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ClaudeWave
Skill2.3k repo starsupdated 24d ago

claude-skills

Claude Skills is a meta-skill for extracting domain material (documentation, APIs, code, specifications) into reusable, maintainable Skill assets organized as SKILL.md entry points with supporting references, scripts, and templates. Use this when creating new Skills from scratch, refactoring existing Skills for clarity and reliability, designing activation patterns with clear boundaries, or splitting large content into navigable reference structures with quality gates.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills /tmp/claude-skills && cp -r /tmp/claude-skills/bundled/skills/claude-skills ~/.claude/skills/claude-skills
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Claude Skills Meta-Skill

Turn scattered domain material into a Skill that is reusable, maintainable, and reliably activatable:
- `SKILL.md` as the entrypoint (triggers, constraints, patterns, examples)
- `references/` for long-form evidence and navigation
- optional `scripts/` and `assets/` for scaffolding and templates

## When to Use This Skill

Trigger this meta-skill when you need to:
- Create a new Skill from scratch from docs/specs/repos
- Refactor an existing Skill (too long, unclear, inconsistent, misfires)
- Design reliable activation (frontmatter + triggers + boundaries)
- Extract a clean Quick Reference from large material
- Split long content into navigable `references/`
- Add a quality gate and a validator

## Not For / Boundaries

This meta-skill is NOT:
- A domain Skill by itself (it builds domain Skills)
- A license to invent external facts (if the material does not prove it, say so and add a verification path)
- A substitute for required inputs (if inputs are missing, ask 1-3 questions before proceeding)

## Quick Reference

### Deliverables (What You Must Produce)

Your output MUST include:
1. A concrete directory layout (typically `skills/<skill-name>/`)
2. An actionable `SKILL.md` with decidable triggers, boundaries, and reproducible examples
3. Long-form docs moved to `references/` with a `references/index.md`
4. A pre-delivery checklist (Quality Gate)

### Recommended Layout (Minimal -> Full)

```
skill-name/
|-- SKILL.md              # Required: entrypoint with YAML frontmatter
|-- references/           # Optional: long-form docs/evidence/index
|   `-- index.md          # Recommended: navigation index
|-- scripts/              # Optional: helpers/automation
`-- assets/               # Optional: templates/configs/static assets
```

The truly minimal version is just `SKILL.md` (you can add `references/` later).

### YAML Frontmatter (Required)

```yaml
---
name: skill-name
description: "What it does + when to use (activation triggers)."
---
```

Frontmatter rules:
- `name` MUST match `^[a-z][a-z0-9-]*$` and SHOULD match the directory name
- `description` MUST be decidable (not "helps with X") and include concrete trigger keywords

### Minimal `SKILL.md` Skeleton (Copy/Paste)

```markdown
---
name: my-skill
description: "[Domain] capability: includes [capability 1], [capability 2]. Use when [decidable triggers]."
---

# my-skill Skill

One sentence that states the boundary and the deliverable.

## When to Use This Skill

Trigger when any of these applies:
- [Trigger 1: concrete task/keyword]
- [Trigger 2]
- [Trigger 3]

## Not For / Boundaries

- What this skill will not do (prevents misfires and over-promising)
- Required inputs; ask 1-3 questions if missing

## Quick Reference

### Common Patterns

**Pattern 1:** one-line explanation
```text
[command/snippet you can paste and run]
```

## Examples

### Example 1
- Input:
- Steps:
- Expected output / acceptance:

### Example 2

### Example 3

## References

- `references/index.md`: navigation
- `references/...`: long-form docs split by topic

## Maintenance

- Sources: docs/repos/specs (do not invent)
- Last updated: YYYY-MM-DD
- Known limits: what is explicitly out of scope
```

### Authoring Rules (Non-negotiable)

1. Quick Reference is for short, directly usable patterns
   - Keep it <= 20 patterns when possible.
   - Anything that needs paragraphs of explanation goes to `references/`.
2. Activation must be decidable
   - Frontmatter `description` should say "what + when" with concrete keywords.
   - "When to Use" must list specific tasks/inputs/goals, not vague help text.
   - "Not For / Boundaries" is mandatory for reliability.
3. No bluffing on external details
   - If the material does not prove it, say so and include a verification path.

### Workflow (Material -> Skill)

Do not skip steps:
1. Scope: write MUST/SHOULD/NEVER (three sentences total is fine)
2. Extract patterns: pick 10-20 high-frequency patterns (commands/snippets/flows)
3. Add examples: >= 3 end-to-end examples (input -> steps -> acceptance)
4. Define boundaries: what is out-of-scope + required inputs
5. Split references: move long text into `references/` + write `references/index.md`
6. Apply the gate: run the checklist and the validator

### Quality Gate (Pre-delivery Checklist)

Minimum checks (see `references/quality-checklist.md` for the full version):
1. `name` matches `^[a-z][a-z0-9-]*$` and matches the directory name
2. `description` states "what + when" with concrete trigger keywords
3. Has "When to Use This Skill" with decidable triggers
4. Has "Not For / Boundaries" to reduce misfires
5. Quick Reference is <= 20 patterns and each is directly usable
6. Has >= 3 reproducible examples
7. Long content is in `references/` and `references/index.md` is navigable
8. Uncertain claims include a verification path (no bluffing)
9. Reads like an operator's manual, not a documentation dump

Validate locally:

```bash
# From repo root (basic validation)
./skills/claude-skills/scripts/validate-skill.sh skills/<skill-name>

# From repo root (strict validation)
./skills/claude-skills/scripts/validate-skill.sh skills/<skill-name> --strict

# From skills/claude-skills/ (basic validation)
./scripts/validate-skill.sh ../<skill-name>

# From skills/claude-skills/ (strict validation)
./scripts/validate-skill.sh ../<skill-name> --strict
```

### Tools & Templates

Generate a new Skill skeleton:

```bash
# From repo root (generate into ./skills/)
./skills/claude-skills/scripts/create-skill.sh my-skill --full --output skills

# From skills/claude-skills/ (generate into ../ i.e. ./skills/)
./scripts/create-skill.sh my-skill --full --output ..

# Minimal skeleton
./skills/claude-skills/scripts/create-skill.sh my-skill --minimal --output skills
```

Templates:
- `assets/template-minimal.md`
- `assets/template-complete.md`

## Examples

### Example 1: Create a Skill from Docs

- Input: an official doc/spec + 2-3 real code samples + common failure modes
- Step
vibeSkill

Vibe Code Orchestrator (VCO) is a governed runtime entry that freezes requirements, plans XL-first execution, and enforces verification and phase cleanup.

skill-creatorSkill

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.

skill-installerSkill

Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).

LQF_Machine_Learning_Expert_GuideSkill

|

adaptyvSkill

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

aeonSkill

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

algorithmic-artSkill

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

alpha-vantageSkill

Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.