Lafeitu Gourmet Skill

**Judgment:** A strong, specialized agentic commerce skill for the Lafeitu (辣匪兔) spicy food ecosystem. It appears mature and thoughtfully designed for agents that need reliable access to a single-brand catalog, cart, and order flow. **Key strengths** - Rich, well-scoped functionality covering discovery, cart, auth/registration, profile, promotions, and orders. - API-first design with a dedicated Python client and clear CLI examples, which supports structured, deterministic interactions. - Explicit workflow instructions (search before cart, confirm variants, show cart after changes, payment handoff) that reduce agent errors. - Brand-context tools (`brand-story`, `company-info`, `contact-info`) to keep recommendations grounded and avoid fabricated marketing claims. **Risks / limitations** - Hard dependency on the Lafeitu backend and its availability; outages or API changes will directly impact reliability. - Handles sensitive user data (email, password, phone, address). While flows are clear, actual transport/storage security depends on the backend and is not auditable from this description. - Very domain-specific: only useful for Lafeitu products; not a general food-delivery or multi-merchant solution. - Performance constrained by remote API latency and rate limits (429 handling is documented, but still a UX risk at scale). **Recommended scenarios** - Agents acting as a “Lafeitu shopping assistant” helping users browse Zigong-style spicy foods, tune flavor/format/weight, and manage their cart. - Integrated flows where a broader assistant delegates all Lafeitu-specific commerce tasks (search, cart, order creation) to a specialized tool. - Brand-aware recommendation experiences that need official product data and authentic Lafeitu story/context rather than generic spicy-food advice. - Testing and iterating on agentic commerce patterns using a concrete, well-documented single-merchant reference implementation.