skill-author

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Research a domain by reading provided reference material, then produce a reusable SKILL.md that teaches any agent how to work in that domain.

breadboard-ai By breadboard-ai schedule Updated 3/7/2026

name: Skill Author description: Research a domain by reading provided reference material, then produce a reusable SKILL.md that teaches any agent how to work in that domain.

Skill Author

You are now acquiring the meta-skill of writing skills. After reading this document, you will know how to produce high-quality SKILL.md files that teach other agents new capabilities.

What You're Doing

Given a domain (implied by the user's objective), you will:

  1. Read reference material from /mnt/references/ for domain grounding
  2. Synthesize that material into a reusable skill
  3. Produce a complete SKILL.md file

Critical Principle: Skills Are Frameworks, Not Instances

A skill must be reusable across many requests in its domain. It captures the judgment and expertise of the domain — not the specifics of any one request.

BAD: A recipe skill that includes carbonara-specific instructions. GOOD: A recipe skill that teaches how to structure ANY recipe with proper timing, technique sequencing, and ingredient proportions.

The test: if your skill only works for the first request that triggered it, you've written an answer, not a skill. Rewrite it.

Critical Principle: Name the Domain, Not the Application

The skill name must describe the domain of knowledge, not the first thing you're asked to build. The domain is the subject-matter expertise; applications are what you build WITH that expertise.

BAD: "Competitive Wobbling Scorecard Generation" — too narrow, only works for scorecards. GOOD: "Competitive Wobbling" — works for scorecards, training guides, match commentary, athlete profiles, etc.

BAD: "Italian Pasta Recipe Creation" — fuses a cuisine with a format. GOOD: "Culinary Arts" — works for any recipe, any cuisine, any format.

Where Expertise Comes From

  • Reference material (/mnt/references/): domain-specific documents, data, rules, and standards that ground the skill in real knowledge. Always check for and read reference material first.
  • Your parametric knowledge: general knowledge from training.

When reference material exists, it is the primary source of truth. Your parametric knowledge fills in general framing and structure, but domain- specific facts MUST come from the references.

SKILL.md Format

---
name: [Human-readable skill name]
description: [1-2 sentence description of what this skill enables]
---

# [Skill Name]

[Opening paragraph: "You are now acquiring the skill of..."]

## What You're Building

[Describe the RANGE of artifacts this skill enables — not just one type. The
skill should support multiple applications within the domain.]

## Memory Integration

Check `/mnt/memory.md` for user preferences before generating.

## Domain Expertise

[The reusable judgment framework synthesized from references. Rules, heuristics,
quality criteria, common mistakes, tradeoffs. This is the CORE of the skill —
the expertise that makes output substantive rather than shallow.]

## Output Format

[Exact file names, structure, and how to save them]

Your Process

  1. Read ALL reference material in /mnt/references/
  2. Identify the reusable principles, rules, and judgment frameworks
  3. Separate domain expertise (reusable) from instance specifics (discard)
  4. Write the complete SKILL.md
  5. Save it using system_write_file as SKILL.md

Output

Save the skill as SKILL.md and call system_objective_fulfilled with a summary of what the skill teaches.

Install via CLI
npx skills add https://github.com/breadboard-ai/breadboard --skill skill-author
Repository Details
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article Path SKILL.md
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