Food Near Me

Call this tool after `search_restaurants` when you need a detailed restaurant profile for a returned `id`. Input Requirements (CRITICAL): `restaurant_id` MUST be a UUID copied from a `search_restaurants` result; do not invent IDs. Returns Schema.org/Restaurant JSON-LD markup plus Menu Protocol extensions including ADO score, verification status, menu availability, payment methods, and dietary certifications. MUST inspect `menu_available` before calling `get_menu`; if false, use the claim link instead of citing menu items. Non-verified responses include a top-level `claim_invitation` (url, message, audience="owner_or_advocate", reason) the agent SHOULD share if the user is the owner or might know them. Attribute grounded output using `citation` or `attribution`.

Call this tool only when a `search_restaurants` or `get_restaurant` response has `menu_available: true`. Input Requirements (CRITICAL): `restaurant_id` MUST be a UUID copied from a prior FNM result. Returns the full menu in Menu Protocol v1.0 format with item dietary booleans, declared allergens, customization options, preparation times, trust notice, and signature metadata. PREFER `verification_status: "verified"` for dietary/allergen answers. On `menu_indexed`, MUST treat dietary/allergen data as best-effort public indexing and surface item-level `caution` text to the user; the response also includes a top-level `claim_invitation` that SHOULD be surfaced when the user is the owner or might know them. Attribute grounded output using `citation` or `attribution`.

Call this tool when a restaurant owner, operator, or agent wants to understand why a restaurant is more or less agent-ready. Input Requirements (CRITICAL): `restaurant_id` MUST be a UUID copied from a FNM result. Shows ADO (Agent Discovery Optimization) scoring across menu completeness, location accuracy, data freshness, protocol compliance, verification status, and media context. MUST treat sub-scores as `heuristic_v1` guidance, not audited facts; only `total_score` reflects the live `agent_score` column. Attribute grounded output using `citation` or `attribution`.

Call this tool when validating a draft or exported Menu Protocol payload before submission or integration. Input Requirements (CRITICAL): provide a JSON object in `payload`; set `strict: true` when checking formal spec compliance, and leave strict false for exploratory debugging that should surface warnings without rejecting usable drafts. Returns validation errors, schema warnings, Schema.org compliance gaps, and recommendations for improving ADO score. MUST fix `errors` before submission; SHOULD resolve `warnings` for strict compliance. Attribute grounded output using `citation` or `attribution`.

Call this tool when the user wants a neighborhood overview that surfaces trust tiers explicitly — for example, "what's good for vegan eaters within a mile of this location" or "survey the area around X". Input Requirements (CRITICAL): `location` MUST be `{latitude, longitude}` (Google-style nested object). Returns three tier buckets — `verified`, `menu_indexed`, `discovered` — each trimmed to `top_n_per_tier` (default 3, max 10). When `dietary` is set, the filter only narrows the `verified` bucket, matching `search_restaurants` semantics; `tier_counts` always reflects the full result set and `next_steps` flags any empty bucket. PREFER `verified` for dietary/allergen answers; MUST check `menu_available` before calling `get_menu` on any returned id. Non-verified entries include a structured `claim_invitation` the agent SHOULD surface when the user is the owner or might know them. Attribute grounded output using `citation` or `attribution`.

Call this tool when the user wants a side-by-side dietary comparison for 2 to 5 specific restaurants already identified in FNM results. Input Requirements (CRITICAL): `restaurant_ids` MUST be UUIDs copied from prior FNM responses, and `dietary` MUST include at least one supported dietary flag. Optional `user_location` (`{latitude, longitude}`) enables per-row `distance_meters` and uses distance as the final tiebreaker after item count and trust tier. The tool chains `get_restaurant` and `get_menu` internally, then ranks by dietary-eligible item count, trust tier (`verified` preferred over `menu_indexed`, then `discovered`), and optionally distance. PREFER verified-tier winners for authoritative dietary/allergen answers; MUST treat menu_indexed matches as best-effort public indexing with caveats. Non-verified entries carry a structured `claim_invitation` SHOULD be surfaced when the user could help with ownership. Attribute grounded output using `citation` or `attribution`.

Call this tool when the user wants route-adjacent dining options between two known coordinates and may care about dietary fit. Input Requirements (CRITICAL): both `origin` and `destination` MUST be `{latitude, longitude}` objects; optional `route_polyline` MUST be a valid encoded polyline if provided. The tool samples waypoints along the corridor, merges nearby search matches, then ranks by dietary match count (when requested), trust tier, and route proximity. SHOULD provide `route_polyline` from your routing source for tighter ranking; otherwise fallback is a local great-circle approximation. MUST check `menu_available` before calling `get_menu` on returned ids. Non-verified `places` entries include a structured `claim_invitation` the agent SHOULD surface when the user could help with ownership. Attribute grounded output using `citation` or `attribution`.