skill-creator

hoangnguyen0403/agent-skills-standard · updated Apr 8, 2026

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$npx skills add https://github.com/hoangnguyen0403/agent-skills-standard --skill skill-creator
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summary

Strict guidelines for authoring High-Density Agent Skills. Maximize information density while minimizing token consumption through progressive disclosure and strategic content organization.

skill.md

Agent Skill Creator Standard

Priority: P0 (CRITICAL)

Strict guidelines for authoring High-Density Agent Skills. Maximize information density while minimizing token consumption through progressive disclosure and strategic content organization.

Core Principles

Token Economy First

Every word costs tokens. Design skills for maximum information/token ratio:

  • Progressive Loading: Load only essential content initially
  • Lazy References: Move detailed examples to references/ folder
  • Imperative Compression: Use verbs, abbreviations, bullet points
  • Context Window Awareness: Design for 4k-32k token limits across agents

Three-Level Loading System

Level 1: Metadata (100 words) → Always loaded
Level 2: SKILL.md Body (100 lines) → When triggered
Level 3: References/Scripts/Assets → As needed

Directory Structure

skills/
└── {category}/                     # e.g., "flutter" (lowercase)
    └── {skill-name}/               # e.g., "bloc-state-management" (kebab-case)
        ├── SKILL.md                # Core Logic (High Density, <100 lines)
        ├── scripts/                # Executable code (Deterministic tasks)
        │   └── automation.py
        ├── references/             # Heavy Examples (Lazy loaded)
        │   ├── patterns.md
        │   └── examples.md
        └── assets/                 # Output templates (Never loaded)
            └── template.json

Writing Rules (Token-Optimized)

  1. Imperative Compression: Start with verbs. No "Please/You should".

    • Waste: "You should use BLoC for state management." (8 words)
    • Efficient: "Use BLoC for state management." (5 words)
  2. Token Economy: Maximize info/token ratio.

    • Skip articles ("the", "a") if readable
    • Use standard abbreviations (cfg, param, impl)
    • Bullet points > paragraphs (3x density)
  3. Progressive Disclosure: Essential info first, details on-demand.

    • Core workflow in SKILL.md
    • Complex examples in references/
    • Templates/assets never loaded
  4. Context-Aware Design: Different agents have different limits.

    • Cursor: ~100k tokens
    • Claude: ~200k tokens
    • Windsurf: ~32k tokens

Content Sections (Token-Budgeted)

Required sections in SKILL.md:

  1. Frontmatter (Mandatory): Metadata for triggering (100 words max)

    ---
    name: Skill Name
    description: What it does + when to use it (triggers activation)
    metadata:
      labels: [tag1, tag2]
      triggers:
        files: ['**/*.ext']
        keywords: [term1, term2]
    ---
    
  2. Priority: P0 (Critical), P1 (Standard), or P2 (Optional)

  3. Structure: ASCII tree of expected file layout

  4. Guidelines: Bullet points of "Do this" (imperative)

  5. Anti-Patterns: Bullet points of "Don't do this"

  6. Reference Links: Links to references/ files (lazy loading)

Size Limits (Strict)

Element Limit Action if Exceeded
SKILL.md total 100 lines Extract to references/
Inline code block 10 lines Move to references/
Anti-pattern item 15 words Compress to imperative
Description after Priority 0 lines Remove (use frontmatter)
Tables 8 rows Extract to references/
Explanatory sections 10 lines Extract to references/

Resource Organization (Token-Saving)

scripts/ - Executable Code

When to use: Deterministic, repeated tasks Benefits: Never loaded into context, executed directly Examples: Code generators, formatters, validators

references/ - Documentation

When to use: Detailed examples, API docs, complex patterns Benefits: Loaded only when needed, keeps SKILL.md lean Examples: Implementation patterns, error handling guides

assets/ - Output Templates

When to use: Boilerplate files, images, configs Benefits: Never loaded, copied to output as-needed Examples: Project templates, config files, icons

Skill Creation Lifecycle

Phase 1: Understanding (Token Audit)

  1. Define concrete use cases
  2. Identify repetitive patterns
  3. Calculate token budget per agent

Phase 2: Planning (Resource Strategy)

  1. Core workflow → SKILL.md
  2. Complex examples → references/
  3. Repeated code → scripts/
  4. Templates → assets/

Phase 3: Implementation (Compression)

  1. Write imperative guidelines
  2. Compress examples to essentials
  3. Test context window fit

Phase 4: Validation (Token Testing)

  1. Verify loading efficiency
  2. Test across different agents
  3. Measure token consumption

Validation Checklist

Before finalizing, verify:

  • SKILL.md ≤100 lines (ideal: 40-60)
  • No inline code >10 lines
  • No repeated frontmatter content
  • Anti-patterns use strict format (see below)
  • Complex examples in references/
  • Tables >8 rows moved to references/
  • No description redundancy after Priority

Anti-Patterns (Token Wasters)

  • Verbose Explanations: "This is important because..." → Delete
  • Redundant Context: Same info in multiple places
  • Large Inline Code: Move code >10 lines to references/
  • Conversational Style: "Let's see how to..." → "Do this:"
  • Over-Engineering: Complex structure for simple skills
  • Redundant Descriptions: Do not repeat frontmatter description after ## Priority
  • Oversized Skills: SKILL.md >100 lines → Extract to references/
  • Nested Formatting: Avoid **Bold**: \More Bold`` - causes visual noise
  • Verbose Anti-Patterns: See strict format below

Anti-Pattern Format (Strict)

Format: **No X**: Do Y[, not Z]. [Optional context, max 15 words total]

Examples:

❌ Verbose (24 words):

- **No Manual Emit**: `**Avoid .then()**: Do not call emit() inside Future.then; always use await or emit.forEach.`

✅ Compressed (11 words):

- **No .then()**: Use `await` or `emit.forEach()` to emit states.

❌ Verbose (18 words):

- **No UI Logic**: `**Logic in Builder**: Do not perform calculations or data formatting inside BlocBuilder.`

✅ Compressed (9 words):

- **No Logic in Builder**: Perform calculations in BLoC, not UI.

Progressive Disclosure Checklist

Extract to references/ when:

  • Code examples >10 lines
  • Tables >8 rows
  • Explanatory sections >10 lines
  • Multiple code variants/alternatives
  • Detailed performance benchmarks
  • Step-by-step tutorials

Reference & Examples

Use the enhanced template below to generate new skills: references/TEMPLATE.md

For comprehensive lifecycle guidance: references/lifecycle.md

For resource organization patterns: references/resource-organization.md

how to use skill-creator

How to use skill-creator 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-creator
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/hoangnguyen0403/agent-skills-standard --skill skill-creator

The skills CLI fetches skill-creator from GitHub repository hoangnguyen0403/agent-skills-standard 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-creator

Reload or restart Cursor to activate skill-creator. Access the skill through slash commands (e.g., /skill-creator) 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.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.757 reviews
  • Shikha Mishra· Dec 28, 2024

    Solid pick for teams standardizing on skills: skill-creator is focused, and the summary matches what you get after install.

  • Min Reddy· Dec 28, 2024

    skill-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Liam Johnson· Dec 20, 2024

    We added skill-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Amina Gill· Dec 12, 2024

    skill-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Zaid Thompson· Dec 8, 2024

    Registry listing for skill-creator matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ganesh Mohane· Dec 4, 2024

    Useful defaults in skill-creator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aisha Gupta· Nov 27, 2024

    skill-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakshi Patil· Nov 23, 2024

    skill-creator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Xiao Singh· Nov 19, 2024

    We added skill-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Aditi Taylor· Nov 11, 2024

    skill-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.

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