your-skill-slug

name	Skill Creator
description	Create new AI agent skills from scratch, improve existing skills, and optimize skill descriptions for better triggering accuracy. Use when users want to build a skill, write a SKILL.md, write handler code, evaluate skill quality, optimize skill metadata, or generate test cases. Covers the full skill development lifecycle from intent capture through deployment and iteration. Even if the user just says "I have an idea for a skill" or "help me package this as a skill", this is the right tool.
allowed-tools	["Read","Write","Bash(curl *)"]
metadata	{"requires":{"env":["CLAW0X_API_KEY"]},"version":"1.0.0","source":"https://github.com/anthropics/skills/tree/main/skills/skill-creator","license":"MIT"}

Skill Creator

Build production-ready AI agent skills for the Claw0x platform. From a one-sentence idea to a deployed, billed, security-scanned skill — this guide and API cover the full lifecycle.

Free to use. This skill costs nothing. Sign up at claw0x.com, create an API key, and start calling. No credit card required.

Quick Reference

When This Happens	Use This Action	What You Get
"I have an idea for a skill"	create	Complete SKILL.md + handler skeleton
"This skill doc needs work"	improve	Refined SKILL.md with before/after scores
"Is this skill ready to deploy?"	evaluate	Quality scores across 4 dimensions
"Agents aren't triggering my skill"	optimize-description	Rewritten description for better discovery
"I need test cases"	generate-tests	Should-trigger and should-not-trigger prompts

---

5-Minute Quickstart

Step 1: Get API Key (30 seconds)

Sign up at claw0x.com → Dashboard → Create API Key

Step 2: Create Your First Skill (2 minutes)

curl -X POST https://api.claw0x.com/v1/call \
  -H "Authorization: Bearer ck_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "skill": "skill-creator",
    "input": {
      "action": "create",
      "intent": "I want a skill that validates email addresses"
    }
  }'

Step 3: Get Complete SKILL.md + Handler (instant)

{
  "skill_md": "---\nname: email-validator\ndescription: Validate email addresses...",
  "handler_skeleton": "import { VercelRequest, VercelResponse }...",
  "evaluation": {
    "completeness": 0.85,
    "clarity": 0.9
  }
}

Step 4: Deploy and Test

Copy the generated files, deploy to Vercel, and you're live!

Done. You just created a production-ready skill in 5 minutes.

How Claw0x Skills Work — Architecture in 60 Seconds

Every skill on Claw0x follows the same pattern:

Agent → POST https://api.claw0x.com/v1/call → Gateway → skill backend → Response

1. An AI agent (or human) calls the Gateway with a Claw0x API key
2. The Gateway authenticates, routes to the skill backend, and handles billing
3. The skill backend runs the handler and returns a result
4. Only 2xx responses are billed. 4xx/5xx = free. Zero risk for the caller.

The caller never needs upstream API keys. One key, one endpoint, zero config.

Skill Directory Structure

Every skill lives in a standard directory:

skills/{slug}/
├── SKILL.md       # Agent discovery entry point (required)
└── handler.ts     # Serverless function logic (required)

• SKILL.md is what agents read to decide whether to invoke the skill
• handler.ts is the actual execution logic, deployed as a Vercel serverless function

Two Types of Skills

API Wrapper Skills

Wrap an external API behind the Claw0x Gateway. The handler calls the upstream API using a server-side key that the caller never sees. Pure Logic Skills have no external API calls. All processing happens inside the handler. Cheaper (50% discount) and get free-tier allocation. Example: sentiment does regex + heuristic analysis locally. skill-creator (this skill) is also pure logic.

Stage 1: Capture Intent Gemini for AI text rewriting.

Pure Logic Skills

No external API calls. All processing happens inside the handler. These are cheaper (50% discount) and get free-tier allocation.

Example: sentiment does regex + heuristic analysis locally. skill-creator (this skill) is also pure logic.

Stage 1: Capture Intent

Before writing any code, answer these six questions. They determine everything downstream.

1. What does this skill do in one sentence? A concrete action. "Extracts structured data from PDF invoices and returns JSON" — not "AI-powered document intelligence."

2. When should an agent invoke this skill? List 3-5 specific trigger phrases. These become the foundation of your description field.

3. What inputs does it need? Every field: name, type, required/optional, constraints.

4. What does the output look like? The exact JSON shape including _meta with skill, version, and latency_ms.

5. Does it need an upstream API? Yes → API Wrapper. No → Pure Logic (cheaper, simpler).

6. What can go wrong? List failure modes. Each needs a specific error code and message.

Why This Matters

A skill with a vague intent produces a vague description, which produces poor triggering, which means agents never invoke it. The six questions force precision upfront.

Stage 2: Write the SKILL.md

The SKILL.md is the single most important file. It's what agents read to decide whether to use your skill.

Frontmatter Rules

---
name: your-skill-slug
description: >
  [Action verb] [what it does]. Use when [trigger phrase 1],
  [trigger phrase 2], or [trigger phrase 3]. [What it handles/returns].
  Even if the user [edge case phrasing], this skill applies.
allowed-tools: Bash(curl *)
metadata:
  requires:
    env:
      - CLAW0X_API_KEY
  version: "1.0.0"
---

Description field rules (critical for triggering):

• Start with an action verb: "Extract", "Rewrite", "Analyze", "Generate", "Validate"
• Focus on what the skill does, not implementation details
• Add "Use when..." followed by 3-5 natural-language trigger phrases
• End with an edge-case catch: "Even if the user just says X, this skill applies"
• Target 30-50 words. Under 20 = agents miss it. Over 60 = agents get confused.
• Be pushy — actively claim territory. "Use when users mention anything related to email validation, address checking, or deliverability" beats "Validates email addresses."

Why pushy descriptions work: Agents match skills by scanning descriptions against user intent. A conservative description only triggers on exact matches. A pushy description catches the long tail of how users actually phrase requests.

Required Sections

Every SKILL.md must include these sections in order:

1. Title + one-line summary
2. How It Works — Under the Hood — explain the actual mechanism. If it's an LLM wrapper, say so. Transparency builds trust.
3. Prerequisites — always CLAW0X_API_KEY. If free, say "No credit card required."
4. When to Use — 4-6 concrete scenarios using trigger phrases from Stage 1.
5. API Call — complete, copy-pasteable curl using https://api.claw0x.com/v1/call. Never internal routes.
6. Input — table with Field, Type, Required, Description columns.
7. Output — exact JSON response shape with realistic values, not placeholders.

• Use tables for structured data

Stage 3: Write the handler.ts the skill can return (400, 401, 500).

10. Pricing — per-call price or "Free" explicitly.

Writing Style

• Explain the why, not just the what. Don't just say "Uses regex fallback." Say why: "because LLM APIs can timeout, and a deterministic path ensures the caller always gets a result."
• Show real examples. Never use placeholder data like "result": "...". Show actual input and output.
• Be specific about limitations. If it can't handle files over 10MB, say so.
• Keep it under 500 lines. If you need more, the skill is doing too much — split it.
• Use tables for structured data. Input/output fields, error codes, event types.

Stage 3: Write the handler.ts

The handler is a Vercel serverless function. Every handler follows the same skeleton.

The Standard Pattern

import { VercelRequest, VercelResponse } from '@vercel/node';
import { authMiddleware } from '../../lib/auth';
import { validateInput } from '../../lib/validation';
import { successResponse, errorResponse } from '../../lib/response';

async function handler(req: VercelRequest, res: VercelResponse) {
  const validation = validateInput(req.body, {
    input: { type: 'object', required: true },
  });
  if (!validation.valid) {
    return errorResponse(res, 'Invalid input', 400, validation.errors);
  }

  const { input } = validation.data!;
  const startTime = Date.now();

  try {
    const result = doSomething(input);
    return successResponse(res, {
      ...result,
      _meta: { skill: 'your-slug', latency_ms: Date.now() - startTime, version: '1.0.0' },
    });
  } catch (error: any) {
    return errorResponse(res, 'Processing failed', 500, error.message);
  }
}

export default authMiddleware(handler);

Key Rules

• Always use authMiddleware — validates the Claw0x API key.
• Always return _meta — the Gateway uses it for billing and analytics.
• Import from ../../lib/ — shared libraries live two directories up.
• Use successResponse / errorResponse — consistent formatting and status codes.
• Handle errors explicitly — 400 for bad input, 500 for internal failures.

API Wrapper: add upstream API call

const API_KEY = process.env.UPSTREAM_API_KEY;
if (!API_KEY) return errorResponse(res, 'Upstream API key not configured', 500);

const upstream = await fetch('https://api.example.com/endpoint', {
  method: 'POST',
  headers: { 'Authorization': `Bearer ${API_KEY}` },
  body: JSON.stringify({ prompt: input.text }),
});
if (!upstream.ok) return errorResponse(res, 'Upstream API failed', 502);

The caller never sees UPSTREAM_API_KEY. That's the whole point of the Gateway model.

Stage 4: Register and Deploy

Step 1: Seed Script

Create app/seed-{slug}.mjs to insert the skill into the database. Must fill all required fields including delivery_mode: 'both', endpoint_url, role, status: 'approved'.

Step 2: Run Seed + Security Scan (mandatory)

node seed-your-slug.mjs
node scan-skill-security.mjs your-slug

Security scan is a hard prerequisite. No skill goes live without it.

Step 3: Deploy

Push the skills repo to trigger Vercel auto-deploy.

Step 4: Verify

- Auditing a skill against Claw0x platform standards

## API CallT https://api.claw0x.com/v1/call \
  -H "Authorization: Bearer $CLAW0X_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"skill": "your-slug", "input": {"action": "..."}}'

Should return 200 with valid JSON including _meta.

Stage 5: Test and Iterate

Triggering Quality Test

1. Write 5 prompts that SHOULD trigger the skill
2. Write 5 prompts that SHOULD NOT trigger the skill
3. Use the generate-tests action to get a starting set
4. If triggering accuracy < 80%, rewrite the description field using optimize-description

Quality Checklist

• SKILL.md has all required sections
• Description is 30-50 words with "Use when..." phrasing
• API call uses https://api.claw0x.com/v1/call
• Input table documents every field
• Output shows real JSON, not placeholders
• handler.ts uses authMiddleware and returns _meta
• Security scan passed
• Gateway test returns 200

---

Prerequisites

A valid Claw0x API key (CLAW0X_API_KEY). Sign up at claw0x.com and create a key in your dashboard.

export CLAW0X_API_KEY="your-api-key-here"

No credit card or wallet balance needed — this skill is free.

When to Use

• Creating a new skill from scratch (SKILL.md + handler.ts)
• Improving or editing an existing skill's documentation
• Evaluating skill quality before deployment
• Optimizing a skill's description for better agent triggering
• Generating test prompts to validate skill behavior
• Auditing a skill against Claw0x platform standards

API Call

curl -s -X POST https://api.claw0x.com/v1/call \
  -H "Authorization: Bearer $CLAW0X_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "skill": "skill-creator",
    "input": {
      "action": "create",
      "intent": "I want a skill that extracts structured data from PDFs",
      "output_format": "markdown",
      "context": {
        "target_tools": ["Read", "Write", "Bash"],
        "complexity": "medium"
      }
    }
  }'

Input

Field	Type	Required	Description
action	string	Yes	One of: create, improve, evaluate, optimize-description, generate-tests
intent	string	Yes (create)	What the skill should do — one clear sentence
skill_md	string	Yes (improve/evaluate/optimize-description/generate-tests)	Existing SKILL.md content
output_format	string	No	markdown (default) or json
context	object	No	Additional context: target_tools (string[]), complexity (low/medium/high), domain (string)
feedback	string	No (improve)	Specific feedback on what to change
num_tests	number	No (generate-tests)	Number of test cases per category (default: 3)

Actions

create — Generate a new skill from intent

Takes a one-sentence intent and produces a complete SKILL.md draft with proper frontmatter, all required sections, and a handler.ts skeleton. Also runs an auto-evaluation and returns improvement suggestions.

improve — Refine an existing skill

Takes existing SKILL.md content and optional feedback. Auto-fixes structural issues (missing frontmatter, missing sections, missing CLAW0X_API_KEY declaration). Returns before/after quality scores and a list of changes made.

evaluate — Score skill quality

Analyzes a SKILL.md across four dimensions: completeness (required sections present), clarity (code examples, tables), triggering quality (description field analysis), and structure (frontmatter, env vars). Returns scores 0-1 per dimension plus actionable issues and suggestions.

optimize-description — Improve triggering accuracy

Analyzes the frontmatter description field and rewrites it for better agent triggering. Checks word count, "Use when" phrasing, action verbs, and edge-case coverage. Returns the original and optimized descriptions with specific tips.

generate-tests — Create test prompts

Generates realistic test prompts in two categories: should-trigger (direct mentions, synonyms, complex queries) and should-not-trigger (unrelated domains, similar-but-wrong tasks). Use these to validate that agents invoke the skill correctly.

Output

create response

{
  "action": "create",
  "name": "PDF Data Extractor",
  "slug": "pdf-data-extractor",
  "skill_md": "---\nname: pdf-data-extractor\ndescription: Extract structured data from PDF documents...\n---\n\n# PDF Data Extractor\n...",
  "handler_skeleton": "import { VercelRequest, VercelResponse } from '@vercel/node';\n...",
  "evaluation": {
    "completeness": 0.85,
    "clarity": 0.9,
    "triggering_quality": 0.8
  },
  "suggestions": [
    "Add error handling for corrupt PDFs",
    "Include example output with realistic invoice data"
  ],
  "_meta": { "skill": "skill-creator", "version": "1.0.0", "latency_ms": 42 }
}

evaluate response

{
  "action": "evaluate",
  "scores": {
    "completeness": 0.8,
    "clarity": 0.7,
    "triggering_quality": 0.6,
    "structure": 0.9,
    "overall": 0.75
  },
  "issues": [
    "Missing section: \"Error Codes\"",
    "Description is too short for reliable triggering"
  ],
  "suggestions": [
    "Add \"Use when...\" phrasing to description",
    "Include action verbs (extract, generate, analyze)"
  ],
  "_meta": { "skill": "skill-creator", "version": "1.0.0", "latency_ms": 15 }
}

Example — Create Action

Request:

{
  "skill": "skill-creator",
  "input": {
    "action": "create",
    "intent": "I want a skill that validates email addresses and checks deliverability",
    "context": { "target_tools": ["Bash"], "complexity": "low" }
  }
}

Response includes: a complete SKILL.md with pushy description, all required sections, a handler.ts skeleton, quality scores, and improvement suggestions. Then use evaluate to score it, optimize-description to improve triggering, and generate-tests to create validation prompts.

Error Codes

Code	Meaning	When
400	Invalid input	Missing required fields, unknown action
401	Unauthorized	Invalid or missing API key
500	Processing failed	Internal error (not billed)

Pricing

Free. This is a pure logic skill with no upstream API costs. Only your Claw0x API key is needed.

---
name: your-skill-slug
description: >
  [Action verb] [what it does]. Use when [trigger phrase 1],
  [trigger phrase 2], or [trigger phrase 3]. [What it handles/returns].
  Even if the user [edge case phrasing], this skill applies.
allowed-tools: Bash(curl *)
metadata:
  requires:
    env:
      - CLAW0X_API_KEY
  version: "1.0.0"
---

Description field rules (critical for triggering):

• Start with an action verb: "Extract", "Rewrite", "Analyze", "Generate", "Validate"
• Focus on what the skill does, not implementation details
• Add "Use when..." followed by 3-5 natural-language trigger phrases
• End with an edge-case catch: "Even if the user just says X, this skill applies"
• Target 30-50 words. Under 20 = agents miss it. Over 60 = agents get confused.
• Be pushy — actively claim territory. "Use when users mention anything related to email validation, address checking, or deliverability" beats "Validates email addresses."

Why pushy descriptions work: Agents match skills by scanning descriptions against user intent. A conservative description only triggers on exact matches. A pushy description catches the long tail of how users actually phrase requests.

Required Sections

Every SKILL.md must include these sections in order:

1. Title + one-line summary
2. How It Works — Under the Hood — explain the actual mechanism. If it's an LLM wrapper, say so. Transparency builds trust.
3. Prerequisites — always CLAW0X_API_KEY. If free, say "No credit card required."
4. When to Use — 4-6 concrete scenarios using trigger phrases from Stage 1.
5. API Call — complete, copy-pasteable curl using https://api.claw0x.com/v1/call. Never internal routes.
6. Input — table with Field, Type, Required, Description columns.
7. Output — exact JSON response shape with realistic values, not placeholders.
8. Example — at least one complete input→output pair with real data.
9. Error Codes — every error the skill can return (400, 401, 500).
10. Pricing — per-call price or "Free" explicitly.

Writing Style

• Explain the why, not just the what. Don't just say "Uses regex fallback." Say why: "because LLM APIs can timeout, and a deterministic path ensures the caller always gets a result."
• Show real examples. Never use placeholder data like "result": "...". Show actual input and output.
• Be specific about limitations. If it can't handle files over 10MB, say so.
• Keep it under 500 lines. If you need more, the skill is doing too much — split it.
• Use tables for structured data. Input/output fields, error codes, event types.

Stage 3: Write the handler.ts

The handler is a Vercel serverless function. Every handler follows the same skeleton.

The Standard Pattern

import { VercelRequest, VercelResponse } from '@vercel/node';
import { authMiddleware } from '../../lib/auth';
import { validateInput } from '../../lib/validation';
import { successResponse, errorResponse } from '../../lib/response';

async function handler(req: VercelRequest, res: VercelResponse) {
  const validation = validateInput(req.body, {
    input: { type: 'object', required: true },
  });
  if (!validation.valid) {
    return errorResponse(res, 'Invalid input', 400, validation.errors);
  }

  const { input } = validation.data!;
  const startTime = Date.now();

  try {
    const result = doSomething(input);
    return successResponse(res, {
      ...result,
      _meta: { skill: 'your-slug', latency_ms: Date.now() - startTime, version: '1.0.0' },
    });
  } catch (error: any) {
    return errorResponse(res, 'Processing failed', 500, error.message);
  }
}

export default authMiddleware(handler);

Key Rules

• Always use authMiddleware — validates the Claw0x API key.
• Always return _meta — the Gateway uses it for billing and analytics.
• Import from ../../lib/ — shared libraries live two directories up.
• Use successResponse / errorResponse — consistent formatting and status codes.
• Handle errors explicitly — 400 for bad input, 500 for internal failures.

API Wrapper: add upstream API call

const API_KEY = process.env.UPSTREAM_API_KEY;
if (!API_KEY) return errorResponse(res, 'Upstream API key not configured', 500);

const upstream = await fetch('https://api.example.com/endpoint', {
  method: 'POST',
  headers: { 'Authorization': `Bearer ${API_KEY}` },
  body: JSON.stringify({ prompt: input.text }),
});
if (!upstream.ok) return errorResponse(res, 'Upstream API failed', 502);

The caller never sees UPSTREAM_API_KEY. That's the whole point of the Gateway model.

Stage 4: Register and Deploy

Step 1: Seed Script

Create app/seed-{slug}.mjs to insert the skill into the database. Must fill all required fields including delivery_mode: 'both', endpoint_url, role, status: 'approved'.

Step 2: Run Seed + Security Scan (mandatory)

node seed-your-slug.mjs
node scan-skill-security.mjs your-slug

Security scan is a hard prerequisite. No skill goes live without it.

Step 3: Deploy

Push the skills repo to trigger Vercel auto-deploy.

Step 4: Verify

# Gateway test (production path)
curl -X POST https://api.claw0x.com/v1/call \
  -H "Authorization: Bearer $CLAW0X_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"skill": "your-slug", "input": {"action": "..."}}'

Should return 200 with valid JSON including _meta.

Stage 5: Test and Iterate

Triggering Quality Test

1. Write 5 prompts that SHOULD trigger the skill
2. Write 5 prompts that SHOULD NOT trigger the skill
3. Use the generate-tests action to get a starting set
4. If triggering accuracy < 80%, rewrite the description field using optimize-description

Quality Checklist

• SKILL.md has all required sections
• Description is 30-50 words with "Use when..." phrasing
• API call uses https://api.claw0x.com/v1/call
• Input table documents every field
• Output shows real JSON, not placeholders
• handler.ts uses authMiddleware and returns _meta
• Security scan passed
• Gateway test returns 200

Prerequisites

A valid Claw0x API key (CLAW0X_API_KEY). Sign up at claw0x.com and create a key in your dashboard.

export CLAW0X_API_KEY="your-api-key-here"

No credit card or wallet balance needed — this skill is free.

When to Use

• Creating a new skill from scratch (SKILL.md + handler.ts)
• Improving or editing an existing skill's documentation
• Evaluating skill quality before deployment
• Optimizing a skill's description for better agent triggering
• Generating test prompts to validate skill behavior
• Auditing a skill against Claw0x platform standards