Wellness Nourish

Delete a single local hydration entry by id after explicit user intent.

Returns synthetic example payloads of nourish_search_food, nourish_estimate_meal, and nourish_daily_summary so agents see the contract before any real call. Shapes are verified against the real pipelines by scripts/demo-contract-test.mjs, so they are safe to write a parser against; `inputs` shows the call that produced each sample.

Estimate nutrition for a short meal text using local deterministic defaults. Accepts text or meal_text; preserve unresolved and confidence.

Estimate meal nutrition from an agent-provided photo observation; always requires user confirmation before logging.

Check late-day protein, calories, and hydration gaps with a compact Telegram-friendly next step.

Export local intake data as JSONL or CSV without provider secrets or tokens. Defaults to the 500 most-recent rows; pass since/until to scope by date or max_rows to widen/narrow. Omitted rows are reported so you can refine instead of dumping months of history into chat (use the `wellness-nourish export` CLI for a full unbounded dump).

Delete a local remembered meal by id or label after explicit user intent.

Fetch a USDA food by source_id, an Open Food Facts food by barcode source_id, or a TACO food by source_id.

Read local calorie, macro, and hydration goals.

Compute per-day progress vs configured goals (kcal, protein, carbs, fat, water) for today / yesterday / last_7_days / last_30_days. Returns per-day breakdown (consumed, goal, pct, delta_to_goal), period totals, multi-day averages, days_on_target count, and locale-aware next-action recommendations (pt-BR if profile language is Portuguese, otherwise en). Read-only: no logging side effects, no explicit_user_intent required.

Summarize local hydration for a date.

List local intake entries with optional filters: date OR since/until range, meal_type, tag, source_trace, min_confidence, limit. All filters AND together. Returns most-recent-first.

Read local remembered meals and nutrition preferences for personal Telegram shortcuts.

Log an intake entry only after explicit user intent. Pass explicit_user_intent: true after the user asks to save/log/register; accepts text or meal_text plus structured food data.

Log local hydration in milliliters after explicit user intent. Pass explicit_user_intent: true after the user asks to save/log water.

Lookup a packaged food barcode in Open Food Facts.

Decode a packaged-food barcode image, then lookup the product in Open Food Facts.

Returns the 11-question onboarding flow for the shared Delx Wellness profile. Read-only. The agent should ask these questions next so wellness-nourish (and the rest of the wellness stack) can personalize responses — non-secret data only, stored at ~/.delx-wellness/profile.json.

Suggest light pre-workout nutrition using goals, current intake, and optional WHOOP/Garmin context.

Describe local storage, secret handling, source licensing, and safety boundaries.

Returns the shared Delx Wellness profile (~/.delx-wellness/profile.json). Read-only. Surfaces calorie/macro targets, dietary preferences, restrictions/allergies, and goals so nourish coach/suggest tools can personalize meals.

Persist a partial patch to the shared Delx Wellness profile. Requires explicit_user_intent: true. Rejects any field containing oauth/token/secret/password/cookie/refresh/api_key/session — the profile is for non-secret wellness context only.

Read the most recent shared wellness_context (delx-wellness-context/v1) written by a wearable connector to ~/.delx-wellness/, so coach tools can be recovery/strain-aware without the agent passing it inline. Read-only; never fabricates wearable data. If no connector has persisted a context yet, returns available:false with the expected path. The returned context can be passed straight into nourish_daily_coach / nourish_suggest_next_meal / nourish_pre_workout_nutrition as wearable_context (or set auto_wearable:true on those tools to pull it automatically).

Personalized 3-step setup walkthrough for the human user. Adapts to current state (USDA key set? OFF enabled? local-dir writable?). Call this first when the user asks 'how do I use this?'

Save a personal meal shortcut locally after explicit user intent, for example 'meu cafe normal' -> '2 ovos e banana'.

Search food providers by query. Use taco or br_local for Brazilian staples, open_food_facts for packaged products, usda for generic foods, or all.

Set local calorie, macro, and hydration goals after explicit user intent. Use daily: {...} or flat shortcuts like calories_kcal/protein_g; pass explicit_user_intent: true after confirmation.

Suggest a next meal from today's intake, goals, personal memory, and optional wearable context.

Undo the most recently logged intake or hydration entry. The most common Telegram/agent recovery move ('I logged the wrong thing'). Returns what was undone so the agent can confirm. Requires explicit_user_intent. Pass kind: 'intake' | 'hydration' | 'any' (default 'any') to scope the undo.

Update a local intake entry by id. Quantity or grams_estimate changes rescale nutrients to keep summaries consistent. Gated: requires explicit user intent — agents must not call this autonomously.

Summarize seven days of local intake totals from a start date.