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self-correcting algebraic agent swarm

Free

Three rigorous prompts for intent parsing and task orchestration without role-play

A self-correcting algebraic agent swarm uses three rigorous prompts to parse and recognize user intent, resulting in clear instructions for a controller agent that locks onto your requirements. This approach minimizes role-play while maximizing task clarity and execution, enabling users to get work done efficiently through structured multi-agent coordination.

Who it's for

developersAI researchersmulti-agent system builderstask automation engineers

Pricing · free

checked today
PlanPriceIncludes
Open SourceFreeFree to use · Self-correcting algebraic architecture · Intent parsing system · Multi-agent orchestration

AI-researched pricing — verify on the official site before subscribing.

Use it for

  • — Complex task decomposition
  • — Intent recognition and parsing
  • — Multi-agent coordination
  • — Prompt engineering optimization
  • — Structured workflow automation
  • — AI system orchestration

Get the most out of it

  1. 01Understand the three-prompt system for intent parsing to maximize controller agent effectiveness
  2. 02Leverage the algebraic structure to create deterministic and reproducible agent behavior
  3. 03Use the self-correcting mechanism to iteratively improve agent task understanding across sessions
  4. 04Combine with LLM frameworks for enhanced reasoning capabilities in swarm coordination
  5. 05Test prompts with diverse user inputs to validate intent recognition accuracy

In the news

  • Show HN: A self-correcting algebraic agent swarmGithub.com · Jul 19, 2026
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