reskill

Audit agent charters and histories, extract repeated boilerplate into shared skills, and report savings.

2|Updated Apr 21, 2026
One-click install
npx skills add https://github.com/elbruno/md-to-slides --skill reskill-elbruno
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reskill
Source: https://github.com/elbruno/md-to-slides/tree/main/.copilot/skills/reskill
Command: npx skills add https://github.com/elbruno/md-to-slides --skill reskill-elbruno

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Reskill reduces per-agent context bloat by identifying overlapping charter/history content and promoting the repeated patterns into reusable shared skills.

Core Features & Use Cases

  • Audit charters and histories: Measures byte size, finds boilerplate shared across multiple agents, and spots mature repeated learnings.
  • Extract reusable skills: Creates or updates skills in the expected directory structure and applies a standardized skill template.
  • Trim content with guardrails: Enforces charter/history size targets and removes session boilerplate while preserving unique identity and required model/tagline elements.
  • Report savings: Produces a before/after table with totals and percentage reduction so the coordinator can verify impact.

Quick Start

Ask the coordinator to run "team, reskill" when you suspect charter or history bloat and want a team-wide context reduction pass.

Frequently Asked Questions about reskill

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

FAQPage Schema
How do I reduce agent charter and history context bloat in team workflows?

To reduce agent context bloat, audit repeated boilerplate and duplicative learnings across agents, then extract them into reusable shared skills. This trims charters to about 1.5KB and histories to 8KB, yielding a savings table with percentage reduction.

What is the best way to extract reusable skills from duplicated agent history entries?

Extracting reusable skills involves identifying patterns appearing 3 or more times across agent histories and charters, then promoting them into a standardized skill template directory structure. This knowledge reuse process removes session boilerplate while preserving unique identity.

When should I run a team-wide context optimization pass for charter management?

Run a context optimization pass when you suspect charter or history bloat, specifically when collaboration, model, or boundary boilerplate and recurring history entries appear across multiple agents. This periodic maintenance measures byte sizes to enforce target limits.

Does context optimization preserve required model and tagline elements during history hygiene?

Yes, history hygiene and context optimization enforce guardrails that remove session boilerplate while preserving unique identity and required model and tagline elements. This ensures agents maintain their core configuration despite trimming histories to about 8KB.

How do I measure byte size reduction after extracting shared knowledge from agents?

Measure byte size reduction by generating a savings report table that compares before and after totals. This output verifies the impact of extracting shared knowledge, displaying exact byte sizes and the overall percentage reduction achieved by trimming duplicative content.