Wrap Up logo

Wrap Up

OrganizationPopular
anthropics
wrap-up

Close out (or revisit) a Claude Managed Agent build — refresh the overview page, recap every primitive the founder now owns, show the run log and live status, suggest 1–2 tailored next upgrades, and sweep hygiene (sessions archived, key only in .env, no literal dates in deployment kickoffs). Use when the founder says "/wrap-up", "wrap up", "close it out", "where do things stand with my agent", or at the end of a /launch-your-agent build.

Overview

Publisheranthropics
Repositorylaunch-your-agent
Skill namewrap-up
Stars
1K
Forks
205
Bundled files
Instructions only
LicenseApache-2.0
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 anthropics on GitHub. Read the source before you install it.

Installation

Install the Wrap Up 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/anthropics/launch-your-agent/tree/main/.claude/skills/wrap-up
  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/anthropics/launch-your-agent.git /tmp/launch-your-agent
mkdir -p .claude/skills
cp -r /tmp/launch-your-agent/.claude/skills/wrap-up .claude/skills/wrap-up
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wrap Up 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 Wrap Up 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 Wrap Up 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.

Wrap-up — celebrate it, show what they built, point at what's next

You are closing out (or checking in on) a founder's Claude Managed Agent. The tone is celebratory: they just shipped a managed agent that runs without them — say so, warmly, in one or two sentences ("🎉 you've shipped a managed agent — here's what you built"), then show them what they own and the one or two upgrades worth doing next. End on the overview page, not a wall of text. This is a moment, not a checklist read-out.

Follow the same voice rules as /launch-your-agent: warm, compact, tables for anything enumerable, primitives called by their real names (Outcome, Session, Deployment, Vault, Memory store) with a plain gloss on first use, the shared emoji shorthand (🤖 agent · 📦 environment · 🎯 outcome · ▶️ session · 🗓️ deployment · 🔌 connector · 🔐 vault · 🧠 memory store · 🧪 evals), no unverified timings. No cost notes — don't volunteer per-run or per-month spend figures; answer cost questions only if the founder asks.

1. Read the state

  • Read ./my-agent/: build-sheet.json, IDS.env, NEXT-DIRECTIONS.md, outcome.md, evals/, the existing agent-overview.html. (If there is no my-agent/ folder here, say so and stop — point them at /launch-your-agent.)
  • If my-agent/.env holds a key, source it and refresh live state via the API (shapes: ../launch-your-agent/references/cma-api.md): each session's status + outcome_evaluations[], deployment status + schedule.upcoming_runs_at, latest usage. Parse with python (strict=False), never jq.
  • No key → continue describe-only and say in one sentence that live status needs the key in .env.
  • A session still running → say so and ask (AskUserQuestion): wait for it, or wrap with what's done.
  • Nothing launched yet → wrap the plan only; everything below still applies but the status is "○ Planned".

2. Produce the wrap-up (in this order)

  1. Congratulate them. One or two warm sentences: they shipped a managed agent — name it, say what it now does on its own. 🎉
  2. Overview page. Refresh agent-overview.html (template: ../launch-your-agent/references/overview-template.html; styling in the sibling overview.css, linked, never inlined). The page already exists from the build — Edit only the slots that changed (status pill, top-bar IDs/stat cells, run-log <tbody> rows, eval verdicts, schedule with next run times, Console links for the key's workspace, the v1/v2 next directions) rather than re-Writing the whole file. If either agent-overview.html or my-agent/overview.css is missing, cp the CSS from the launch-your-agent skill's references/ first, then Write the HTML once. Open it in their browser — the page is the closing artifact; the chat below just points at it.
  3. "Here's what you built" — the primitives recap table, one row per CMA primitive that now exists: emoji · what it is (one plain sentence) · what it's set to · live ID · which card on the page shows it. Final muted row(s) for primitives deliberately not used → "see NEXT-DIRECTIONS". Follow with the run log table (run · rubric version · verdict · one-line note).
  4. "Here's what's next" — 1–2 extensions picked from the v1/v2 plan that matter most for this use case, pitched concretely: what it does for them, what it takes, how small the change is. The rest of the plan stays written down. Standard candidates to weigh alongside whatever the plan already holds: delivery via a connector (Slack/email, always_ask-gated), a memory store if runs repeat themselves, wiring a mocked connector for real, and — when it suits how they'll actually use the agent — a generated interface: a page or small app Claude Code builds for them in a follow-up session, shaped to the need (graphical output for results that want charts, a results viewer that pulls outputs and verdicts via the Files/Sessions API, or a simple way to interact with the agent — kick off a run, steer it, answer its confirmations).
  5. Hygiene sweep — quiet by default. Do the sweep (archive finished sessions; check the deployment's initial_events for literal dates; check the key only ever lived in .env; save a passed run as evals/case-01/expected.md if there's no golden case yet) and fix silently what you can. Only mention something if it's materially relevant — i.e. the founder must act (a key that touched chat → rotate; a literal date you can't patch without their say-so) or it changes how they use the agent. No "✅ all good" lists.
  6. Last words — one short line: everything lives in their Console (platform.claude.com → Managed Agents, in the key's workspace), this folder recreates it anywhere (LAUNCH.md), and they can rerun /wrap-up whenever they want a fresh picture.

Notes

  • Idempotent: running it again just refreshes the page and tables.
  • Don't re-litigate design decisions here — this skill reports and suggests; changes go through /launch-your-agent (or a plain conversation) afterwards.

Frequently asked questions

What does the Wrap Up AI skill do?

Close out (or revisit) a Claude Managed Agent build — refresh the overview page, recap every primitive the founder now owns, show the run log and live status, suggest 1–2 tailored next upgrades, and sweep hygiene (sessions archived, key only in .env, no literal dates in deployment kickoffs). Use when the founder says "/wrap-up", "wrap up", "close it out", "where do things stand with my agent", or at the end of a /launch-your-agent build.

Why use Wrap Up on TypingMind?

Because you install it once and use it with any model. Wrap Up 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 Wrap Up in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/launch-your-agent/tree/main/.claude/skills/wrap-up. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wrap Up?

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 Wrap Up?

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

Is the Wrap Up AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇