schema: spec-driven

# Project context (optional)
# This is shown to AI when creating artifacts.
# Add your tech stack, conventions, style guides, domain knowledge, etc.
context: |
  Tech stack:
    - Language: Python 3.13+
    - Package manager: uv (pyproject.toml — never requirements.txt)
    - Chat interface: Chainlit 2.x (entry point: chat_app.py)
    - LLM access: LiteLLM (provider-agnostic; src/llm.py wraps litellm.completion)
    - Email channel: IMAP/SMTP via stdlib (imaplib, smtplib); entry point: main.py
    - Storage: file-based JSON (no database); data/ directory
    - Knowledge base: admin-editable Markdown files in openspec/.../knowledge-base/
    - Tests: pytest + pytest-mock (tests/ directory)

  Key architectural decisions:
    - Channel-agnostic agent core: src/agent/ (prompts, response_parser) is shared
      between email (src/agent/core.py / EmailAgent) and chat (chat_app.py)
    - LLM streaming: src/llm.stream_complete() yields chunks via litellm stream=True
    - Session state for chat: cl.user_session (Chainlit server-side, survives page refresh)
    - Accessibility: public/custom.css (contrast, dvh, reduced-motion) +
      public/accessibility.js (ARIA live region, focus management, skip link)
    - Admin notifications routed by playgroup type (indoor→Andrea, outdoor→Barbara, CC Markus)

  Conventions:
    - German is the default language; agent auto-detects and switches to English
    - Use informal "du" in German agent responses
    - All knowledge base content stays in Markdown (non-technical admins can edit it)
    - Schema validation required before saving any completed registration
    - Never hardcode fee amounts or contact details in application code

# Per-artifact rules (optional)
# Add custom rules for specific artifacts.
# Example:
#   rules:
#     proposal:
#       - Keep proposals under 500 words
#       - Always include a "Non-goals" section
#     tasks:
#       - Break tasks into chunks of max 2 hours