speckit-swarmOrchestrates complex tasks by detecting keywords, decomposing work into parallel chunks, and coordinating multiple specialized agent personas for full execut...
Install via ClawdBot CLI:
clawdbot install Heldinhow/speckit-swarmNative implementation of oh-my-opencode-style orchestration using OpenClaw's tools.
skills/speckit-swarm/
├── SKILL.md # This file
├── src/
│ ├── ultrawork.ts # Ultrawork detection & trigger
│ ├── personas/
│ │ ├── mod.ts # Persona exports
│ │ ├── sisyphus.ts # Main orchestrator
│ │ ├── hephaestus.ts # Deep worker
│ │ ├── oracle.ts # Design/debug
│ │ ├── librarian.ts # Research/docs
│ │ └── explore.ts # Fast scout
│ ├── planner.ts # Task decomposition
│ └── index.ts # Main entry
# Use personas directly
sessions_spawn task:"..." model:"minimax-m2.5" thinking:"high"
When user includes "ulw" or "ultrawork":
import { PERSONAS, buildTaskPrompt } from './speckit-swarm';
const persona = PERSONAS.hephaestus;
const task = "Fix the login bug in auth.ts";
sessions_spawn({
task: buildTaskPrompt({ task, persona: 'hephaestus' }),
model: persona.config.model,
thinking: persona.config.thinking
});
When user includes "ulw" or "ultrawork":
import { planTask, shouldUseUltrawork } from './speckit-swarm';
const task = "ulw refactor the auth module";
if (shouldUseUltrawork(task)) {
const plan = planTask(task);
// Execute plan.chunks with parallel_spawn
}
import { planTask } from './speckit-swarm';
const plan = planTask("Create a new API endpoint");
// plan.chunks = [{ label: 'spec', ... }, { label: 'setup', ... }, ...]
O handler detecta "ulw" automaticamente e prepara tarefas para parallel_spawn.
// Verifica se contém keyword ulw
containsUltrawork(task: string): boolean
// Limpa o prefixo ulw da tarefa
cleanUltraworkTask(task: string): string
// Prepara execução ultrawork
prepareUltrawork(task: string): {
shouldExecute: boolean;
chunks: Array<{
label: string;
task: string;
model?: string;
thinking?: string;
}>;
cleanedTask: string;
}
// Na minha resposta, quando receber mensagem com "ulw":
const ultrawork = prepareUltrawork("ulw create a new API");
if (ultrawork.shouldExecute) {
// Executar com parallel_spawn
parallel_spawn({
tasks: ultrawork.chunks,
wait: "all"
});
}
Antes de paralelizar, verifico se não há conflitos:
| Tipo de Tarefa | Estratégia |
|----------------|------------|
| Criar novo projeto/CLI/API | PARALLEL ✓ |
| Múltiplos arquivos novos | PARALLEL ✓ |
| Refatorar módulo | CAUTIOUS (verifica dependências) |
| Corrigir bug | SEQUENTIAL ✗ |
| Editar mesmo arquivo | SEQUENTIAL ✗ |
| Tarefa simples | SINGLE |
Isso evita problemas de concorrência quando múltiplos agentes tentam modificar o mesmo arquivo.
// Detecção automática
const result = prepareParallelExecution("criar um novo CLI");
// result.shouldExecute = true (detectou complexidade)
if (result.shouldExecute) {
parallel_spawn({
tasks: result.chunks,
wait: "all"
});
}
Generated Feb 24, 2026
When starting a new software project, such as creating a CLI tool or API, Speckit Swarm can automatically detect 'ulw' keywords to decompose the task into parallel chunks. This allows simultaneous work on specifications, setup, and initial coding by different personas like Oracle for design and Hephaestus for deep implementation, speeding up project initiation and reducing time-to-market.
For refactoring large codebases or modules, the system uses Ultrawork Mode to break down the task into non-conflicting chunks, such as updating dependencies, rewriting functions, and testing. It employs cautious parallel execution to avoid file conflicts, with personas like Sisyphus coordinating and Librarian researching patterns, ensuring efficient and error-free refactoring.
In debugging complex systems, Speckit Swarm can be used manually with the Oracle persona to analyze architecture and hunt for bugs, while Explore scouts for quick file analysis. It avoids parallel execution for bug fixes to prevent concurrency issues, focusing on sequential, thorough investigation to resolve issues reliably in production environments.
For tasks requiring extensive research or documentation, such as creating technical reports or exploring codebases, the Librarian persona handles docs lookup and pattern finding with medium thinking. It can work in parallel with other personas for complementary tasks, like Oracle designing structure, to produce comprehensive and accurate documentation efficiently.
When building a minimum viable product (MVP), Speckit Swarm leverages Ultrawork Mode to parallelize creation of multiple components, such as UI, backend, and database setup. Personas like Hephaestus execute deep work autonomously, while Sisyphus tracks progress, enabling fast iteration and deployment for startups or agile teams.
Offer Speckit Swarm as a cloud-based service where development teams subscribe monthly to access AI-powered orchestration. It includes features like automatic task decomposition and persona management, helping teams reduce project timelines and improve code quality, with tiered pricing based on usage and support levels.
Sell perpetual or annual licenses to large enterprises for on-premises or private cloud deployment. This model includes custom integration, training, and premium support, targeting industries like finance or healthcare that require high security and compliance, with revenue from upfront fees and maintenance contracts.
Provide a free version with basic features like manual persona usage and limited parallel execution, then upsell premium add-ons such as advanced Ultrawork Mode, additional personas, or priority support. This attracts individual developers and small teams, converting them to paid users as their needs grow.
💬 Integration Tip
Integrate Speckit Swarm by importing its modules into existing TypeScript/JavaScript projects and using the prepareUltrawork function to automatically handle complex tasks, ensuring to check for concurrency conflicts before parallel execution to avoid file modification issues.
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