reskill

Extract shared patterns from team charters and histories into reusable skills.

Updated Apr 12, 2026
One-click install
npx skills add https://github.com/barichter/squad --skill reskill-barichter
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reskill
Source: https://github.com/barichter/squad/tree/main/.copilot/skills/reskill
Command: npx skills add https://github.com/barichter/squad --skill reskill-barichter

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

The reskill Skill resolves issues of excessive context and redundancy within team charters and histories, leading to inefficiencies and unnecessary cognitive load.

Core Features & Use Cases

  • Team-wide Charter Optimization: Extracts shared patterns and knowledge from charters, streamlining agent interactions and reducing redundancy.
  • History Slimming: Refines histories by summarizing and promoting recurring patterns to skills, decreasing bloat and enhancing accessibility.
  • Use Case: Consider a team of software developers with charters that repeat common patterns. After using reskill, each agent's charter will be concise, leveraging shared skills to avoid repetitive explanations.

Quick Start

Execute the reskill command to initiate an optimization pass on the current team's charters and histories.

Frequently Asked Questions about reskill

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

FAQPage Schema
How do I reduce context overhead and redundancy in team charters and histories?

You can reduce context overhead by identifying shared patterns within team charters and histories, then extracting them into reusable skills. This optimization process decreases bloat and enhances accessibility without requiring manual refactoring.

How does extracting shared patterns from agent histories improve software development efficiency?

Extracting shared patterns from agent histories improves efficiency by promoting recurring behaviors into standalone skills. This reduces the need for repetitive explanations in charters, streamlining context and lowering cognitive load for collaborative software development teams.

Can I use plain text agent charters with pypdf for history optimization?

Yes, plain text agent charters and histories are the expected inputs for optimization. The process utilizes the pypdf dependency specifically for extracting text from documents, enabling the automated identification and extraction of shared patterns into reusable skills.

What is the best way to slim down bloated agent histories in collaborative software development?

The best way to slim down bloated agent histories is to run an optimization pass that summarizes activities and promotes recurring patterns to skills. This refines histories by removing redundant context while maintaining essential collaborative development knowledge.

Does optimizing team charters require manually identifying redundant patterns across multiple agents?

No, optimizing team charters does not require manual pattern identification. The process automates the identification of shared patterns across charters and extracts them into reusable skills, allowing each agent's charter to remain concise and leverage shared knowledge.