Anthropic Multi-Agent Research
A suggested workflow where a main agent coordinates parallel search sub-agents, followed by citation processing. Task: Suggested implementation: A lead agent plans research and spawns parallel sub-agents to search specific angles. Each worker returns compressed summaries, and a final citation agent matches claims to sources. Human role: Define the research scope, approve the plan, and verify the final report's accuracy.; tools: Tool described in the source. Human role: Not stated in the source; limitations: Prerequisites: Access to multiple LLM instances and a search API. Constraints: High token consumption (approx. 15x normal chat) makes it suitable only for complex queries. Integration uncertainty: Requires robust memory management for the lead agent to survive long runs. Human approval: Mandatory for final report publication..
Tools
Tool described in the source
Published on Agent Work Atlas:
Overview
A suggested workflow where a main agent coordinates parallel search sub-agents, followed by citation processing.
Workflow
Suggested implementation: A lead agent plans research and spawns parallel sub-agents to search specific angles. Each worker returns compressed summaries, and a final citation agent matches claims to sources. Human role: Define the research scope, approve the plan, and verify the final report's accuracy.
Reported result
Actual outcomes are not verified in this source. The text cites an internal Anthropic evaluation where this multi-agent setup beat a single agent by 90.2%, but used 15x more tokens. No external deployment metrics or failure rates are provided. Acceptance check: Compare token cost and citation accuracy against a single-agent baseline on a sample query.
Human role
Not stated in the source
Limitations
Prerequisites: Access to multiple LLM instances and a search API. Constraints: High token consumption (approx. 15x normal chat) makes it suitable only for complex queries. Integration uncertainty: Requires robust memory management for the lead agent to survive long runs. Human approval: Mandatory for final report publication.
Try it
Act as a research coordinator. I need a comprehensive report on [replaceable topic, e.g., 'impact of AI on supply chain logistics in 2024']. Steps: 1. Draft a research plan with 3-5 distinct sub-questions. Wait for my confirmation. 2. Once approved, spawn parallel search tasks for each sub-question. Use [replaceable search tool/API] to find sources. 3. Compress findings into key points with source URLs. 4. Synthesize a final report where every claim is cited. 5. Output format: Markdown with sections for Executive Summary, Detailed Findings, and References. Safeguards: Do not publish or send the report externally. Present it here for my review. If a source is inaccessible, note it explicitly. Measure success by citation density (at least 1 citation per paragraph) and relevance to the original topic. If the topic is too broad, ask clarifying questions before starting.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.