Strict guidelines for authoring High-Density Agent Skills. Maximize information density while minimizing token consumption through progressive disclosure and strategic content organization.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionskill-creatorExecute the skills CLI command in your project's root directory to begin installation:
Fetches skill-creator from hoangnguyen0403/agent-skills-standard and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate skill-creator. Access via /skill-creator in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Strict guidelines for authoring High-Density Agent Skills. Maximize information density while minimizing token consumption through progressive disclosure and strategic content organization.
Every word costs tokens. Design skills for maximum information/token ratio:
references/ folderLevel 1: Metadata (100 words) → Always loaded
Level 2: SKILL.md Body (100 lines) → When triggered
Level 3: References/Scripts/Assets → As needed
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
Imperative Compression: Start with verbs. No "Please/You should".
Token Economy: Maximize info/token ratio.
Progressive Disclosure: Essential info first, details on-demand.
Context-Aware Design: Different agents have different limits.
Required sections in SKILL.md:
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]
---
Priority: P0 (Critical), P1 (Standard), or P2 (Optional)
Structure: ASCII tree of expected file layout
Guidelines: Bullet points of "Do this" (imperative)
Anti-Patterns: Bullet points of "Don't do this"
Reference Links: Links to references/ files (lazy loading)
| 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/ |
When to use: Deterministic, repeated tasks Benefits: Never loaded into context, executed directly Examples: Code generators, formatters, validators
When to use: Detailed examples, API docs, complex patterns Benefits: Loaded only when needed, keeps SKILL.md lean Examples: Implementation patterns, error handling guides
When to use: Boilerplate files, images, configs Benefits: Never loaded, copied to output as-needed Examples: Project templates, config files, icons
Before finalizing, verify:
description after ## Priority**Bold**: \More Bold`` - causes visual noiseFormat: **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.
Extract to references/ when:
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
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
Solid pick for teams standardizing on skills: skill-creator is focused, and the summary matches what you get after install.
skill-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added skill-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
skill-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for skill-creator matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in skill-creator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
skill-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
skill-creator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added skill-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
skill-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.
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