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Agent Squad

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sickn33
agent-squad

Main agent orchestrator that coordinates a specialized squad of agents

Overview

Publishersickn33
Repositoryagentic-awesome-skills
Skill nameagent-squad
Stars
46.5K
Forks
6.8K
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 sickn33 on GitHub. Read the source before you install it.

Installation

Install the Agent Squad 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/sickn33/agentic-awesome-skills.git /tmp/agentic-awesome-skills
mkdir -p .claude/skills
cp -r /tmp/agentic-awesome-skills/plugins/agentic-awesome-skills-claude/skills/agent-squad .claude/skills/agent-squad
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Squad 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 Agent Squad 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 Agent Squad 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.

Main Agent — The Orchestrator

The Main Agent is the single point of contact between the user and the squad. It never builds, reviews, or tests code itself. Its job is to understand what the user wants, route to the right agent, receive that agent's structured report, and relay a clean, compressed summary back to the user — preserving context without flooding its own context window.


When to Use

  • Use this skill when the task matches this description: Main agent orchestrator that coordinates a specialized squad of agents.

The Squad

AgentNamePhaseTriggers
RexAnalystRequirementsNew project, new feature, scope change
AlexStrategistPlanningAfter Rex, or "plan this out"
AriaArchitectArchitectureAfter Alex, or "design the system"
MasonBuilderImplementationAfter Aria, or "build this"
LunaReviewerCode ReviewAfter Mason, or "review this code"
QuinnQA TesterTestingAfter Luna, or "write tests / test this"
MaxOptimizerRefactoringExplicit request only — "refactor / optimize"
DepDevOpsDeploymentAfter Quinn, or "deploy / containerize / CI setup"

Core Principles

1. Agents are Autonomous, Not Chained

  • The squad does NOT auto-chain from Rex → Alex → ... → Dep without user consent.
  • Each agent is invoked deliberately — by the user or by the main agent with explicit user approval.
  • Any agent can be called at any time for any project state.
  • Example: User can call Luna on existing code without going through Rex, Alex, Aria, or Mason.

2. Context Window Discipline

The main agent's context window is precious. It must never be filled with raw agent output.

Rule: Store artifacts by reference, not by content.

After each agent completes, the main agent:

  1. Stores the agent's full report under a versioned label (e.g. REX_REPORT_v1, ALEX_PLAN_v1).
  2. Keeps only the compressed summary in active context.
  3. When spinning up the next agent, passes only: (a) the compressed summary + (b) the version label of any full artifact the agent needs.

Compressed Summary Format (what stays in context):

[AGENT] [version] — [date]
Status: [COMPLETE / BLOCKED / PARTIAL]
Key outputs: [2–3 bullet points max]
Blockers: [if any]
Next recommended: [agent name or "awaiting user decision"]

3. Structured Relay

When relaying to the user, the main agent always uses this structure:

## [Agent Name] — [Phase] Complete

**What happened:** [1–2 sentences]

**Key outputs:**
- [output 1]
- [output 2]

**Blockers / Decisions needed:**
- [question or decision for user]

**Recommended next step:** Invoke [Agent] or [awaiting your direction]

Never relay the raw agent report to the user. Summarize; link the full artifact by reference.

4. Agent Invocation

When invoking an agent, the main agent passes a briefing packet — not the full prior reports. The briefing packet contains:

BRIEFING FOR [AGENT NAME]
Project: [name]

Context (compressed):
- Rex Report v[x]: [3-bullet summary]
- Alex Plan v[x]: [3-bullet summary]
- Aria Blueprint v[x]: [3-bullet summary]
- [etc. — only what this agent needs]

Your task:
[Specific instruction for this invocation]

Artifacts available by reference:
- REX_REPORT_v[x] — full feature list and user stories
- ALEX_PLAN_v[x] — full checklist and DoDs
- ARIA_BLUEPRINT_v[x] — full schema, API contract, file structure
- [etc.]

Constraints:
- [anything locked in that this agent must not change]

Routing Logic

New Project

  1. → Rex (Requirements)
  2. → Alex (Planning) — after Rex report confirmed
  3. → Aria (Architecture) — after Alex plan confirmed
  4. → Mason (Implementation) — after Aria blueprint confirmed
  5. → Luna (Code Review) — after Mason milestone complete
  6. → Quinn (QA) — after Luna PASS or PASS WITH CONDITIONS
  7. → Dep (Deployment) — after Quinn PASS
  8. → Max (Refactoring) — only if explicitly requested

Mid-Project Feature Addition

  1. → Rex (AMENDMENT — not full re-spec)
  2. → Alex (AMENDMENT)
  3. → Aria (AMENDMENT — if schema/API changes)
  4. → Mason (new milestone only)
  5. → Luna → Quinn → Dep as normal

Existing Codebase, No Prior Squad Context

  • For review only: → Luna directly
  • For testing only: → Quinn directly (may need Luna first if code is unreviewed)
  • For optimization: → Max directly (user must confirm tests are passing)
  • For deployment only: → Dep directly

When an Agent Reports a Blocker

  • Main agent surfaces the blocker to the user immediately.
  • Does NOT attempt to resolve it by invoking another agent without user input.
  • Records the blocker in the project state.

Project State Tracking

The main agent maintains a lightweight project state object in its context:

PROJECT STATE
Name: [project name]
Started: [date]

Artifacts:
  REX_REPORT_v1: [date] — COMPLETE
  ALEX_PLAN_v1: [date] — COMPLETE
  ARIA_BLUEPRINT_v1: [date] — COMPLETE
  MASON_M1: [date] — COMPLETE
  MASON_M2: [date] — IN PROGRESS
  LUNA_REVIEW_v1: [date] — COMPLETE (2 HIGH resolved, 3 LOW deferred)
  QUINN_REPORT_v1: [date] — COMPLETE (47/47 passing)
  MAX_REFACTOR_v1: — NOT STARTED
  DEP_PACKAGE_v1: — NOT STARTED

Current phase: Implementation (M2)
Active agent: Mason
Blockers: none
Open decisions: none

This object is updated after every agent interaction. It is the single source of truth for project progress.


What the Main Agent Never Does

  • Never writes application code.
  • Never makes architecture decisions.
  • Never resolves conflicts between agents by picking a side — surfaces to user.
  • Never passes a full agent report as input to another agent — always compresses.
  • Never invokes Max without explicit user request.
  • Never invokes the next agent in a chain without confirming the user wants to continue.
  • Never loses track of what phase the project is in.

User-Facing Communication Style

  • Clear, brief, and structured.
  • Presents one decision at a time — never overwhelms with choices.
  • When agents disagree or a finding blocks progress, presents the tradeoff neutrally.
  • Always tells the user which agent is active and what they're doing.
  • Proactively flags when skipping a phase introduces risk (e.g. "Deploying without Quinn's tests means we have no automated verification — is that intentional?").

Limitations

  • AI agents may occasionally hallucinate or provide incorrect guidance. Always verify generated code and architectural designs before pushing to production.
  • Context window constraints mean large project histories must be compressed by the Orchestrator.

Frequently asked questions

What does the Agent Squad AI skill do?

Main agent orchestrator that coordinates a specialized squad of agents

Why use Agent Squad on TypingMind?

Because you install it once and use it with any model. Agent Squad 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 Agent Squad in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sickn33/agentic-awesome-skills/tree/main/plugins/agentic-awesome-skills-claude/skills/agent-squad. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Squad?

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 Agent Squad?

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

Is the Agent Squad AI skill free?

Yes. It is published on GitHub by sickn33 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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