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synthesize

Synthesize SWARM run data into structured notes with claim analysis.

39|4|Updated Feb 3, 2026
Search Tags:#research automation#data organization#note generation#SWARM#experiment synthesis
One-click install
npx skills add https://github.com/swarm-ai-research/swarm --skill synthesize-swarm-ai-research
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: synthesize
Source: https://github.com/swarm-ai-research/swarm/tree/main/.skills/synthesize
Command: npx skills add https://github.com/swarm-ai-research/swarm --skill synthesize-swarm-ai-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the synthesis of SWARM run data into comprehensive notes, facilitating the organization and analysis of experimental results.

Core Features & Use Cases

  • Run Synthesis: Converts SWARM run data into structured notes.
  • Claim Analysis: Checks for new evidence in existing claims and suggests updates.
  • Index Reconstruction: Updates the experiment index with new and updated notes.
  • Batch Processing: Handles multiple runs with a single command.
  • Use Case: Use this Skill after running a SWARM simulation to automatically generate and update notes, keeping track of experimental outcomes and claims in one place.

Quick Start

Run the synthesis process for a specific run using the command '/synthesize [run_id]'.

Frequently Asked Questions about synthesize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate SWARM run synthesis and note generation?▼

You can automate SWARM run synthesis by executing the synthesis process with a specific run ID. This converts experimental run data into structured notes, performing claim analysis and updating the experiment index automatically.

What does claim analysis do during experiment synthesis?▼

Claim analysis during experiment synthesis checks for new evidence in existing claims and suggests updates. This ensures your structured notes accurately reflect the latest experimental outcomes and tracked data.

Can I process multiple SWARM runs at the same time?▼

Yes, you can process multiple SWARM runs at the same time using batch processing. This handles multiple runs with a single command, automatically generating and updating notes for all specified experimental results.

Do I need a specific environment to run SWARM experiment synthesis?▼

Yes, SWARM experiment synthesis requires the SWARM environment and Python scripts for execution. You must have this framework set up to automate the conversion of run data into structured notes.

How does index reconstruction work for experimental notes?▼

Index reconstruction for experimental notes works by updating the experiment index with new and updated notes. This maintains an organized, centralized record of all synthesized experimental outcomes and claims.

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