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learning-systems

Learn from task outcomes to improve swarm decomposition quality.

Updated Jan 14, 2026
One-click install
npx skills add https://github.com/primeinc/swarm --skill learning-systems-primeinc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: learning-systems
Source: https://github.com/primeinc/swarm/tree/main/packages/opencode-swarm-plugin/global-skills/learning-systems
Command: npx skills add https://github.com/primeinc/swarm --skill learning-systems-primeinc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Learning Systems Skill enables the Swarm plugin to learn from task outcomes, automatically adjusting decomposition quality over time to improve efficiency and reliability.

Core Features & Use Cases

  • Implicit Feedback Scoring: converts task outcomes (duration, errors, retries) into quantitative signals without requiring explicit user input.
  • Confidence Decay & Pattern Maturity: applies time-based decay to prior learnings and progresses patterns from candidate to proven, guiding future task planning.
  • Use Case: when decomposing a complex feature, the system records outcomes and adapts prompts to favor successful strategies for similar tasks.

Quick Start

Provide a task to decompose and execute, then review how the system records outcomes and updates pattern maturity.

Frequently Asked Questions about learning-systems

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

FAQPage Schema
How do I improve task decomposition quality using past project outcomes?▼

Task decomposition quality improves when the system records task outcomes like duration and errors, converting them into quantitative signals to guide future swarm planning decisions.

What is implicit feedback scoring for swarm planning?▼

Implicit feedback scoring automatically converts task execution metrics such as duration, errors, and retries into quantitative signals without requiring explicit user input.

How does confidence decay affect learned task patterns?▼

Confidence decay applies time-based degradation to prior learnings, ensuring outdated task patterns lose influence while proven mature patterns continue guiding future planning.

Can I automate pattern maturity tracking across iterative projects?▼

Pattern maturity tracking progresses task strategies from candidate to proven status automatically across iterative projects, adapting prompts to favor successful decomposition approaches.

Do I need explicit user feedback to adjust swarm decomposition strategies?▼

No explicit user feedback is needed; the system relies on implicit feedback from observed task outcomes to automatically adjust decomposition quality and pattern confidence.

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