Process independent work items through bounded parallel tasks and structured aggregation.
Editorial note checked 2026-10-29 against this instruction snapshot. Supporting scripts and runtime behavior remain outside this editorial review.
The source defines table-oriented fanout, batching and output collection using specific interpreter tools. It is a specialized orchestration pattern rather than generic permission to spawn agents.
Developers with many independent, similarly structured work items.
The required tool environment may be absent. Parallelism multiplies costs and can produce partial results or repeated external effects if retries are not controlled.
Requires @langchain/quickjs code interpreter with swarm_task PTC tool
Inspect the pinned source snapshot and its supporting files first. The command selects this skill through the open-source skills CLI. Node.js and agent-specific setup may be required. Installation can download code. Catalog ingestion never executes skill instructions or install scripts.
npx skills add https://github.com/langchain-ai/langchain-skills/tree/126c384d8552dcb476b226c244172186cc3f4328/config/skills/swarm --skill swarmReview pinned skill folder ↗ · CLI documentation ↗
After source review, use npx skills check and npx skills update to inspect and apply upstream updates. Re-check changed instructions before running them.
Static review only. This is not a security audit or a guarantee of safety.
SKILL.md text only; scripts, dependencies and runtime behavior not audited.
No configured text patterns matched. Unmatched or concealed behavior can still exist.
Allowed tools declaration: Unknown. Runtime permissions and network behavior: Unknown.
86/100 · Metadata coverage 100% · Model 1.0
Scores summarize observable discovery signals. Popularity and repository activity apply to the whole repository. Unknown runtime safety earns no certification.
Define one row’s work and output contract, provide only required context and choose a bounded batch size.
Test partial failure, duplicate items and aggregation completeness, ensuring that missing rows remain visible and action-only tasks do not repeat consequential operations.
Related by category; compare scope and dependencies before choosing an alternative.
Explore dispatching parallel agents as a productivity & planning workflow from obra/superpowers. Compare its source, maintenance and review signals before choosing it for your agent.
Explore executing plans as a productivity & planning workflow from obra/superpowers. Compare its source, maintenance and review signals before choosing it for your agent.
Explore finishing a development branch as a productivity & planning workflow from obra/superpowers. Compare its source, maintenance and review signals before choosing it for your agent.
Configure a Deep Agents application around its harness and supported extension points.
Choose Deep Agents storage backends according to persistence and filesystem requirements.
Coordinate Deep Agents tasks with explicit delegation, planning and approval boundaries.