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Build Clip Prompt Plan

lab_clip_bauplan
Read-only

Turn a structured clip plan into a sectioned video prompt (style, references, world, camera, timestamped beats with a living tail, title, sound, continuity) and check it before any paid run: beats past the duration, overlaps, a title after the end, a cut inside a one-shot, an unknown @image tag. startbar=false means a hard finding. anschluss is the opening for the NEXT clip of a chain; pass the previous plan as vorher to get the opening this clip inherits. Free, no model call. Paste prompt into lab_animate or lab_verkettung.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "bauplan": "<bauplan>"
    },
    "name": "lab_clip_bauplan"
  }
}

Input Schema

NameRequiredDescriptionDefault
vorherNo
bauplanYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations only declare readOnlyHint, and the description adds real behavioral value: free, no model call, an enumerated list of validation checks (duration overruns, overlaps, late title, cut in a one-shot, unknown @image tag) and the meaning of `startbar=false`. It stops short of describing the shape of the returned plan or the exact wording of findings.

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 core action and the cost signal, with the parenthetical section list and validation list packed efficiently. The final two sentences on `anschluss`/`vorher` and the paste target are slightly compressed and read as an afterthought rather than being structured.

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

Completeness4/5

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

With no output schema, the description does the work of explaining what comes back (a sectioned prompt plus findings and a `startbar` flag) and what to do with it next. It would be complete if it sketched the returned object's fields beyond `prompt`, `startbar`, and `anschluss`.

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?

The description carries the key semantics the schema cannot: `vorher` is the previous plan of a chain, and passing it determines the opening this clip inherits (`anschluss`). The reported schema description coverage is 0%, so this explanation of the chaining parameter is exactly the compensation needed, though the contents of `bauplan` are not summarized in prose.

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 and resource ('turn a structured clip plan into a sectioned video prompt') plus a second function (validating it), and enumerates the sections produced. It also implicitly separates itself from lab_animate/lab_verkettung by noting it is free and makes no model call, while those are the paid consumers of its output.

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

Usage Guidelines4/5

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

Gives a clear context of use ('check it before any paid run') and explicit downstream routing ('paste `prompt` into lab_animate or lab_verkettung'). It does not state when a caller would skip this tool entirely, so the exclusion side is left implicit.

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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