Agent Swarm Deployer

Deploy a swarm of parallel sub-agents to process massive, independent data tasks (documents, records, rows, items) and aggregate the results. Use this for data operations; use agent-army for code changes.

Contents

• references/overview.md -- swarm vs army comparison, use cases, architecture diagram
• references/swarm-design.md -- input/output schemas, batch-size and swarm-size formulas, scaling guidelines
• references/agent-brief.md -- agent brief template, data distribution methods, progress tracking
• references/aggregation-recovery.md -- merge logic, completeness validation, retry strategy, error-handling table
• references/output-formats.md -- CSV/JSON/Markdown/individual-file outputs, final summary report
• references/task-configs.md -- ready-made configs for sentiment, lead scoring, content generation, summarization

Workflow

1. Understand the task. Pin down five things before deploying anything: data source, operation per item, output format, output destination, and quality/validation requirements. If any is ambiguous, ask the user first -- a wrong spec wastes all agent compute.

2. Intake and inventory. Glob/Bash to locate and count items. Read 3-5 samples to learn structure. Estimate tokens per item and total. Report an intake summary (source, total count, item format, sample structure, token estimate).

3. Detect input schema and define output schema. Derive the input schema from samples; define the exact output schema the task requires. See references/swarm-design.md.