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Propose surfaces to put things on

propose_surfaces

Find flat surfaces to put something on, in a video or an image: a sign, a screen, a poster, a wall. Each proposal has an id, its four corners at the seed frame in source, film and film_norm, its true width over height when the perspective shows it, how well it is outlined and how trackable it is (edges or features), and, for a video, followed by a tracker over the whole range: the range where all of it stays in the frame, and the stretches where it is lost (not found near where it was). What passes in front of it is for track_occluders on the track. A sheet shows the proposals numbered on the seed frame. Then track the one you pick with track_plane({fromProposal:"sf_...", ...}): its corners and seed time come from the proposal. With query, the surface is looked for inside the boxes find_objects draws for those words; without, the best outlined flat shapes win. Example: propose_surfaces({assetId:"vid_street", clipId:null, query:"blank sign", at:{seconds:null, atSpace:null}, startSeconds:null, endSeconds:null, maxResults:null, detail:null}). It reads up to 19 frames and takes a few seconds. It uses no credits. Proposals last a day.

Input Schema

NameRequiredDescriptionDefault
atYesThe seed frame. seconds null: the best of three frames across the range.
queryYesWhat surface to find, in a few words: "blank sign", "billboard", "laptop screen", "phone screen", "poster", "wall", "table top". null proposes the flattest, best outlined surfaces it sees.
clipIdYesA clip: looks at its asset over the part the clip plays, and maps the surfaces to the film. Else null.
detailYesHow much the answer says: brief is one line per result with its ids; normal (null) adds the transform; full adds every matrix of the chain.
assetIdYesThe video or image to look at. null with clipId reads the clip's asset.
projectIdYesThe project this call runs on without changing the open project. null (or leaving it out) uses the open project. wait_for_jobs takes the projectId of the calls that started the jobs.
endSecondsYesEnd of that range. null: the end of the clip, or of the asset.
maxResultsYesSurfaces to propose, 1 to 10. null: 5.
startSecondsYesStart of the range to follow the surfaces over, in at.atSpace seconds. null: the start of the clip, or of the asset.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=false and destructiveHint=false, so the description carries the real burden and does well: it discloses cost ('uses no credits'), latency ('reads up to 19 frames and takes a few seconds'), state lifetime ('Proposals last a day'), that a numbered sheet is produced, and precisely what each proposal contains. The only gap is that it never explains why the call is a non-readOnly mutation beyond the ephemeral proposals.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose and the sibling routing before the dense return-value sentence. The middle sentence listing every proposal field is a long run-on chain that takes effort to parse, and the fully-null example call is only mildly useful, but nothing is truly wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description fully compensates by enumerating the return contents (id, four corners in source/film/film_norm, width-to-height, outline quality, trackability, tracker range and lost stretches, numbered sheet). Combined with cost, timing and proposal lifetime, an agent has everything needed to call it and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning the schema does not: query drives the find_objects-box search path versus default flat-shape selection, and the seed frame / start-end range govern what gets proposed versus tracked. It also restates defaults (max 5, 1-10) that are already in the schema, so it is additive rather than fully compensating.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource ('find flat surfaces... a sign, a screen, a poster, a wall') in a video or image, and separates itself from siblings by saying the surface is looked for inside boxes that find_objects draws and that the picked one is followed by track_plane. An agent can distinguish it from find_objects, track_plane and track_occluders without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit routing: with a query the search is constrained to find_objects boxes, without one the best outlined flat shapes win; occluding content is explicitly deferred to track_occluders, and following the chosen proposal is deferred to track_plane with fromProposal. When to pass a query and when to leave it null is spelled out with examples.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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