gym, standing personal events) as hard constraints.
  • Re-run comparisons honestly: if the defrag did not hold (blocks got booked over), report it and diagnose which changes stuck.

Scheduled Mode

As a monthly Cowork scheduled task: re-measure, compare against the last report, flag regression (creeping recurrings, eroded focus blocks), and propose the next round of cuts.

Quick Commands

  • "Audit my calendar" -- steps 1-2, the measurement and scorecard
  • "Defrag my week" -- full workflow
  • "Where can I fit 3 hours of deep work?" -- focus-block placement only
  • "Draft the decline for [meeting]" -- one diplomatic message

Frequently asked questions

What does the Cowork Calendar Defrag AI skill do?

Audit your calendar with Cowork's calendar tools -- measure meeting load and fragmentation, identify which recurring meetings earn their slot, propose consolidations and focus blocks, and draft the diplomatic messages that reclaim your week.

Why use Cowork Calendar Defrag on TypingMind?

Because you install it once and use it with any model. Cowork Calendar Defrag 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 Cowork Calendar Defrag in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/cowork-calendar-defrag. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cowork Calendar Defrag?

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 Cowork Calendar Defrag?

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

Is the Cowork Calendar Defrag AI skill free?

Yes. It is published on GitHub by OneWave-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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