dispatching-parallel-agents

obra/superpowers · Agent Skill

Distribuisce attività indipendenti a più agenti per l'esecuzione parallela, ottimizzando tempo e risorse.

Vai all'installazione ↓

Panoramica

AutoreobraCommunity
Repositoryobra/superpowers ↗
Cartella dello skilldispatching-parallel-agents
Stelle282.954
File inclusi1
LicenzaMIT
Aggiornato23 luglio 2026
LinkSorgente dello skill ↗ · Repository ↗

Verifica Mozgi

Cosa abbiamo trovato nei file dello skill. I dettagli con l’abbonamento.

Sicurezza
rischio basso · nessun rischio evidente — il report completo mostra i dettagli
Compatibilità
solo istruzioni — funziona con la maggior parte degli agenti
Skill simili
51 skill simili trovati
Inoltre con l’abbonamento

Installazione

Uno skill è una cartella con un file SKILL.md. Scegli il tuo agente ed esegui i comandi in un terminale (macOS, Linux o Git Bash su Windows) dalla radice del progetto.

Incolla il prompt in Claude, Codex o un altro assistente: controllerà lo skill e lo installerà.

Install the “dispatching-parallel-agents” skill from mozgi.io (https://mozgi.io/skills/dispatching-parallel-agents/) for me.

1. Download the archive: https://mozgi.io/skills/dispatching-parallel-agents/download
   If it fails, take the skill folder from the source: https://github.com/obra/superpowers/tree/main/skills/dispatching-parallel-agents
2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me.
3. Put the “dispatching-parallel-agents” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.).
4. Make sure <skills folder>/dispatching-parallel-agents/SKILL.md exists.
5. Briefly tell me what this skill does and offer to try it on my task.

If you cannot do a step yourself, tell me what to click or type.

File dello skill

1 file Scarica ZIP

Leggi SKILL.md e i file correlati prima di installare. Clicca un file per l'anteprima.

Contenuto di SKILL.md

Testo originale dell'autore · sola lettura

Dispatching Parallel Agents

Overview

You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.

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

digraph when_to_use {
    "Multiple failures?" [shape=diamond];
    "Are they independent?" [shape=diamond];
    "Single agent investigates all" [shape=box];
    "One agent per problem domain" [shape=box];
    "Can they work in parallel?" [shape=diamond];
    "Sequential agents" [shape=box];
    "Parallel dispatch" [shape=box];

    "Multiple failures?" -> "Are they independent?" [label="yes"];
    "Are they independent?" -> "Single agent investigates all" [label="no - related"];
    "Are they independent?" -> "Can they work in parallel?" [label="yes"];
    "Can they work in parallel?" -> "Parallel dispatch" [label="yes"];
    "Can they work in parallel?" -> "Sequential agents" [label="no - shared state"];
}

Use when:

  • 3+ test files failing with different root causes
  • Multiple subsystems broken independently
  • Each problem can be understood without context from others
  • No shared state between investigations

Don't use when:

  • Failures are related (fix one might fix others)
  • Need to understand full system state
  • Agents would interfere with each other

The Pattern

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

3. Dispatch in Parallel

Issue all three subagent dispatches in the same response — they run in parallel:

Subagent (general-purpose): "Fix agent-tool-abort.test.ts failures"
Subagent (general-purpose): "Fix batch-completion-behavior.test.ts failures"
Subagent (general-purpose): "Fix tool-approval-race-conditions.test.ts failures"
# All three run concurrently.

Multiple dispatch calls in one response = parallel execution. One per response = sequential.

4. Review and Integrate

When agents return:

  • Read each summary
  • Verify fixes don't conflict
  • Run full test suite
  • Integrate all changes

Agent Prompt Structure

Good agent prompts are:

1. Focused - One clear problem domain

2. Self-contained - All context needed to understand the problem

3. Specific about output - What should the agent return?

Fix the 3 failing tests in src/agents/agent-tool-abort.test.ts:

1. "should abort tool with partial output capture" - expects 'interrupted at' in message
2. "should handle mixed completed and aborted tools" - fast tool aborted instead of completed
3. "should properly track pendingToolCount" - expects 3 results but gets 0

These are timing/race condition issues. Your task:

1. Read the test file and understand what each test verifies
2. Identify root cause - timing issues or actual bugs?
3. Fix by:
   - Replacing arbitrary timeouts with event-based waiting
   - Fixing bugs in abort implementation if found
   - Adjusting test expectations if testing changed behavior

Do NOT just increase timeouts - find the real issue.

Return: Summary of what you found and what you fixed.

Common Mistakes

❌ Too broad: "Fix all the tests" - agent gets lost

✅ Specific: "Fix agent-tool-abort.test.ts" - focused scope

❌ No context: "Fix the race condition" - agent doesn't know where

✅ Context: Paste the error messages and test names

❌ No constraints: Agent might refactor everything

✅ Constraints: "Do NOT change production code" or "Fix tests only"

❌ Vague output: "Fix it" - you don't know what changed

✅ Specific: "Return summary of root cause and changes"

When NOT to Use

Related failures: Fixing one might fix others - investigate together first

Need full context: Understanding requires seeing entire system

Exploratory debugging: You don't know what's broken yet

Shared state: Agents would interfere (editing same files, using same resources)

Real Example from Session

Scenario: 6 test failures across 3 files after major refactoring

Failures:

  • agent-tool-abort.test.ts: 3 failures (timing issues)
  • batch-completion-behavior.test.ts: 2 failures (tools not executing)
  • tool-approval-race-conditions.test.ts: 1 failure (execution count = 0)

Decision: Independent domains - abort logic separate from batch completion separate from race conditions

Dispatch:

Agent 1 → Fix agent-tool-abort.test.ts
Agent 2 → Fix batch-completion-behavior.test.ts
Agent 3 → Fix tool-approval-race-conditions.test.ts

Results:

  • Agent 1: Replaced timeouts with event-based waiting
  • Agent 2: Fixed event structure bug (threadId in wrong place)
  • Agent 3: Added wait for async tool execution to complete

Integration: All fixes independent, no conflicts, full suite green

Verification

After agents return:

1. Review each summary - Understand what changed

2. Check for conflicts - Did agents edit same code?

3. Run full suite - Verify all fixes work together

4. Spot check - Agents can make systematic errors

Domande frequenti

Che cosa fa lo skill dispatching-parallel-agents?

Distribuisce attività indipendenti a più agenti per l'esecuzione parallela, ottimizzando tempo e risorse.

Come si installa dispatching-parallel-agents?

Apri il blocco “Installazione” in questa pagina e scegli il tuo agente — Claude Code, Codex, Cursor o Gemini CLI — per i comandi pronti che copiano la cartella dello skill nel posto giusto. Oppure copia il prompt dalla scheda “Con l'assistente” e lascia che sia l'assistente a controllare e installare lo skill.

Con quali modelli AI funziona dispatching-parallel-agents?

Gli skill sono semplici istruzioni in Markdown (formato Agent Skills), quindi dispatching-parallel-agents funziona con qualsiasi agente che legge SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode e altri. Il modello carica le istruzioni solo quando il compito corrisponde alla descrizione dello skill.

dispatching-parallel-agents è gratuito?

Lo skill è pubblicato apertamente da obra con licenza MIT. Lo skill in sé non costa nulla: paghi solo il tuo fornitore AI per i token usati.

È sicuro installare gli skill?

Uno skill è un insieme di istruzioni che il tuo agente seguirà: leggi SKILL.md e i file correlati prima di installarlo. Gli script nella cartella dello skill vengono eseguiti solo se li esegue l'agente: controlla cosa fa e non concedere permessi superflui.

In cosa differisce uno skill da un server MCP o da un plugin?

Un server MCP o un plugin danno al modello nuovi strumenti: codice che viene eseguito e restituisce un risultato. Uno skill fornisce conoscenza e metodo: come affrontare il compito, quali passi seguire e com'è un buon risultato. Non servono server né chiavi API.

Skill correlati

Tutti gli skill →