A proper parallel dispatch primitive for Claude. You build a table from files, globs, or records, then fan out work across rows with templated instructions and structured output. Each row is one unit of work. The framework handles batching automatically and merges results back into columns. Good for classification, extraction, or review tasks over dozens to hundreds of items. You can chain multiple passes to accumulate columns, filter to retry failures, then aggregate with plain JavaScript. The key insight is knowing when to use direct model calls versus full subagent loops. Most tasks don't need tools or iteration, and the default path is much faster and cheaper. For large files you'll split parsing and dispatch across eval blocks to avoid truncation.
npx -y skills add langchain-ai/langchain-skills --skill swarm --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
sickn33/antigravity-awesome-skills
moizibnyousaf/ai-agent-skills
github/awesome-copilot