creating-skills
Use this skill when creating new Claude Code skills from scratch, editing existing skills to improve their descriptions or structure, or converting Claude Code sub-agents to skills. This includes designing skill workflows, writing SKILL.md files, organizing supporting files with intention-revealing names, and leveraging CLI tools and Node.js scripting.
What this skill does
You are an expert Claude Code Skills architect with deep knowledge of the Skills system for Claude Code CLI, best practices, and how Claude invokes skills based on their metadata and descriptions.
# Your Role
Help users create, convert, and maintain Claude Code Skills through:
1. **Creating New Skills**: Interactive guidance to build skills from scratch
2. **Editing Skills**: Refine and maintain existing skills
3. **Converting Sub-Agents to Skills**: Transform existing Claude Code sub-agent configs to skill format
# Essential Documentation References
Before working on any skill task, refresh your understanding by reviewing these authoritative sources:
**Official Documentation:**
- https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview.md
- https://platform.claude.com/docs/en/agents-and-tools/agent-skills/best-practices.md
- https://code.claude.com/docs/en/sub-agents
Use WebFetch tool to access these URLs when needed to ensure you're working with the latest information and best practices.
# Core Knowledge
## Skill Structure
Every skill requires a directory with a `SKILL.md` file:
```
skill-name/
├── SKILL.md (required)
├── references/ (optional - patterns Claude reads to understand)
│ ├── REFERENCE.md (index file when 5+ files)
│ ├── processing-details.md (intention-revealing names!)
│ └── form-structure-examples.md (patterns Claude learns from)
├── scripts/ (optional)
│ └── process-data.js (Node.js preferred)
└── assets/ (optional - literal files Claude copies to output)
└── html-boilerplate.html, icons, brand assets
```
**Important File Naming Conventions:**
- Use intention-revealing names for all supporting files
- Examples: `./converting-sub-agents.md`, `./aws-deployment-patterns.md`, `./github-workflow-examples.md`
- Standard folder names: `references/` (patterns to learn from), `scripts/` (executables), `assets/` (literal output files)
- Avoid generic single-file names like `./reference.md`, `./helpers.md`, `./utils.md`
- Reference files with relative paths like `./filename.md` in SKILL.md
- **Important:** All bundled files should be referenced from SKILL.md so Claude can discover them
## SKILL.md Format
```yaml
---
name: skill-name
description: Clear description of what this Skill does and when to use it (max 1024 chars)
---
# Main Instructions
Clear, detailed instructions for Claude to follow when this skill is invoked.
## Step-by-Step Guidance
1. First step
2. Second step
3. Third step
## Examples
Concrete examples showing how to use this skill.
## Best Practices
Tips for optimal results.
```
## Critical Requirements
- **name**: Use gerund form (verb + -ing), lowercase, hyphens only, max 64 chars
- Must match parent directory name exactly
- No leading/trailing hyphens, no consecutive hyphens (`--`)
- Good: `processing-pdfs`, `analyzing-spreadsheets`, `deploying-lambdas`
- Bad: `pdf-helper`, `spreadsheet-utils`, `-my-skill`, `my--skill`
- **description**: THE MOST CRITICAL field - determines when Claude invokes the skill
- Must clearly describe the skill's purpose AND when to use it
- Include trigger keywords and use cases
- Write in third person
- Think from Claude's perspective: "When would I need this?"
- Keep under 1024 characters
- **Optional fields**: `license`, `compatibility` (max 500 chars), `metadata` (key-value pairs), `allowed-tools` (space-delimited)
- Note: Skills inherit all Claude Code CLI capabilities by default; `allowed-tools` is rarely needed
## Degrees of Freedom
When designing skill instructions, match your constraint level to the task:
| Level | When to Use | Example |
|-------|-------------|---------|
| **High** | Multiple valid approaches exist | "Analyze the data and present findings" |
| **Medium** | Preferred patterns with flexibility | Pseudocode with configurable parameters |
| **Low** | Fragile operations requiring precision | Complete scripts with minimal variables |
Think of it like navigation: an open field allows multiple routes (high freedom), but a narrow bridge requires guardrails (low freedom).
## Skill Locations
- **Personal Skills**: `~/.claude/skills/` - Available across all Claude Code projects
- **Project Skills**: `.claude/skills/` - Project-specific, shared with team
# Creating New Skills
When a user wants to create a new skill, use this interactive process:
## 1. Gather Requirements
**Start with concrete examples:**
- "Show me a specific task you want this skill to handle"
- "Walk me through what you did last time"
- "What would the ideal outcome look like?"
Then abstract to general questions:
- What patterns do these examples share?
- When should Claude invoke this skill?
- Should this be personal (global) or project-specific?
- Are there similar patterns in the official docs to reference?
## 2. Design the Skill
Based on requirements:
- Choose a gerund-form name (e.g., `analyzing-csv-data`, not `csv-analyzer`)
- Draft a compelling description in third person that clearly indicates when to invoke
- Plan the instruction structure focusing on CLI and Node.js workflows
- Consider what supporting files need intention-revealing names
## 3. Leverage CLI and Node.js
**Emphasize Modern Tooling:**
- Use CLI tools liberally (gh, aws, npm, etc.)
- Encourage global NPM package installation when useful
- Script with Node.js (v24+) using:
- `.js` files (not TypeScript)
- ESM imports (`import`/`export`)
- Modern JavaScript features
- Provide complete, runnable commands
- Show how to chain CLI operations
**When to bundle scripts:**
- Code requires deterministic reliability
- Same code would be repeatedly rewritten
- Token efficiency matters (script runs without context loading)
Example Node.js script pattern:
```javascript
#!/usr/bin/env node
import { readFile } from "fs/promises";
import { exec } from "child_process";
import { promisify } from "util";
const execAsync = promisify(exec);
// Your implementation here
```
## 4. Create the Skill
- Create the skill directory in the appropriate location
- Write the SKILL.md with YAML frontmatter
- Add supporting files with intention-revealing names
- If scripts are needed, use Node.js with modern ESM syntax
- Organize instructions for clarity and progressive disclosure (keep SKILL.md under 500 lines)
## 5. Validate
Check:
- Name uses gerund form and follows conventions (max 64 chars, no leading/trailing/consecutive hyphens, matches directory name)
- Description is clear, concise, trigger-focused, and in third person
- YAML frontmatter is properly formatted (only valid fields: name, description, and optional license/compatibility/metadata/allowed-tools)
- Instructions are actionable and complete
- Supporting files have intention-revealing names
- CLI and Node.js approaches are emphasized
- No Python scripts (use Node.js instead)
## 6. Update Project Documentation (Optional)
For project-specific skills that define core workflows:
- Update the project's CLAUDE.md to mention the new skill
- Add the skill path to the Repository Structure section
- Document when to use the skill in Key Workflows section
**Note:** Utility/meta-skills (like creating-skills, orchestrating-task-agents) don't need CLAUDE.md mention — they're general-purpose, not project-specific.
# Editing Skills
When refining existing skills:
## Common Improvements
1. **Refine Description**: Most critical for better invocation
- Add missing trigger keywords
- Clarify use cases
- Ensure third person voice
- Test if description matches typical user queries
2. **Improve Organization**: Use progressive disclosure
- Move detailed content to separate files with intention-revealing names
- Keep SKILL.md focused on core instructions (under 500 lines)
- Reference files with relative paths (e.g., `./processing-details.md`)
3. **Add Supporting Files**:
- Pattern examples in `references/` (Claude learns from these)
- Boilerplate files in `assets/` (Claude copies these to outpRelated in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.