create
Scannednpx machina-cli add skill hugoguerrap/crypto-claude-desk/create --openclawCreate New Component
Extend the crypto trading desk with a new component based on the user's natural language description: $ARGUMENTS
Workflow
Step 1: Parse Request
Determine what the user wants to create:
- MCP server — if the request involves new data sources, APIs, or tools (e.g., "on-chain analytics", "DeFi tracker", "social media monitor")
- Agent — if the request involves a new specialist role (e.g., "macro analyst", "DeFi strategist", "on-chain detective")
- Skill — if the request involves a new workflow or command (e.g., "multi-coin comparison", "rebalance portfolio", "alert system")
If unclear, ask the user what type of component they want.
Step 2: Research
Delegate to system-builder agent:
"Research what's needed to create: $ARGUMENTS. Use WebSearch to find relevant public APIs (prefer no-API-key-required). Use WebFetch to read API documentation. Read existing components in the project to understand patterns — read at least 2 files from the relevant directory (mcp-servers/, agents/, or skills/). Read mcp-servers/validators.py for reusable validation. Write a research summary to data/create/{name}-research.md with: APIs found, rate limits, data available, recommended approach."
Step 3: Generate
After research completes, delegate to system-builder agent:
"Based on the research in data/create/{name}-research.md, generate a new {type} for: $ARGUMENTS. Follow the exact patterns from existing files. Write the component to the correct location:
- MCP server → mcp-servers/{name}.py
- Agent → agents/{name}.md
- Skill → skills/{name}/SKILL.md Write a creation summary to data/create/{name}-summary.md."
Step 3b: Generate Tests (MCP servers only)
If the component is an MCP server, delegate to system-builder agent:
"Generate a test file for the new MCP server mcp-servers/{name}.py. Read tests/helpers.py to understand the call_tool() helper. Read at least 2 existing test files (e.g., tests/test_crypto_data.py, tests/test_crypto_exchange.py) to understand the testing pattern:
- Import with
sys.path.insert(0, str(Path(__file__).resolve().parent.parent / 'mcp-servers')) - Use
from helpers import call_toolwrapper for FastMCP tools - Mock ALL external API calls (HTTP, CCXT, etc.) — tests must run offline
- One test class per tool, with at least:
test_successandtest_error_handling - Assert
result['status'] == 'success'on happy path - Assert
result['status'] == 'error'on failure path Write the test totests/test_{name}.py."
Step 4: Integration Guidance
After the component is generated, present:
- What was created — show the file path and a brief description
- Review — show the key parts of the generated file for the user to review
- Next steps — tell the user what they need to do:
For MCP servers:
- Add the server configuration to
mcp-servers.plugin.json - Add the server name to relevant agents'
mcpServerslist in their frontmatter - Add the server to the MCP table in
CLAUDE.md - Run
uv run --frozen pytest tests/test_{name}.py -vto verify the tests pass - Run
/setupto verify the new server starts correctly
For agents:
- Add routing rules in
CLAUDE.md(which queries should route to this agent) - Add the agent to the agents table in
CLAUDE.md
For skills:
- Auto-discovered by Claude Code — no configuration needed
- Add to the skills table in
CLAUDE.mdfor documentation
Output
Present:
- Research findings (APIs, feasibility)
- Generated component (file path + key capabilities)
- Test results (MCP servers: show pytest output)
- Integration checklist (numbered steps)
Source
git clone https://github.com/hugoguerrap/crypto-claude-desk/blob/main/skills/create/SKILL.mdView on GitHub Overview
The Create skill extends the crypto desk by turning a natural language request into a new MCP server, agent, or skill. It guides through parsing the request, researching requirements, generating the component following existing project patterns, and integrating it with tests and configuration. This enables rapid expansion of capabilities from user descriptions.
How This Skill Works
When a user asks to create something, the system classifies the target component (MCP server, agent, or skill). It delegates research to a system-builder process, which uses public APIs and project patterns to draft a plan. It then generates the new component in the correct directory, writes a creation summary, and, if an MCP server is involved, also generates tests per the documented pattern.
When to Use It
- You want a new MCP server to integrate data sources, APIs, or tools (e.g., on-chain analytics or DeFi tracker)
- You want a new agent that represents a specialized role (e.g., macro analyst, DeFi strategist, on-chain detective)
- You want a new workflow or command (a skill) like multi-coin comparison, rebalance portfolio, or alert system
- You need to prototype a component by following established project patterns and file structures
- You're unsure which component type fits your NL description and need guidance on classification
Quick Start
- Step 1: Parse the user request to decide if you’re creating an MCP server, agent, or skill
- Step 2: Research APIs, data sources, and existing patterns by inspecting relevant project files
- Step 3: Generate the component in the correct directory and write a creation summary; if MCP, also generate tests
Best Practices
- Clearly classify the request as MCP server, agent, or skill before proceeding
- Review existing components in mcp-servers/, agents/, or skills/ to align with patterns
- Document APIs, rate limits, and data availability during the research phase
- For MCP servers, plan tests early and mock external calls to keep tests offline
- Provide a concise integration checklist so the user can wire the new component into CLAUDE.md and related configs
Example Use Cases
- create a DeFi protocol tracker MCP server
- create an agent for macro analysis
- create a multi-coin comparison skill
- create an on-chain detective agent
- create an alert system skill