Skill-Builder: Meta-Skill for Creating Skills

You help create new agent skills that follow established patterns. Your role is to guide skill design, generate scaffolding, and validate completeness.

Core Principle

Skills are diagnostic frameworks with tools, not feature checklists.

A skill diagnoses a problem space, identifies states, and provides interventions. Scripts provide randomization and structure; the LLM provides judgment. Each does what it's best at.

Skill Anatomy

Every skill has these components:

skill-name/
├── SKILL.md           # Diagnostic framework + documentation
├── scripts/           # Deno TypeScript tools
│   └── *.ts
├── data/              # JSON datasets (if needed)
│   └── *.json
└── references/        # Supporting documentation (optional)
    └── *.md

SKILL.md Structure

---
name: skill-name
description: One sentence starting with action verb
license: MIT
metadata:
  author: your-name
  version: "1.0"
  maturity_score: [0-20]                          # Optional
---

# Skill Name: Subtitle

You [role description]. Your role is to [specific function].

## Core Principle
**Bold statement capturing diagnostic essence.**

## The States
### State X1: Name
**Symptoms:** What the user notices
**Key Questions:** What to ask
**Interventions:** What framework/tool to apply

[Repeat for each state]

## Diagnostic Process
1. Step one
2. Step two
...

## Key Questions
### For Category A
- Question?
- Question?

## Anti-Patterns
### The [Problem Name]
**Problem:** Description
**Fix:** Solution

## Available Tools
### script.ts
Description of what it does.
\`\`\`bash
deno run --allow-read scripts/script.ts [args]
\`\`\`

## Example Interaction
**User:** "Problem description"
**Your approach:**
1. Action
2. Action

## What You Do NOT Do
- List of boundaries
- Things the skill never does

## Integration Graph

### Inbound (From Other Skills)
| Source Skill | Source State | Leads to State |
|--------------|--------------|----------------|
| [skill] | [state] | [state] |

### Outbound (To Other Skills)
| This State | Leads to Skill | Target State |
|------------|----------------|--------------|
| [state] | [skill] | [state] |

### Complementary Skills
| Skill | Relationship |
|-------|--------------|
| [skill] | [how they relate] |

Skill Types

Type D: Diagnostic Skills

Purpose: Identify problems, recommend interventions Pattern: States → Questions → Interventions Examples: story-sense, worldbuilding, conlang

Key characteristics:

• Problem states with symptoms/questions
• Cross-references to intervention tools
• "What you do NOT do" section enforces boundaries
• Integration tables mapping to other skills

Type G: Generator Skills

Purpose: Produce structured output from parameters Pattern: Parameters → Generation → Output Examples: Functions in story-sense, phonology in conlang

Key characteristics:

• Input parameters with defaults
• Randomization with optional seeding
• Multiple output formats (human, JSON, brief)
• Quality levels (starter → comprehensive)

Type U: Utility Skills

Purpose: Support other skills, build infrastructure Pattern: Input → Analysis/Transformation → Report Examples: list-builder, skill-builder

Key characteristics:

• Meta-level operation
• Quality metrics and validation
• Templates and scaffolding
• Cross-skill applicability

Type O: Orchestrator Skills

Purpose: Coordinate multiple skills into autonomous workflows Pattern: Input → Multi-Pass Evaluation Loop → Polished Output Examples: chapter-drafter

Key characteristics:

• Invokes multiple sub-skills sequentially
• Iterates until quality thresholds met
• Accumulates context across work units
• Operates autonomously without human checkpoints

Required frontmatter:

metadata:
  orchestrates:           # Sub-skills to coordinate
    - skill-one
    - skill-two
  pass_order:             # Evaluation sequence
    - skill-one
    - skill-two
  pass_weights:           # Weight per skill (sum to 100)
    skill-one: 50
    skill-two: 50
  max_iterations: 3       # Per-pass iteration limit
  global_max_iterations: 50  # Total cap

See skills/fiction/orchestrators/README.md for architectural details.

Skill Maturity Scoring (24 points)

Skills are evaluated on a 24-point scale parallel to the framework 24-point system.

Completeness (11 points)

Check	Points	Criteria
Core Principle	1	Bold statement capturing diagnostic essence
States	2	3-7 states for diagnostic skills (N/A for generator/utility)
State Components	2	Symptoms, Key Questions, Interventions for each state
Diagnostic Process	1	Step-by-step process documented
Anti-Patterns	2	3+ anti-patterns with Problem/Fix structure
Examples	2	2+ worked examples showing skill application
Boundaries	1	"What You Do NOT Do" section

Quality (5 points)

Check	Points	Criteria
Self-Contained	1	Can be used without reading other skills
Type+Mode Declared	1	Required frontmatter fields present
State Naming	1	Consistent state prefix matching skill abbreviation
Integration Map	1	Documents connections to other skills
Tools Documented	1	All scripts have usage documentation

Usability (4 points)

Check	Points	Criteria
Output Persistence	1	Customized (not boilerplate) persistence section
Progressive Disclosure	1	Quick reference section for at-a-glance use
Decision Tree	1	Routing logic for common scenarios
Actionability	1	Clear next steps for each diagnosis

Execution Intelligence (4 points) — NEW

Check	Points	Criteria
Reasoning Requirements	1	Specifies when extended thinking benefits the task
Execution Strategy	1	Documents sequential vs. parallelizable work
Subagent Guidance	1	Identifies when to spawn specialized subagents
Context Management	1	Documents token footprint and optimization strategies

Maturity Levels

Level	Score	Description
Draft	0-8	Missing core elements
Developing	9-14	Functional but incomplete
Stable	15-20	Production-ready
Battle-Tested	21-24	Has case studies + full execution intelligence

Required Metadata

Type (Required)

Every skill must declare its type in frontmatter:

metadata:

Type	Definition	Required Sections
diagnostic	Identifies problems, recommends interventions	States, Diagnostic Process, Anti-Patterns
generator	Produces structured output from parameters	Parameters, Generation Logic, Output Formats
utility	Supports other skills, builds infrastructure	Process, Templates, Validation
orchestrator	Coordinates multiple skills into autonomous workflows	Orchestration Loop, Pass Criteria, Iteration Limits

Mode (Required)

Every skill must declare its mode in frontmatter:

metadata:

Mode	Definition	User Relationship
diagnostic	Identifies problem states and recommends	Agent diagnoses, user decides
assistive	Guides without producing content	Agent asks questions, user creates
collaborative	Works alongside user	Agent produces, user guides
evaluative	Assesses existing work	Agent reviews, user responds
application	Operates in real-time context	Agent runs, user participates
generative	Creates output from parameters	Agent produces, user selects

Compound modes (e.g., diagnostic+generative) are allowed when skills perform multiple functions.

Optional Metadata

metadata:
  maturity_score: 15

State Naming Convention

States must follow a consistent naming pattern:

Convention: {ABBREV}{NUMBER}: {State Name}

Rules:

1. Abbreviation is 1-3 uppercase letters derived from skill name
2. Numbers start at 0 (for "no X exists" states) or 1
3. State names are descriptive, not just numbers
4. Sub-states use decimal notation (4.5, 5.75) when inserting between existing states

Standard Abbreviations:

Skill	Abbreviation	Example
story-sense	SS	State SS1: Concept Without Foundation
dialogue	D	State D1: Identical Voices
conlang	L	State L1: No Language
worldbuilding	W	State W1: Backdrop World
revision how to use skill-builder CursorClaude CodeClineCodexWindsurfGooseGitHub CopilotVS CodeGemini CLIKiloOpencodeKimi CLIRoo ClineAiderContinueZedBolt.newLovablev0Replit AgentSweepSmol DeveloperDevinCavemanAmpAntigravity How to use skill-builder on Cursor AI-first code editor with Composer 1 Prerequisites Before installing skills in Cursor, ensure your development environment meets these requirements: ›Cursor installed and configured on your development machine ›Node.js version 16.0+ with npm package manager (verify with node --version) ›Active project directory or workspace where you want to add skill-builder 2 Execute installation command Execute the skills CLI command in your project's root directory to begin installation: $npx skills add https://github.com/jwynia/agent-skills --skill skill-buildercopy The skills CLI fetches skill-builder from GitHub repository jwynia/agent-skills and configures it for Cursor. 3 Select Cursor when prompted The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor: ◆ Which agents do you want to install to? │ │ ── Universal (.agents/skills) ── always included ──── │ • Amp │ • Antigravity │ • Cline │ • Codex │ ●Cursor(selected) │ • Cursor │ • Windsurf 4 Verify installation Confirm successful installation by checking the skill directory location: .cursor/skills/skill-builder Reload or restart Cursor to activate skill-builder. Access the skill through slash commands (e.g., /skill-builder) or your agent's skill management interface. ⚠ Security & Verification Notice We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use. Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment. Additional Resources ›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills? List & Monetize Your Skill Submit your Claude Code skill and start earning GET_STARTED → Use Cases▌ Task Automation & Efficiency Automate repetitive workflows and reduce manual effort Example Generate reports, summarize documents, draft communications ✓ Save 3-5 hours per week on routine tasks Knowledge Enhancement Learn new skills, understand complex topics, get expert guidance Example Explain concepts, provide examples, suggest learning resources ✓ Accelerate learning and skill development by 2x Quality Improvement Enhance output quality through reviews, suggestions, and refinements Example Review drafts, suggest improvements, catch errors ✓ Improve work quality by 30-40% with less effort Implementation Guide▌ Prerequisites ›Claude Desktop or compatible AI client with skill support ›Clear understanding of task or problem to solve ›Willingness to iterate and refine outputs Time Estimate 15-45 minutes depending on use case complexity Installation Steps 1.Install skill using provided installation command 2.Test with simple use case relevant to your work 3.Evaluate output quality and relevance 4.Iterate on prompts to improve results 5.Integrate into regular workflow if valuable Common Pitfalls ⚠Expecting perfect results without iteration ⚠Not providing enough context in prompts ⚠Using skill for tasks outside its intended scope ⚠Accepting outputs without review and validation Best Practices▌ ✓ Do +Start with clear, specific prompts +Provide relevant context and constraints +Review and refine all outputs before using +Iterate to improve output quality +Document successful prompt patterns ✗ Don't −Don't use without understanding skill limitations −Don't skip validation of outputs −Don't share sensitive information in prompts −Don't expect skill to replace human judgment 💡 Pro Tips ★Be specific about desired format and style ★Ask for multiple options to choose from ★Request explanations to understand reasoning ★Combine AI efficiency with human expertise When to Use This▌ ✓ Use When Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement. ✗ Avoid When Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion. Learning Path▌ 1Familiarize yourself with skill capabilities and limitations 2Start with low-risk, non-critical tasks 3Progress to more complex and valuable use cases 4Build expertise through regular use and experimentation Discussion Product Hunt–style comments (not star reviews) post comment No comments yet — start the thread. general reviews Ratings 4.5★★★★★47 reviews ★★★★★Zaid Tandon· Dec 28, 2024 I recommend skill-builder for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area. ★★★★★Oshnikdeep· Dec 24, 2024 Keeps context tight: skill-builder is the kind of skill you can hand to a new teammate without a long onboarding doc. ★★★★★Amelia Sanchez· Dec 20, 2024 We added skill-builder from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront. ★★★★★Aisha Patel· Dec 4, 2024 Keeps context tight: skill-builder is the kind of skill you can hand to a new teammate without a long onboarding doc. ★★★★★Isabella Huang· Nov 23, 2024 skill-builder has been reliable in day-to-day use. Documentation quality is above average for community skills. ★★★★★Shikha Mishra· Nov 15, 2024 skill-builder has been reliable in day-to-day use. Documentation quality is above average for community skills. ★★★★★Chen Patel· Nov 11, 2024 skill-builder reduced setup friction for our internal harness; good balance of opinion and flexibility. ★★★★★Emma Gonzalez· Oct 14, 2024 Solid pick for teams standardizing on skills: skill-builder is focused, and the summary matches what you get after install. ★★★★★Sakshi Patil· Oct 6, 2024 Solid pick for teams standardizing on skills: skill-builder is focused, and the summary matches what you get after install. ★★★★★Chen Gupta· Oct 2, 2024 Registry listing for skill-builder matched our evaluation — installs cleanly and behaves as described in the markdown. showing 1-10 of 47 prev1 / 5next bookmarkshare