Zhongcao Local Business Note Maker

Create a coordinated three-image REDnote (Xiaohongshu) discovery note for a non-food physical local business. Turn a storefront, space, service, product, or merchant brief into a store-front cover, a store or service highlight, and a visit-ready closing visual. Pair the visual story with title ideas, caption beats, and tags that use only facts the user has supplied.

Scope and routing

Use this Skill for retail shops, beauty and wellness studios, creative spaces, gyms, hotels, attractions, pop-ups, and other local places where a coordinated note should help people recognise the place and its experience.

Route a restaurant, café, dish, menu, or food-visit story to zhongcao-food-note-maker; route a generic multi-image topic to zhongcao-carousel-maker; route one isolated post cover to zhongcao-cover-maker; and route an outfit-led note to zhongcao-ootd-lookbook-maker.

Keep the business name, category, city or area, address, hours, price, availability, offer, booking details, credentials, results, and service claims limited to user-provided facts. A photo can guide visible details, but it is not evidence for facts the user has not stated.

Inputs and default note

Reuse the conversation's business brief, audience, visual direction, and references. For a note that represents a real local business, require at least one accessible storefront, space, service, or featured-product photo plus the business category and visitor angle. A concise brief containing the business category, city or area, signature offering, and visual direction can instead start a concept visual route; present it as a concept visual rather than a record of the real location.

Ask only for an input that changes the result: the business anchor, visitor angle, or visual direction. Put user-provided facts and visual must-keeps on a private business-note card before drafting any image prompt. Read local-business note planning when the brief needs structure.

Default to a three-slide vertical 3:4 note at 2K, delivered as one ordered sequence only when the live model card accepts count: 3 and output_relationship: "sequence":

1. Store-front cover — a recognisable entry point with clear title-safe space.
2. Store or service highlight — the approved space, visitor experience, signature service, or featured product.
3. Visit-ready close — a coherent final scene with room for the user's verified visit details.

Use model: "auto" and model-managed controls unless the user asks to choose a model, compatibility, or price. Before fixing model, canvas, control, count, output relationship, or price, read beatra.models.list for the selected image_to_image, text_to_image, or image_edit capability. If the live card does not support the requested ordered sequence, show the available count, relationship, maximum charge, and call count, then obtain the user's choice of a revised paid route. Never present independent candidates as a connected note.

Golden path

1. Build the business-note card: business anchor, user-provided facts, audience, visitor angle, visual must-keeps, palette, lighting, title-safe placement, and the three slide roles.
2. Route an accessible source photo to beatra.images.transform, a concept brief to beatra.images.generate, and a selected-slide correction to beatra.images.edit.
3. Draft one three-slide visual story plus the free post package: title ideas, caption beats, fact checklist, and discovery tags.
4. Read the live card and show one confirmation with all slide roles, the full prompt, exact reference order, must-keeps, canvas, model behaviour, controls, count, relationship, current maximum charge, and call count.
5. After approval, create one stable opaque client_request_id, submit exactly once through the bundled client, and retain the returned task ID.
6. Poll the original task, review accessible results against the note card, and deliver the ordered artifacts with the post package and actual returned facts.

Read the local-business workflow for exact routes, request payloads, confirmation, polling, recovery, and image review.

Paid-work confirmation

Planning, post writing, and prompt drafting are free. The optional Xiaohongshu lookup is the one thing that can charge before generation, and it is priced and approved on its own. Before image generation or a revision, obtain one clear confirmation of the frozen business-note card, paid image request, source and reference order, canvas, model, controls, count, current price, maximum charge, and total call count.

When the user asks for text embedded in an image, freeze the exact supplied text and its placement in that confirmation. Keep the title, caption, and facts available separately so the user can choose final wording after review.

Every changed business anchor, fact, source or reference order, prompt, slide role, canvas, model, count, output relationship, control, or embedded text is new paid work with a new confirmation and a new client_request_id. A focused revision to an accepted slide is new paid work too.

Execute and deliver

Use only this package's bundled scripts/mcp_client.py for remote operations. Send one JSON object on standard input after call <tool-name>. Never configure or call a host Beatra Connector, and never use REST/OpenAPI as a fallback. Read Bundled MCP Client diagnostics for commands and connection troubleshooting.

Upload a local source and put its returned artifact at images[0] for a transform. Later images, up to three, guide the approved visual direction in the user-stated order. The default is an explicit 3:4 canvas. If the user chooses aspect: "source", the final ordered reference is the canvas anchor; show that source-derived choice in the confirmation instead of assuming the first image sets the output ratio. For a concept-only route use generate. For a focused revision use the accepted slide at images[0] with edit and no more than two normalized regions.

The bundled client registers the installation itself on first use through beatra.installations.register; there is no register subcommand to invoke. A returned task_id belongs to the original approved work: poll only with beatra.tasks.get. Replay only a genuinely unknown create response with the byte-equivalent frozen payload and same ID. If the task ID is missing, use beatra.tasks.list scoped to the original capability and follow each next_cursor across the creation window, then verify the candidate with beatra.tasks.get before a replay. Call beatra.tasks.cancel only at the user's request; on 409, keep polling the original and report cancellation only at terminal status: "canceled".

Review only accessible images for user-confirmed visual must-keeps, each slide role, 3:4 composition, visual continuity, title-safe placement, and any visible embedded text. Deliver only completed-task facts: artifact links, dimensions, format, resolved model, task IDs, and billing.net_charged_credits. Present the ordered note, slide roles, title ideas, caption beats, fact checklist, tag set, and at most one focused unexecuted revision suggestion.

Reading Xiaohongshu before you write

Optional, and paid. When the connection exposes Beatra's public social lookup, this Skill can read Xiaohongshu directly instead of working from what the user remembers: one page of notes matching a keyword, one specific note the user pastes, one page of that note's top comments, and an account's profile or recent notes. Six operations, Xiaohongshu only.

Every one of them costs 60 credits, and there is no cheap operation on this platform to fall back on. The same reads cost 6 on TikTok. They cost 6 on Douyin too — except Douyin's own keyword search, which is also 60, so do not say "ten times Douyin" without naming the read. A three-step read — the field, one note, that note's top comments — is 180 credits, and every further page is another 60. Say the number before offering anything, confirm each lookup on its own before it runs, and say plainly that this Skill's own deliverable arrives either way at no cost. Offer one read, not a plan of four.

The rule is the whitelist, not a list of exceptions: a platform with no operation on it cannot be looked up from here, and another platform's notes are never presented as Xiaohongshu's. A returned image URL is not a viewed image — state a visual finding only about an image the host can actually open. Every figure that reaches the work is labelled as looked up with the time it was read, or as supplied by the user, or as missing. Nothing is estimated, and nothing is carried in from what notes in this category usually do.

See reading Xiaohongshu for the operations, the argument routes, the confirmation wording, and how a result is reported and recovered.

References by task

• Local-business note planning: business card, slide roles, factual inputs, and post angles.
• Local-business workflow: source-photo, concept, and edit routes; confirmation; task recovery; and review.
• Installation and authentication and installation registration: first use and credentials.
• Tasks and results and billing, errors, and recovery: returned task fields, balance, validation, and structured errors.
• Bundled MCP Client diagnostics and uninstall and disconnect: client operation and removal.

Runtime and safe automatic updates

The bundled client silently checks at most once every 24 hours per installation. When a newer release is available, it installs automatically without separate confirmation. It uses only fixed official Beatra discovery and immutable CDN paths. Before replacement, it verifies discovery data, manifest, archive, and every packaged file against expected identity, size, and SHA-256 values, then replaces only package-owned files in the installed Skill directory.

Checks, downloads, verification, replacement, rollback, and recovery fail open: the current installation stays usable and the original command continues. The setting persists for this installation. Read automatic updates and safety for the official sources, integrity checks, replacement boundary, failure behaviour, and controls.

python3 scripts/mcp_client.py update --auto off
python3 scripts/mcp_client.py update --auto on
python3 scripts/mcp_client.py update --check