sso-mcp-server: Command for Claude Code

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Outline

IMPORTANT: Automatically generate a 'docs:' prefixed git commit message (e.g., 'docs: add implementation plan for feature-name') and commit design.md, research.md, data-model.md, and contracts/ upon completion.

1. Setup: Run .rainbow/scripts/bash/setup-design.sh --json from repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").

2. Load context: Read FEATURE_SPEC, memory/ground-rules.md, and docs/architecture.md (if it exists). Load IMPL_PLAN template (already copied).

3. Execute plan workflow: Follow the structure in IMPL_PLAN template to:

   • Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
   • Fill Ground-rules Check section from ground-rules
   • Align with architecture decisions from architecture.md (if available)
   • Evaluate gates (ERROR if violations unjustified)
   • Phase 0: Generate research.md (resolve all NEEDS CLARIFICATION)
   • Phase 1: Generate data-model.md, contracts/, quickstart.md
   • Phase 1: Update agent context by running the agent script
   • Re-evaluate Ground-rules Check post-design

4. Stop and report: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, and generated artifacts.

Phases

Phase 0: Outline & Research

1. Extract unknowns from Technical Context above:

   • For each NEEDS CLARIFICATION → research task
   • For each dependency → best practices task
   • For each integration → patterns task
   • Review architecture.md (if exists) for relevant architectural decisions and patterns

2. Generate and dispatch research agents:

   For each unknown in Technical Context:
     Task: "Research {unknown} for {feature context}"
   For each technology choice:
     Task: "Find best practices for {tech} in {domain}"
   If architecture.md exists:
     Review: Architectural patterns, ADRs, and quality strategies relevant to this feature