Real Work

Community

Elfocrash

real-work

Use when planning a multi-step task or working in plan mode and you need to capture the plan as a durable, resumable artifact — breaking work into phases with per-item checkboxes, completion tracking, autonomous verification, and a handoff summary so a future agent can pick up where you left off. Use when user wants to create or design a plan or mentioned "real work".

Overview

Publisher	Elfocrash
Repository	`skills`
Skill name	`real-work`
Stars	148
Forks	21
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 Elfocrash on GitHub. Read the source before you install it.

Installation

Install the Real Work AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Elfocrash/skills/tree/master/skills/real-work
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.

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/Elfocrash/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/real-work .claude/skills/real-work

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Real Work 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 Real Work 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 Real Work 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.

Real Work

Turn planning into a durable, resumable artifact. The plan file — not the conversation — is the source of truth: it records what to do, what's done, how it was verified, and how to deploy. Any future agent can resume from it with zero prior context.

Use when planning multi-step / multi-session work that may outlive the current session. Skip for trivial single-session tasks.

1. Reach complete understanding first

Do not write the plan until scope is fully understood. Relentlessly ask the user questions until you both share a complete understanding with no gaps — treat an unasked question as a future bug.

Don't stop at the first round; keep going until no ambiguity, assumption, or open decision remains. Probe edges: scope boundaries (in/out), dependencies, constraints, success criteria, data, environments, deployment, failure cases.
Surface every assumption for the user to confirm. If an answer opens a new unknown, ask the follow-up — drill down recursively.
Use AskUserQuestion for concrete choices. When done, summarize the full scope back and only proceed once the user confirms nothing is missing.

2. Write the plan

Save to plans/<descriptive-name>.md in the repository root (create plans/ if needed). Use this self-documenting template:

markdown
# <Work Title>

<1-2 sentence goal and scope.>

## For Future Agents
As work proceeds: mark checkboxes `- [x]` as items complete; when a phase is done,
set its status to `Complete` and write its **Phase Summary** (what was done, key
decisions, anything needed to continue with zero context); run the phase's
**Verification Plan** and record the result before moving on. When all phases are
done, fill in **Final Recap** and **Deployment Plan**.

## Phase 1: <Title>
Status: Not started   <!-- Not started | In progress | Complete -->

- [ ] <concrete, actionable item>
- [ ] <concrete, actionable item>

### Verification Plan
- <command/check the agent can run autonomously, with expected result>

### Phase Summary
_(write when phase completes)_

## Phase 2: <Title>
Status: Not started
- [ ] <actionable item>
### Verification Plan
- <autonomous check>
### Phase Summary
_(write when phase completes)_

## Final Recap
_(write when all phases complete: summary of the entire piece of work)_

## Deployment Plan
_(write when all phases complete: step-by-step deployment instructions)_

Common mistakes

Vague items — each checkbox is a concrete task ("Add retry logic to PaymentClient.Charge"), not a theme ("improve payments").
Non-autonomous verification — give runnable commands with expected output, not "test it manually".
Wrong location — always the repo-root plans/ folder.
Pre-filling summaries — phase summaries, recap, and deployment plan stay as placeholders until that work actually completes.

Frequently asked questions

What does the Real Work AI skill do?

Why use Real Work on TypingMind?

Because you install it once and use it with any model. Real Work 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 Real Work in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Elfocrash/skills/tree/master/skills/real-work. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Real Work?

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 Real Work?

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

Is the Real Work AI skill free?

Yes. It is published on GitHub by Elfocrash 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.

View all

Tag Duplicate Prs Issues

openclaw

OrganizationPopular

Use gitcrawl to search duplicate OpenClaw PRs/issues, group related work in prtags, and sync duplicate state to GitHub.

Update Team Server

Update the operator-configured Team server through its canonical owner; trust native validation and acceptance without duplicate checks or schedulers.

Cloud Image Bake

Bake, select, prove, and safely retire a Cloud Worker image with crabbox and config one-liners.

Acp Router

Route plain-language requests for Claude Code, Cursor, Copilot, OpenClaw ACP, OpenCode, Gemini CLI, Qwen, Kiro, Kimi, iFlow, Factory Droid, Kilocode, or explicit ACP harness work into either OpenClaw…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Real Work

1. Reach complete understanding first

2. Write the plan

Common mistakes

Frequently asked questions

Related AI Skills

Set up your own AI workspace now