reskill
Team-wide charter and history optimization through skill extraction
Best use case
reskill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Team-wide charter and history optimization through skill extraction
Teams using reskill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/reskill/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How reskill Compares
| Feature / Agent | reskill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Team-wide charter and history optimization through skill extraction
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
## Context
When the coordinator hears "team, reskill" (or similar: "optimize context", "slim down charters"), trigger a team-wide optimization pass. The goal: reduce per-agent context consumption by extracting shared patterns from charters and histories into reusable skills.
This is a periodic maintenance activity. Run whenever charter/history bloat is suspected.
## Process
### Step 1: Audit
Read all agent charters and histories. Measure byte sizes. Identify:
- **Boilerplate** — sections repeated across ≥3 charters with <10% variation (collaboration, model, boundaries template)
- **Shared knowledge** — domain knowledge duplicated in 2+ charters (incident postmortems, technical patterns)
- **Mature learnings** — history entries appearing 3+ times across agents that should be promoted to skills
### Step 2: Extract
For each identified pattern:
1. Create or update a skill at `.copilot/skills/{skill-name}/SKILL.md`
2. Follow the skill template format (frontmatter + Context + Patterns + Examples + Anti-Patterns)
3. Set confidence: low (first observation), medium (2+ agents), high (team-wide)
### Step 3: Trim
**Charters** — target ≤1.5KB per agent:
- Remove Collaboration section entirely (spawn prompt + agent-collaboration skill covers it)
- Remove Voice section (tagline blockquote at top of charter already captures it)
- Trim Model section to single line: `Preferred: {model}`
- Remove "When I'm unsure" boilerplate from Boundaries
- Remove domain knowledge now covered by a skill — add skill reference comment if helpful
- Keep: Identity, What I Own, unique How I Work patterns, Boundaries (domain list only)
**Histories** — target ≤8KB per agent:
- Apply history-hygiene skill to any history >12KB
- Promote recurring patterns (3+ occurrences across agents) to skills
- Summarize old entries into `## Core Context` section
- Remove session-specific metadata (dates, branch names, requester names)
### Step 4: Report
Output a savings table:
| Agent | Charter Before | Charter After | History Before | History After | Saved |
|-------|---------------|---------------|----------------|---------------|-------|
Include totals and percentage reduction.
## Patterns
### Minimal Charter Template (target format after reskill)
```
# {Name} — {Role}
> {Tagline — one sentence capturing voice and philosophy}
## Identity
- **Name:** {Name}
- **Role:** {Role}
- **Expertise:** {comma-separated list}
## What I Own
- {bullet list of owned artifacts/domains}
## How I Work
- {unique patterns and principles — NOT boilerplate}
## Boundaries
**I handle:** {domain list}
**I don't handle:** {explicit exclusions}
## Model
Preferred: {model}
```
### Skill Extraction Threshold
- **1 charter** → leave in charter (unique to that agent)
- **2 charters** → consider extracting if >500 bytes of overlap
- **3+ charters** → always extract to a shared skill
## Anti-Patterns
- Don't delete unique per-agent identity or domain-specific knowledge
- Don't create skills for content only one agent uses
- Don't merge unrelated patterns into a single mega-skill
- Don't remove Model preference line (coordinator needs it for model selection)
- Don't touch `.squad/decisions.md` during reskill
- Don't remove the tagline blockquote — it's the charter's soul in one lineRelated Skills
My Skill
No description provided.
rework-rate
Measure and interpret PR rework rate — the emerging 5th DORA metric
project-conventions
Core conventions and patterns for this codebase
tiered-memory
Three-tier agent memory model (hot/cold/wiki) for 20-55% context reduction per spawn
test-discipline
Update tests when changing APIs — no exceptions
Skill: Retro Enforcement
## Purpose
reflect
Learning capture system that extracts HIGH/MED/LOW confidence patterns from conversations to prevent repeating mistakes. Use after user corrections ("no", "wrong"), praise ("perfect", "exactly"), or when discovering edge cases. Complements .squad/agents/{agent}/history.md and .squad/decisions.md.
notification-routing
Route agent notifications to specific channels by type — prevent alert fatigue from single-channel flooding
iterative-retrieval
Max-3-cycle protocol for agent sub-tasks with WHY context and coordinator validation. Use when spawning sub-agents to complete scoped work.
error-recovery
Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.
docs-standards
Microsoft Style Guide + Squad-specific documentation patterns
{skill-name}
{what this skill teaches agents}