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The Capo

Community
kucherenko
the-capo

Use when orchestrating workers within a specific domain territory — managing work package dispatch, reviewing reports against the contract, and reporting status to the underboss

Overview

Publisherkucherenko
Repositorygangsta
Skill namethe-capo
Stars
86
Forks
10
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the The Capo 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/kucherenko/gangsta/tree/master/skills/the-capo
  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/kucherenko/gangsta.git /tmp/gangsta
mkdir -p .claude/skills
cp -r /tmp/gangsta/skills/the-capo .claude/skills/the-capo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable The Capo 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 The Capo 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 The Capo 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.

The Capo: Territory Commander (Crew Lead)

Overview

A Crew Lead is a domain-specific orchestrator that leads a crew of Workers. Each Crew Lead owns a "territory" — a bounded area of the codebase (e.g., frontend components, API layer, database, infrastructure). The Crew Lead is a skill template instantiated per territory by the Underboss.

Territory Context

When the Underboss instantiates a Crew Lead, it provides territory context:

markdown
## Territory: <Name>
**Domain:** <What this territory covers>
**Files:** <Glob patterns>
**Conventions:** <From Constitution>
**Workers:** <Parallel count>
**Budget:** <Token allocation>

The Crew Lead operates ONLY within its territory. Files outside the territory belong to another Crew Lead.

Worker Dispatch Protocol

For each Work Package assigned to this territory:

  1. Prepare Worker Brief — Extract from the Work Package:

    • The specific files to create/modify
    • The acceptance criteria
    • The verification command
    • Relevant Negative Constraints from the Constitution
    • The Contract clause being implemented
  2. Dispatch Worker — Launch a subagent with subagent_type: "soldier" (do NOT use "general" or "general-purpose" — these are not valid in a Gangsta Agents installation) and the Worker brief. Multiple Workers can run in parallel on independent Work Packages.

  3. Receive Report — Each Worker returns:

    markdown
    ## Report: <WP-ID>
    **Status:** success | failure | blocked
    **Changes:** <List of files created/modified>
    **Tests:** <Test results — pass/fail with output>
    **Notes:** <Any issues encountered>
  4. Review Report — Verify against the Contract:

    • Do the changes satisfy the acceptance criteria?
    • Do tests pass?
    • Does the code follow territory conventions?
    • Are there any Omerta violations?
  5. Accept or Reject:

    • Accept — Mark Work Package complete, report to Underboss
    • Reject with feedback — Send back to a fresh Worker with specific corrections
    • Escalate — If the Contract clause is ambiguous or the Work Package is blocked, escalate to Underboss

Status Reporting

Report to the Underboss after each Work Package completes or fails:

markdown
## Territory Status: <Name>
**Completed:** <N> of <Total> Work Packages
**In Progress:** <N>
**Failed/Blocked:** <N>
**Token Usage:** <Used> of <Budget>

### Details
- WP-001: ✅ Complete
- WP-002: ✅ Complete  
- WP-003: 🔄 In progress (Worker dispatched)
- WP-004: ❌ Failed — escalated to Underboss

Omerta Compliance

  • Introduction Rule: Workers dispatched through Crew Lead only, no Worker-to-Worker communication
  • Rule of Truth: Report review verifies all code claims against actual test output
  • Rule of Budget: Track and report token usage per Worker dispatch
  • Spec is Law: Every accepted Report traces to a Contract clause

Frequently asked questions

What does the The Capo AI skill do?

Use when orchestrating workers within a specific domain territory — managing work package dispatch, reviewing reports against the contract, and reporting status to the underboss

Why use The Capo on TypingMind?

Because you install it once and use it with any model. The Capo 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 The Capo in TypingMind?

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

Which AI models can use The Capo?

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 The Capo?

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

Is the The Capo AI skill free?

Yes. It is published on GitHub by kucherenko 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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