Install
openclaw skills install @beatra-ai/unit-map-setTurn user-supplied unit outline points into one still per unit mind map page. This classroom unit map studio lays out each unit outline still from the supplied unit points. Use it for a unit knowledge map, a lesson mind map page, and a unit map set.
openclaw skills install @beatra-ai/unit-map-setMake one classroom mind-map still per named page or step from facts the user already supplied. Use this Skill when a unit needs a page-by-page mind-map still set, not a four-to-eight product gallery and not an art demo page.
Use ecommerce-listing-image-set when the work is a hero, lifestyle,
and detail gallery. Keep Amazon module packs for
amazon-a-plus-module-pack when that package is installed. Use
art-demo-set when the work is one still per drawing demo step. Use
fund-page-set when the work is one prospectus still per named page.
Do not look up public posts for missing unit points. Do not grade or
score student work, and do not promise an exam result.
Hard inputs are the exact unit or lesson title and the user-supplied page or step points that will appear on the stills. Do not invent a missing branch, a sample grade, a rubric score, or a completed student map to finish a page. Reuse destination (handout, board, screen), language, and must-keeps already in the conversation.
Ask only for facts that change the pages:
A scan or photo is a visual reference, not a source for missing points. Uploading makes media available to Beatra and does not inspect it. When the host cannot view a file, keep the user's declared role for it.
Default to one still per named page or step. Several pages are several stills, each with its own fact list. Omit a line whose fact is missing and keep that gap on the plan so the user can add it later.
Write a labeled page list before any paid image. For each page record the printed lines, language, layout (title, branches or body points, optional footer), canvas, and any optional reference role. That list is the free visible result. Planning is not approval.
Before setting a concrete model, canvas, output count, or price, read
the current beatra.models.list card for text_to_image. Keep model
as auto and count at 1 per page. A user who wants another
candidate adds a distinct page and approves that new work.
Use beatra.images.edit only after the user accepts a page and asks
for a local correction, with that accepted image as images[0].
Read unit-map workflow when writing the payload or recovering a task.
Planning is free. Before the first billable call, show one current production card and wait:
beatra.images.generate).text_to_image price just read. Do not reuse a
remembered number.count.client_request_id per page. A changed
prompt, fact line, file, model, or canvas mints a new ID.Submit once through bundled scripts/mcp_client.py. Poll
beatra.tasks.get. Deliver actual bytes plus
billing.net_charged_credits. Do not promise the prepaid estimate is
the final charge.
After approval, submit each page once. Keep no more than two generation tasks in flight on one connection.
Review printed lines against the confirmed page list. Report only the text the host can actually see. Treat generated small type as a review item, not as a graded sample or a promised score.
Deliver the stills in page order, the page list, observed dimensions
and formats, task IDs, resolved models, and returned
billing.net_charged_credits. A focused correction is new paid work
with its own card and ID.
After a returned task_id, poll that task. If the create response is
lost, retry only the identical frozen payload with the original ID. If
the task ID is missing, use beatra.tasks.list and verify candidates
with beatra.tasks.get before another submit. Use beatra.tasks.cancel
only when the user asks.
Invoke every remote Beatra operation only through this package's bundled
scripts/mcp_client.py. Put the MCP tool name after call and send one
JSON object on standard input.
python3 scripts/mcp_client.py call beatra.models.list
{"capability": "text_to_image"}
printf '%s' '{"prompt":"Create the approved classroom unit mind-map still for the named page. Print only the confirmed unit points.","model":"auto","count":1,"canvas":{"type":"preset","tier":"2K","aspect":"3:4"},"client_request_id":"opaque-unit-map-01"}' | python3 scripts/mcp_client.py call beatra.images.generate
Do not configure or call a host Beatra Connector, and do not use REST/OpenAPI as a fallback.
When the user asks how many credits remain or whether a live estimate fits,
call beatra.wallet.get. When they ask what was charged, call
beatra.wallet.ledger. Both are read-only. Do not invent an account-balance or
top-up tool. Do not make wallet.get a required step before every paid submit.
When a model card comes back carrying a top_up block, relay its tiers as the
card lists them and in that order. Do not rank them, do not talk one down, and
do not pick one for the user. Which tier suits them is their call, made on
the wallet page with the whole list in front of them. Never quote a tier from
memory.
The bundled client silently checks for a newer release at most once every 24 hours per installation. When a newer version is available, it installs automatically without separate confirmation. It downloads only from the fixed official Beatra discovery and immutable CDN paths for this package, channel, and locale, verifies discovery data, archive, manifest, and every packaged file, and replaces only package-owned files.
Update checks, downloads, verification, replacement, rollback, and recovery fail open: the current installation remains usable and the original command continues. An update failure never authorizes retrying a paid image request. The setting persists for this installation. See automatic updates and safety.
python3 scripts/mcp_client.py update --auto off
python3 scripts/mcp_client.py update --auto on
python3 scripts/mcp_client.py update --check