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Dispatching Parallel Agents

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bobmatnyc
Dispatching Parallel Agents

Use multiple Claude agents to investigate and fix independent problems concurrently

Overview

Publisherbobmatnyc
Repositoryclaude-mpm
Skill nameDispatching Parallel Agents
Stars
152
Forks
34
Bundled files
4
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Dispatching Parallel Agents 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/bobmatnyc/claude-mpm.git /tmp/claude-mpm
mkdir -p .claude/skills
cp -r /tmp/claude-mpm/src/claude_mpm/skills/bundled/collaboration/dispatching-parallel-agents .claude/skills/bobmatnyc-dispatching-parallel-agents
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dispatching Parallel Agents 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 Dispatching Parallel Agents 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 Dispatching Parallel Agents 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.

Dispatching Parallel Agents

SCOPE: ORCHESTRATOR / PM-LEVEL ONLY (#581). This skill describes the top-level orchestrator (PM) capability to spawn parallel agents via the Agent/Task tool. Subagents do not have access to the Agent tool and cannot spawn sub-subagents — agent-spawning is harness-enforced at the top level. If you are a subagent (engineer, qa, research, etc.), this skill does not apply to you: complete your assigned scope and return results to the PM. (This skill is intentionally not deployed to subagents; see config/skill_to_agent_mapping.yaml.)

Overview

When you have multiple unrelated failures (different test files, different subsystems, different bugs), investigating them sequentially wastes time. Each investigation is independent and can happen in parallel.

Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.

When to Use This Skill

Activate this skill when you're facing:

  • 3+ test files failing with different root causes
  • Multiple subsystems broken independently
  • Each problem is self-contained - can be understood without context from others
  • No shared state between investigations
  • Clear domain boundaries - fixing one won't affect others

Don't use when:

  • Failures are related (fix one might fix others)
  • Need to understand full system state first
  • Agents would interfere with each other (editing same files)
  • Exploratory debugging (don't know what's broken yet)

The Iron Law

One agent, one problem domain, one clear outcome.
Never overlap scopes. Never share state. Always integrate consciously.

Core Principles

Independence is Key

Problems must be truly independent - no shared files, no related root causes, no dependencies between fixes.

Focus Over Breadth

Each agent gets narrow scope: one test file, one subsystem, one clear goal. Broad tasks lead to confusion.

Clear Output Required

Every agent must return a summary: what was found, what was fixed, what changed. No silent fixes.

Conscious Integration

Don't blindly merge agent work. Review summaries, check conflicts, run full suite, verify compatibility.

Quick Start

1. Identify Independent Domains

Group failures by what's broken:

File A tests: Tool approval flow
File B tests: Batch completion behavior
File C tests: Abort functionality

Each domain is independent - fixing tool approval doesn't affect abort tests.

2. Create Focused Agent Tasks

Each agent gets:

  • Specific scope: One test file or subsystem
  • Clear goal: Make these tests pass
  • Constraints: Don't change other code
  • Expected output: Summary of what you found and fixed

agent-prompts.md for prompt templates and examples

3. Dispatch in Parallel

typescript
// In Claude Code / AI environment
Task("Fix agent-tool-abort.test.ts failures")
Task("Fix batch-completion-behavior.test.ts failures")
Task("Fix tool-approval-race-conditions.test.ts failures")
// All three run concurrently

coordination-patterns.md for dispatch strategies

4. Review and Integrate

When agents return:

  • Read each summary - understand what changed
  • Verify fixes don't conflict - check for same file edits
  • Run full test suite - ensure compatibility
  • Spot check changes - agents can make systematic errors

troubleshooting.md for conflict resolution

Decision Tree

Multiple failures?
  └→ Are they independent?
      ├→ NO (related) → Single agent investigates all
      └→ YES → Can they work in parallel?
          ├→ NO (shared state) → Sequential agents
          └→ YES → Parallel dispatch ✓

Key Benefits

  1. Parallelization - Multiple investigations happen simultaneously
  2. Focus - Each agent has narrow scope, less context to track
  3. Independence - Agents don't interfere with each other
  4. Speed - N problems solved in time of 1

Navigation

Pattern Reference

Agent Management

  • Agent Prompts - Prompt structure, templates, common mistakes, constraints

Learning Resources

  • Examples - Real-world scenarios, case studies, time savings analysis

Problem Solving

  • Troubleshooting - Conflict resolution, verification strategies, common pitfalls

Related Skills

Key Reminders

  1. Independence is mandatory - Related failures need single-agent investigation
  2. Focus beats breadth - Narrow scope per agent prevents confusion
  3. Always verify integration - Don't blindly merge agent work
  4. Clear outputs required - Every agent returns summary of changes
  5. Parallelization has overhead - Only worth it for 3+ independent problems

Red Flags - STOP

STOP immediately if:

  • Agents are editing the same files (scope overlap)
  • Fixes from one agent break another's work (hidden dependencies)
  • You can't clearly separate problem domains (not independent)
  • Agents return no summary (can't verify changes)
  • Integration requires major refactoring (conflicts)

When in doubt: Start with one agent, understand the landscape, then dispatch if truly independent.

Integration with Other Skills

Prerequisite: Basic understanding of problem domains and test structure Complementary: pm-workflow for coordinating multiple agents Domain-specific: Testing skills for understanding test failures

Real-World Impact

From debugging session (2025-10-03):

  • 6 failures across 3 test files
  • 3 agents dispatched in parallel
  • All investigations completed concurrently
  • Zero conflicts between agent changes
  • Time saved: 3 problems solved in parallel vs sequentially

examples.md for detailed case study

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dispatching Parallel Agents AI skill do?

Use multiple Claude agents to investigate and fix independent problems concurrently

Why use Dispatching Parallel Agents on TypingMind?

Because you install it once and use it with any model. Dispatching Parallel Agents 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 Dispatching Parallel Agents in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bobmatnyc/claude-mpm/tree/main/src/claude_mpm/skills/bundled/collaboration/dispatching-parallel-agents. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dispatching Parallel Agents?

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 Dispatching Parallel Agents?

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

Is the Dispatching Parallel Agents AI skill free?

It is published on GitHub by bobmatnyc. Check the repository for licensing terms. 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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