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Derive Shots From Scenes

lab_shots_ableiten
Idempotent

Derive the shot layer from what the clips already say about themselves — consecutive clips of the same scene become one shot, and a scene that returns later becomes a second one (one location cut into twice is two shots). Costs nothing: it groups rows and reads titles, it generates nothing. Titles come from the project's shotlist where the scene is in there, so this is more than a regrouping — it fetches meaning the pipeline already produced. SHOTS YOU SET BY HAND SURVIVE. Only derived ones are replaced, and clips already held by a manual shot are left out of the grouping entirely — a derivation does not take handwork's material away. Read clips_ohne_szene in the answer: those clips say nothing about where they belong, so each became its own shot. That number is a job for the pipeline, not a fault of this call — and grouping two nameless clips would be a claim about connection that nobody made.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seq_idYesSequence id (from lab_create_sequence/lab_list_sequences) — positive integer as string

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations mark this as a non-read-only but idempotent and non-destructive write; the description elaborates exactly what gets overwritten (only derived shots), what survives (manual shots, whose clips are excluded from grouping entirely), and that it costs nothing because it generates nothing. This is rich behavioral disclosure beyond the structured hints and is consistent with them.

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?

Front-loads the mechanism well, but the prose is long and stylized, with several em-dash-broken sentences that could be tightened. Most sentences carry real information (cost, manual survival, clips_ohne_szene) but the density is high and the structure is discursive rather than crisp.

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 usefully explains a return field (`clips_ohne_szene`) and why those clips each became their own shot, which is valuable for interpreting results. It doesn't fully describe the response shape, but for a one-parameter idempotent tool it is largely complete.

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 description coverage is 100% for the single seq_id parameter, which the schema already documents as a sequence id from lab_create_sequence/lab_list_sequences. The description adds nothing about the parameter, 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 (derive) and resource (the shot layer) and even spells out the algorithm: consecutive clips of one scene become a shot, and a returning scene becomes a second. It implicitly distinguishes itself from manual sibling lab_shots_setzen by explaining that hand-set shots survive and only derived ones are replaced.

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 clear context for when this applies (clips that already declare their scene) and routes away from the manual path by noting hand-set shots are preserved. It stops short of an explicit when-not or a direct naming of the alternative tool (lab_shots_setzen), so the routing is inferable rather than spelled out.

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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