"Affinity Photo" matching MCP tools:

• upload_file

  Hermoso

  Persist an ARBITRARY user file (image or video, up to 150MB) into Hermoso and get back a durable public URL that EVERY publish, schedule and ad-build tool accepts — post_to_meta / post_to_linkedin / post_to_linkedin_page / post_to_youtube / post_to_tiktok / post_to_pinterest / post_to_x / post_to_reddit / post_to_google_business / schedule_post / upload_meta_asset / upload_google_ads_asset / create_meta_ad / create_linkedin_ads_creative / set_youtube_thumbnail / save_to_drive / save_to_onedrive. THIS IS THE BRING-YOUR-OWN-CREATIVE PATH: it is for files that have NOTHING to do with a Hermoso render (media on the user's desktop, an agency's finished ad, a photo they shot), and it means you can publish, schedule and run ads through Hermoso without generating anything here. Provide exactly ONE source: `path` (a local file — works ONLY when Hermoso runs locally over stdio/CLI; the hosted connector can't see the user's machine), or `dataUri` (a base64 data: URI — keep under ~15MB on the hosted connector). If the file is ALREADY at a public https URL, the Meta, Reddit and ChatGPT-Ads tools take it directly and re-host it safely — but LinkedIn (posts and ad creatives), Pinterest, the YouTube thumbnail and upload_google_ads_asset upload the BYTES themselves and therefore refuse an external host, so run it through here first and pass the URL this returns. When in doubt, use this: its URL works everywhere. Returns {url, kind, bytes}.

  Connector

• quizbase_random

  QuizBase

  Fetch N random trivia questions matching filters. Quality-first: by default excludes questions flagged for review (use quality='all' to include for audit/research). USE WHEN: building a quiz, sampling content for warmup, generating practice sets. NOT WHEN: you need a specific question ID (use quizbase_question_by_id) or want to explore a topic deeply with facets (use quizbase_topic_by_slug). KEY FILTERS: - amount: 1-50, default 10. - lang: ISO 639-1. Default "en". Supported: en, pl. Strict — unknown language returns 400. - category (slug): e.g. geography, history, science-and-nature. Full list via quizbase_categories. - difficulty: trivial | easy | medium | hard | expert. LLM-calibrated. Records not yet LLM-rated hold the importer placeholder (mostly "medium" for factoid sources). - type: multiple | boolean (default both; no text_input in random). - regions (cultural affinity, AND): empty in data = no cultural advantage assumed. Lowercase ISO 3166-1 alpha-2 ('us', 'pl', 'gb') + cultural codes ('jewish', 'christian-catholic', 'islam'). Filter for content statistically more likely known by residents/members. Discover via quizbase_regions. - source (array): include only these source databases (one or more of 12: opentdb, opentriviaqa, kqa-pro, entityq, mintaka, mkqa, nq-open, creak, qasc, arc, webq, quizbase). - exclude_source (array): drop these sources, e.g. ["entityq"] for human-curated only. Applied after source. - license (SPDX): CC-BY-SA-4.0 | CC-BY-SA-3.0 | MIT | etc. Restrict to redistribution-friendly content. - topic (curated slug): higher precision than tags. Alias resolver matches subcategories+tags. List via quizbase_topics. - topics_any: OR over curated topics, max 10. - tags (AND), tags_any (OR), subcategory: raw taxonomy. Use topic if available. - quality: 'high' (default, recommended) = cleanest, most broadly-useful. 'standard' = broader pool incl. niche/too-specific (more volume). 'all' = audit/research, includes flagged — when 'all', each question gains a "quality" field ('high' or 'needs_review'). - exclude (UUIDs, max 250): de-dupe within a quiz session. OUTPUT: { questions: [...], meta: { count, language } }. Each question carries full per-record attribution (source, author, license, licenseVersion, licenseUrl, sourceId, url, modifications, lastModified) — identical shape to REST /api/v1/questions/random. ATTRIBUTION REQUIRED if you redistribute. CC-BY-SA modifications must be credited per § 3(a)(1)(B) using each question's own attribution object. COMMON MISTAKES: forcing lang='pl' for a global audience (use 'en' default); skipping quality (default already excludes flagged content — only pass quality='all' for audit); using tags when a curated topic exists (worse precision).

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• get_upload_url

  Partle

  Mint a one-shot signed upload URL for a product you own. Authenticated. OAuth (scope `products:write`) preferred; `api_key` fallback. Use this when you have **local image bytes** (a file the user attached, bytes you generated/downloaded in your sandbox) and you want to attach them to a product that already exists. Common cases: - `create_product` returned 409 (duplicate name) — the listing already exists; this tool gives you an upload URL for it without creating anything new. - You're adding a 2nd, 3rd, … photo to a product. The returned URL is valid for ~15 min, single product, signed with your authenticated identity. From your sandbox, do **one PUT**: requests.put(result["upload_url"], data=open("/path/to/photo.jpg", "rb").read(), headers={"Content-Type": "image/jpeg"}) No auth header on that PUT — the URL is the credential. If you have a public URL (not local bytes), use `upload_product_image(product_id, image_url=...)` instead. Args: product_id: Product to attach the future image to. You must own it. api_key: Optional API key (`pk_*`, generate at /account). Used when there is no OAuth token, and also when the OAuth token lacks the required scope — an explicitly passed key overrides an ambient token that is scoped too narrowly. An invalid or revoked token still fails regardless. Omit when using OAuth. Returns: ``{"upload_url": str, "upload_expires_in": int}``, or ``{"error": ...}`` on auth/ownership failure.

  Connector

• upload_product_image

  Partle

  Attach an image to an existing product by giving Partle a public URL to download the image from. Authenticated. OAuth (scope `products:write`) preferred; `api_key` fallback. **When to use this tool**: the image is already hosted at a public URL (a scraped product page, an Imgur link, a CDN URL the user provided). Partle's server fetches it and stores it. **When NOT to use this tool**: you have local image bytes (a file the user attached, or bytes you generated/downloaded in your sandbox). Sending those bytes through a tool argument blows past conversation context limits — phone-photo-sized payloads can be 6+ MB of base64. Instead, in your code-execution sandbox, POST the file directly to the HTTP endpoint with multipart encoding: requests.post( "https://partle.rubenayla.xyz/v1/external/products/{product_id}/images", files={"file": open("/path/to/photo.jpg", "rb")}, headers={"X-API-Key": "pk_..."}, ) Or, to create the listing and attach an image in one HTTP request: requests.post( "https://partle.rubenayla.xyz/v1/external/products", data={"metadata": json.dumps({"name": ..., "price": ...})}, files={"image": open("/path/to/photo.jpg", "rb")}, headers={"X-API-Key": "pk_..."}, ) Args: product_id: ID of the product to attach the image to. image_url: Publicly fetchable URL of the image. Server fetches it and stores it. api_key: Optional API key (`pk_*`, generate at /account). Used when there is no OAuth token, and also when the OAuth token lacks the required scope — an explicitly passed key overrides an ambient token that is scoped too narrowly. An invalid or revoked token still fails regardless. Omit when using OAuth. Returns: The created `ProductImage` record with its `id` (use for deletion) and storage path, or ``{"error": ...}`` on validation/auth failure.

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• get_upload_url

  Partle Marketplac

  Mint a one-shot signed upload URL for a product you own. Authenticated. OAuth (scope `products:write`) preferred; `api_key` fallback. Use this when you have **local image bytes** (a file the user attached, bytes you generated/downloaded in your sandbox) and you want to attach them to a product that already exists. Common cases: - `create_product` returned 409 (duplicate name) — the listing already exists; this tool gives you an upload URL for it without creating anything new. - You're adding a 2nd, 3rd, … photo to a product. The returned URL is valid for ~15 min, single product, signed with your authenticated identity. From your sandbox, do **one PUT**: requests.put(result["upload_url"], data=open("/path/to/photo.jpg", "rb").read(), headers={"Content-Type": "image/jpeg"}) No auth header on that PUT — the URL is the credential. If you have a public URL (not local bytes), use `upload_product_image(product_id, image_url=...)` instead. Args: product_id: Product to attach the future image to. You must own it. api_key: Optional API key (`pk_*`, generate at /account). Used when there is no OAuth token, and also when the OAuth token lacks the required scope — an explicitly passed key overrides an ambient token that is scoped too narrowly. An invalid or revoked token still fails regardless. Omit when using OAuth. Returns: ``{"upload_url": str, "upload_expires_in": int}``, or ``{"error": ...}`` on auth/ownership failure.

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• get_recommendations

  FreqBlog Music Metadata

  Recommended tracks for one or more seed tracks — the drop-in for Spotify's removed GET /v1/recommendations. Blends up to 5 catalog seed tracks into a single point in audio-feature space and returns the nearest catalogue tracks, RE-RANKED by genre affinity (so a feature-close cross-genre track doesn't outrank same-genre picks). Returns `seeds` (each {id, found}), `count`, and `tracks` (each {track, score, genre_relation}; each track carries its `genre`). `genre_relation` is "same", "compatible" (different but mixable family), "cross" (unrelated), or "unknown" (either side has no mapped genre), measured against the PRIMARY seed — the first of your seed_tracks we could actually use, so reordering seed_tracks changes it and a skipped seed never becomes the reference. With a SINGLE seed the field is the ranking's own verdict, so it explains the order (same as suggest_next_track). With SEVERAL seeds the ranking considers ALL of them while the label stays relative to your primary seed, so a "cross" label on a multi-seed call does NOT mean the track was pushed down — it may share a family with another of your seeds. `score` is the raw audio-feature cosine similarity in [0,1]; genre affinity influences the ORDER, not the score, so the list is NOT strictly score-descending. Use cross_genre=strict to return same-genre-family tracks ONLY (off-genre dropped server-side), or allow to disable the genre ranking. seed_tracks are catalog itunes_track_ids from search_catalog or the itunes_track_id field of a get_audio_features result. NO id? Pass `track` (+ optional `artist`) instead and we resolve the name to the best catalog match and seed on it — the resolved track is echoed back as `seed_query`; seed_tracks wins if both are given. Costs 2 quota units.

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• submit_kyc_document

  agentcard

  Submit the user's ID photo for identity verification. Ways in: (a) image data you hold programmatically (e.g. the user sent the photo in this chat and your platform exposes its bytes) — pass front_base64 (and back_base64 for a license back; its barcode reads most accurately); (b) local (stdio) mode — pass file_path/back_file_path and the file is read from disk; (c) neither — you get a secure upload link to hand the user. Do NOT ask the user what kind of document it is or where it was issued — the type and country are detected automatically from the photo; only relay a question if the result says the type could not be determined. Returns the fields read off the document — SHOW THEM TO THE USER for confirmation before continuing — plus whatever is still missing. If the result says NO identity details could be read, the image did not read as an ID at all: never insist to the user that it was their ID. Supported: JPEG/PNG/WebP up to 12MB (convert iPhone HEIC first).

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• log_body_metrics

  Wellness Project

  Log or update body composition metrics for a given date. Use when the user shares weight, body fat percentage, or any other body composition reading — whether typed manually, copy-pasted from a smart scale app, or described from a photo of a scale display. PROACTIVE DATA COLLECTION: If the user hasn't shared their data yet, ask them to copy-paste the output from their scale app or upload a photo of the display — this lets you parse all fields at once instead of asking one by one. INFER — do not ask: - date: default to today; infer from context ("this morning", "yesterday") - derived fields (lean_mass_lb, fat_mass_lb): calculate from weight and body fat % if possible — lean = weight × (1 - bf%/100), fat = weight × bf%/100 You may log any subset of fields. One row per day. Calling this tool twice on the same date updates the existing entry (upsert).

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• log_lab_results

  Wellness Project

  Log one or more blood test or biomarker results. Use when the user shares lab values — copy-pasted from a Quest/LabCorp PDF, typed from a paper report, or described from a photo of their results. REQUIRED WORKFLOW: 1) call list_lab_markers for canonical names and LOINC codes. 2) for each marker the user provides, find the best match and use its canonical marker_name and loinc_code. 3) if no match exists, use the name as stated and omit loinc_code. If the user says they have lab results but hasn't shared them, prompt: "You can paste the text from your lab report PDF, or upload a photo of the results page — I'll parse all the values at once." INFER — do not ask: date (look for a collection/drawn date in the pasted text, default today), panel_name (from list_lab_markers for matched markers, infer for unmatched), flag (extract from the report if present: "H", "L", "HH", "LL", "A"), ref_range_low/high (parse from the report if shown), lab_name (from the report header, same for all markers in a visit). Submit all markers from a single lab visit in one call.

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• get_my_active_references

  switch

  Read the user's staged references in Switch Studio. Returns TWO groups: (1) the image-generation reference strip (typed face/body/outfit/scenery/product slots) under `refs`, and (2) the VIDEO-tab references the user staged in the Omni/Image video tabs (the @Image1/@Image2 strip) under `videoReferences`, with usable signed URLs. Call this before generate_image or generate_video whenever the user says "use my refs" or refers to images they staged in Studio (including "the images in my video tab"). To make a video from the video-tab refs, pass videoReferences.imageUrls into generate_video reference_image_urls (and videoUrls into reference_video_urls) in reference-to-video / omni mode. Refs marked alive:false are dead (stored file gone) and are already excluded from the usable url lists. NOTE: a photo the user just attached in THIS chat is in neither group — for that, call upload_media and use its returned url/asset id directly.

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• post_to_meta

  Hermoso

  Publish to a connected Facebook Page, its linked Instagram, OR the brand’s Threads account — text/link/image/VIDEO/CAROUSEL. A MULTI-SLIDE creative is a CAROUSEL, not several posts: pass the slides in order as imageUrls[] and they publish as ONE swipeable post (Instagram album, Threads carousel, Facebook multi-photo post). Never publish slide 1 of a deck on its own — the creative tells the viewer to swipe. target:"facebook" (default) posts to the Page; target:"instagram" publishes a photo or Reel to the linked IG business account (needs an image or video); target:"threads" posts to the connected Threads account (text, image, or video). Works with ANY media — a finished Hermoso ad OR an arbitrary user file: imageUrl/videoUrl accept a public https URL, a data: URI, or a Hermoso /generated path; for a LOCAL file (e.g. on the user’s desktop) call upload_file first and pass the url it returns. This PUBLISHES immediately — confirm the copy + media with the user first. Needs a connected Meta account (Settings ▸ Connectors ▸ Meta) with posting permission; Threads needs its own connection.

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• quizbase_list

  QuizBase

  Cursor-paginated browse over the catalog. Quality-first: by default excludes questions flagged for review (use quality='all' for full pool). USE WHEN: full catalog sync, delta sync (updated_since), exhaustive enumeration by filter. NOT WHEN: you only need N random samples (use quizbase_random) or a single record (use quizbase_question_by_id). PAGINATION: stable cursor over id UUIDv7 DESC. First call: omit cursor. Next: pass meta.nextCursor. Stop when nextCursor is null. KEY FILTERS (full parity with REST): - lang: ISO 639-1, default "en". Supported: en, pl. - category (slug), difficulty (trivial|easy|medium|hard|expert — LLM-calibrated), type (multiple|boolean), subcategory (raw slug). - tags (AND), tags_any (OR, max 10): raw tag slugs. - topic (curated, alias resolver), topics_any (OR over curated): higher precision than tags. - regions (cultural affinity, AND): empty = no cultural advantage assumed. Lowercase ISO 3166-1 alpha-2 ('us', 'pl', 'gb') + cultural codes ('jewish', 'christian-catholic', 'islam'). Filter for content statistically more likely known by residents/members. Discover via quizbase_regions. - source (array): include only these of 12 (opentdb, opentriviaqa, kqa-pro, entityq, mintaka, mkqa, nq-open, creak, qasc, arc, webq, quizbase). - exclude_source (array): drop these sources, e.g. ["entityq"]. Applied after source. - license (SPDX): e.g. CC-BY-SA-4.0, MIT. - quality: 'high' (default) = cleanest, most broadly-useful. 'standard' = broader pool incl. niche/too-specific. 'all' = full pool incl. flagged; when 'all', each question gains a "quality" field ('high' or 'needs_review'). - updated_since (ISO 8601): only questions updated after this — for delta sync caches. BATCH + TRANSLATION MAPPING: - ids (up to 250): fetch those exact records in one call (anti-repeat, deep-links, restoring a saved set). Terminal selector — browse filters and cursor are ignored. Missing ids → meta.missing. - content_language (en|pl): with ids, returns each question's sibling in that CONTENT language across the translation chain — the same questions in another language. Distinct from lang (labels only). PAGINATION + COUNTING: - cursor (string): from previous meta.nextCursor. Omit for page 1. - limit (1-100, default 20). - count: none (default, skip — page via nextCursor) | exact (precise COUNT(*), index-only ~25-90ms). OUTPUT: { questions: [...], meta: { count, countMode, language, nextCursor, total? } }. Each question carries full per-record attribution (source, author, license, licenseVersion, licenseUrl, sourceId, url, modifications, lastModified) — identical shape to REST /api/v1/questions. ATTRIBUTION REQUIRED if you redistribute. Credit each question using its own attribution object — see license + licenseUrl + modifications fields per record. COMMON MISTAKES: not passing the cursor on subsequent calls (you'll re-read page 1); polling without updated_since when doing delta sync.

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• upload_product_image

  Partle Marketplac

  Attach an image to an existing product by giving Partle a public URL to download the image from. Authenticated. OAuth (scope `products:write`) preferred; `api_key` fallback. **When to use this tool**: the image is already hosted at a public URL (a scraped product page, an Imgur link, a CDN URL the user provided). Partle's server fetches it and stores it. **When NOT to use this tool**: you have local image bytes (a file the user attached, or bytes you generated/downloaded in your sandbox). Sending those bytes through a tool argument blows past conversation context limits — phone-photo-sized payloads can be 6+ MB of base64. Instead, in your code-execution sandbox, POST the file directly to the HTTP endpoint with multipart encoding: requests.post( "https://partle.rubenayla.xyz/v1/external/products/{product_id}/images", files={"file": open("/path/to/photo.jpg", "rb")}, headers={"X-API-Key": "pk_..."}, ) Or, to create the listing and attach an image in one HTTP request: requests.post( "https://partle.rubenayla.xyz/v1/external/products", data={"metadata": json.dumps({"name": ..., "price": ...})}, files={"image": open("/path/to/photo.jpg", "rb")}, headers={"X-API-Key": "pk_..."}, ) Args: product_id: ID of the product to attach the image to. image_url: Publicly fetchable URL of the image. Server fetches it and stores it. api_key: Optional API key (`pk_*`, generate at /account). Used when there is no OAuth token, and also when the OAuth token lacks the required scope — an explicitly passed key overrides an ambient token that is scoped too narrowly. An invalid or revoked token still fails regardless. Omit when using OAuth. Returns: The created `ProductImage` record with its `id` (use for deletion) and storage path, or ``{"error": ...}`` on validation/auth failure.

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• acc_upload_file

  ACC MCP

  Upload a file from a public source URL into an ACC project folder. Runs the full four-step APS Data Management flow: top-folder discovery → storage object creation → OSS PUT of bytes → first-version item creation. When to use: The user wants to push a document/photo/model into ACC Docs — e.g. 'upload this site photo to the Tower project Photos folder' or an automation needs to archive an exported report into Project Files. When NOT to use: Do not use for files already in ACC; do not use for files behind auth-gated URLs (fetch step is an unauthenticated GET). For very large files (>100MB), prefer the chunked/signed-S3 upload flow, not this single-PUT implementation. APS scopes: data:read data:write data:create account:read. Rate limits: APS Data Management ~50 req/min per endpoint; OSS upload bandwidth typically 100 MB/min per app. This tool issues 3–5 APS calls per upload, so budget accordingly. Errors: 401 (APS token expired — refresh); 403 (user lacks folder write permission — ask account admin to grant 'Edit' on folder); 404 (project_id not found or folder_path does not match any top folder — verify 'b.' prefix, hub membership, and folder name); 422 (invalid file_name or conflicting version); 429 (rate limit — back off 60s); 5xx (ACC/OSS upstream — retry with jitter BUT be cautious: storage object may already be created so reuse, do not re-create). Also: if source file_url returns non-2xx, the tool throws before touching ACC. Side effects: Creates a storage object, uploads bytes, and creates a versioned item in the target folder. NOT idempotent — a retry may create a duplicate item with a new version. Surface the returned item_id to the user to avoid re-uploads.

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• searchProducts

  dm-drogerie-markt

  Search for products available in the German dm-drogerie market (online and local stores). USE WHEN: searching dm-drogerie products by name, category, ingredient, property, or any natural language query (any language supported). Often answers questions about ingredients and properties directly. Covers: dm-drogerie markt brands, make-up, skincare, perfume, hair, health, nutrition, baby & child, household, home & living, photo, and pets. OUTPUT: Returns a maximum of 15 products. GTIN, DAN, brand, title, details, category, price, appLink (direct product URL), description, highlights/USPs, and extensive attributes including: - Dietary/Allergen: vegan, vegetarian, bio, glutenFree, lactoseFree, sugarFree, nutFree, soyFree - Cosmetic Ingredients: fragranceFree, alcoholFree, parabenFree, sulfateFree, preservativeFree, dyeFree, oilFree, siliconeFree, naturalCosmetics - Product Properties: waterproof, new, limitedEdition, sellout, onlineOnly, exclusiveDm, dmBrand, purchasable NOT FOR: nutritional information (calories, protein, carbs, fats), complete allergen lists, full ingredient details. For these, use 'getProductDetails' tool with the GTINs or DANs. LIMITATIONS: Only make claims based on EXPLICITLY stated product highlights/descriptions. Do NOT extrapolate or assume properties not mentioned in the results.

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• get_photo

  holiday-photo-plus-2

  Display a holiday photo to the user by creating an HTML artifact that embeds the photo from its hosted URL. After calling this tool you MUST create an HTML artifact (type text/html) whose body is a single <img> tag pointing at the hosted URL returned in the result. Do not write a prose description, caption, or commentary — the user wants to view the photo, not read about it. Use list_photos first to discover valid IDs.

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• generate_clips

  Recao

  Render UGC video scenes as ad-ready clips, metered per second of video (the estimate shows the exact price before anything renders). Pass 3 to 6 scenes (5 to 8 seconds each, one action per scene, spoken lines at most 20 words; empty spoken_line for silent characters). Consecutive scenes pack into single TAKES of up to 15 seconds, one generation each. HOW CHARACTER IDENTITY WORKS, read carefully: all characters are described in TEXT (avatar_id resolves to its persona brief; or write the persona field yourself, covering one character or a whole ensemble). The video model rejects every image that contains a person, so no photo can anchor a face. Text keeps a character IDENTICAL only WITHIN a take; ACROSS takes it preserves the look and styling but the exact face can drift, and neither avatar_id nor persona prevents that. Structure your script so scenes where the same character must be recognizably identical sit adjacent and fit one take (15s or less); treat cross-take appearances as different shots of a matching character, and review the result. reference_image_urls (up to 9 https images) keeps real products or props on-model in every take; these images must contain no people. Without confirm, it validates the contract and returns the per-scene price estimate in EUR, and makes nothing. With confirm=true it starts the metered render and returns a job_id: rendering runs in the background over a few minutes, so poll clips_status with that id to get per-scene clip URLs plus the uncut takes. Paid plans only.

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• share_listing_whatsapp

  Tu Lugar

  Generate a ready-to-send WhatsApp message for one of the authenticated agent's OWN listings: a polished, WhatsApp-tuned caption + a one-tap wa.me link (optionally pre-addressed to a client phone) + the property's main photo to attach. Use whenever the agent wants to send, share, or forward a listing to a client (or to their WhatsApp status). Pass listing_id (from my_listings); optionally client_phone to pre-address the chat. After calling, you can personalize the message for a specific client and rebuild the wa.me link yourself (URL-encode the new text into https://wa.me/<number>?text=...).

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• ic_headsets_return

  Immersive Commons

  Closes an active lend. The caller must be the borrower OR an operator. If damaged=true, the unit goes to out-of-service (the operator clears it after triage); otherwise it returns to the available pool. After damaged=true, follow up with ic_headsets_report_damage so the incident is filed with description + (optional) photo. Args: { lend_id, damaged: boolean }. Returns: { ok, unit_status: 'available' | 'out-of-service' }. Required scope: headsets:lend.

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• show_tours_activities

  GuruWalk

  Present a selection of tours or activities to the traveler as a visual list of cards (photo, rating, price, booking button) rendered inline in the conversation. Showing cards is the default way to present tours to the traveler: whenever your reply features specific tours (recommendations, a shortlist, availability results), call this tool alongside your text instead of waiting to be asked. Don't re-render a selection you already showed unless it changed. Call it AFTER finding tours with the search tools — it is a presentation tool, not a search tool. If you already checked availability with get_product_availability, you can pass each item's sessions (date and start time) and the cards will highlight them with booking links preselecting the date. For clients without UI support the same data is returned as structured text.

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