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Stockfilm — Authentic Vintage Footage

build_rough_cut

Read-only

Auto-assemble a timed sequence of vintage clips into a video timeline based on a description. Returns an ordered list of clips with durations. Great for creating edit lists or storyboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paceNoEditing pace: slow (4-8s/clip), balanced (3-6s/clip), fast (2-4s/clip)
queryYesNatural language description of the video sequence (e.g. 'american road trip summer vacation 1960s')
year_toNoLatest year filter
year_fromNoEarliest year filter
target_secondsNoTarget timeline length in seconds (20-600, default 60)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / title
      Removed value: -"RoughCutRequest"
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover readOnlyHint=true and destructiveHint=false, so safety is clear. The description adds useful behavioral context by stating the tool auto-assembles and returns an ordered list with durations, which is not present in the annotations. There is no contradiction with the annotations.

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

Conciseness5/5

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

The description is three short sentences with no filler. It front-loads the action, then states output and use case, and every sentence adds useful information.

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 complete parameter descriptions, read-only/open-world annotations, and a clear statement of the return value, an agent has enough to call the tool correctly. A concrete output example or mention of edge cases would improve completeness, but they are not essential for this tool.

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?

All five parameters have schema descriptions, including pace ranges, year filters, and target_seconds bounds, so the schema carries most of the semantic weight. The description's mention of 'based on a description' and 'timed sequence' lightly reinforces the query and timing parameters but adds no new detail beyond the schema. Baseline 3 is appropriate.

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?

The description names a specific verb and resource: 'Auto-assemble a timed sequence of vintage clips into a video timeline based on a description.' It also states the core deliverable, an ordered clip list with durations. This clearly distinguishes it from sibling tools like search_vintage_footage or license_clip.

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?

The phrase 'Great for creating edit lists or storyboards' gives a clear intended use case. It does not explicitly mention when not to use the tool or name alternative tools, but the edit-list/storyboard context is enough to guide selection among the provided siblings.

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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