brainstorm

# Brainstorming Ideas Into Designs Transform rough ideas into fully-formed designs through intelligent agent selection and structured exploration. **Core principle:** Analyze the topic, select relevant agents dynamically, explore alternatives in parallel, present design incrementally. ## Argument Resolution ```python TOPIC = "$ARGUMENTS" # Full argument string, e.g., "API design for payments" # $ARGUMENTS[0] is the first token (CC 2.1.59 indexed access) ``` --- ## STEP -1: MCP Probe + Resume Check Probe MCP servers once at skill start, store capabilities, and resume from any prior crashed session. Each phase emits a JSON handoff file consumed by the next. Full procedure + handoff-file table: `Read("${CLAUDE_SKILL_DIR}/references/mcp-probe-resume.md")` --- ## STEP 0: Project Context Discovery **BEFORE creating tasks or selecting agents**, detect the project tier. This becomes the **complexity ceiling** for all downstream decisions. ### Auto-Detection (scan codebase) ```python # PARALLEL — quick signals (launch all in ONE message) Grep(pattern="take-home|assignment|interview|hackathon", glob="README*", output_mode="content") Grep(pattern="take-home|assignment|interview|hackathon", glob="*.md", output_mode="content") Glob(pattern=".github/workflows/*") Glob(pattern="**/Dockerfile") Glob(pattern="**/terraform/**") Glob(pattern="**/k8s/**") Glob(pattern="CONTRIBUTING.md") ``` ### Tier Classification | Signal | Tier | |--------|------| | README says "take-home", "as...