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Vidova

by ai.vidova
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Cover private details

cover_private

Find every private detail in what a film clip plays and cover each with an opaque black box that follows it on every frame, its corners as it turns: shipping and address labels, receipts, payment cards, number plates, IDs, parcel barcodes, and any screen or document showing a person's name, address, email, phone, order or tracking number, card number or one-time code; faces too with faces true. Use it for every request to hide, blur, censor, mask or redact private information, and for footage that shows such details when the edit is to be posted: never cover them by hand with a blur or a fixed box. A model looks at one frame a second, the details are carried through the frames between, it looks again where one was lost, and checks frames half way between; each detail gets its own object track and a black-box region pinned to it on a new track in front of the clip. It answers each detail with its times and the track and cover it wrote. Uses about 2.3 credits a frame looked at (about two looks a second) and about 61 credits a minute of video carried.

Input Schema

NameRequiredDescriptionDefault
facesYestrue to cover people's faces too; null or false covers only private details, not people.
clipIdYesThe id of the video clip on the film whose private details to cover (read_film lists the clips).
atSpaceYesWhat startSeconds and endSeconds are. null or source: seconds of the clip's video. timeline: seconds of the film while the clip plays.
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.
endSecondsYesWhere to stop, in source seconds of the clip's video; null to the clip's last frame.
startSecondsYesWhere to start, in source seconds of the clip's video, inside what the clip plays; null from the clip's first frame.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / atSpace
      Added value: +{
+  "anyOf": [
+    {
+      "enum": [
+        "source",
+        "timeline"
+      ],
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "description": "What startSeconds and endSeconds are. null or source: seconds of the clip's video. timeline: seconds of the film while the clip plays."
+}
    • changedInput schema / required
      Previous value: -[
-  "clipId",
-  "startSeconds",
-  "endSeconds",
-  "faces",
-  "projectId"
-]New value: +[
+  "clipId",
+  "startSeconds",
+  "endSeconds",
+  "faces",
+  "atSpace",
+  "projectId"
+]
  2. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly=false, destructive=false), and the description adds rich behavior beyond that: model samples one frame a second, details carried between frames, re-checks, per-detail object tracks, black-box region on a new track in front of the clip, and credit cost (~2.3/frame, ~61/minute). This is unusually thorough behavioral disclosure.

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

Conciseness3/5

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

The purpose is front-loaded, and the cost sentence earns its place, but the body is a dense run-on stitched with semicolons that buries the operational details. Structure could be tightened without losing content.

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?

There is no output schema, but the description explains the return value ("answers each detail with its times and the track and cover it wrote"). Combined with cost, processing model, and full parameter coverage, an agent has everything needed to call it correctly.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all six parameters including the faces/atSpace/projectId semantics. The description reinforces that faces being true also covers people but adds no format or edge-case detail beyond the schema, so the baseline 3 applies.

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 specific verb (find and cover) and resource (private details in what a film clip plays), and enumerates the concrete detail types (labels, receipts, cards, plates, IDs, barcodes, screens, faces). An agent can clearly separate this from siblings like track_faces, track_box, or cutout_subject.

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?

"Use it for every request to hide, blur, censor, mask or redact private information" plus the condition "when the edit is to be posted" gives explicit when-to-use. It also states when-not: "never cover them by hand with a blur or a fixed box," routing the agent away from manual alternatives.

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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