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ASecurity

Extend the system by creating new MCP servers, agents, or skills. Usage: /create a DeFi protocol tracker or /create an agent for macro analysis

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  • Added May 26, 2026
ai-agentstestingapidocumentation

Works with

  • claude code
  • api
  • mcp

Security analysis

A100/100

Scanned May 27, 2026

npx -y skills add hugoguerrap/crypto-claude-desk --skill create --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: create
description: Extend the system by creating new MCP servers, agents, or skills. Usage: /create a DeFi protocol tracker or /create an agent for macro analysis
user-invocable: true
---

# Create 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_tool` wrapper for FastMCP tools
- Mock ALL external API calls (HTTP, CCXT, etc.) — tests must run offline
- One test class per tool, with at least: `test_success` and `test_error_handling`
- Assert `result['status'] == 'success'` on happy path
- Assert `result['status'] == 'error'` on failure path
Write the test to `tests/test_{name}.py`."

### Step 4: Integration Guidance
After the component is generated, present:

1. **What was created** — show the file path and a brief description
2. **Review** — show the key parts of the generated file for the user to review
3. **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' `mcpServers` list in their frontmatter
- Add the server to the MCP table in `CLAUDE.md`
- Run `uv run --frozen pytest tests/test_{name}.py -v` to verify the tests pass
- Run `/setup` to 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.md` for documentation

### Output
Present:
1. Research findings (APIs, feasibility)
2. Generated component (file path + key capabilities)
3. Test results (MCP servers: show pytest output)
4. Integration checklist (numbered steps)

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