Skip to main content
Glama

auto_rough_cut

Generate a rough cut video timeline from source clips filtered by keywords, with control over duration, pacing, and segment structure. Uses FCPXML input to produce a targeted rough cut output.

Instructions

Generate a rough cut from source clips based on keywords, duration, and pacing

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filepathYesSource FCPXML with clips
output_pathYesWhere to save rough cut
target_durationYesTarget length (3m, 00:03:00:00)
pacingNomedium
keywordsNoFilter clips by keywords
segmentsNoSegment structure [{name, keywords, duration_seconds}]
priorityNobest
favorites_onlyNo
add_transitionsNo
Behavior2/5

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

No annotations are provided, placing full burden on the description. It only states 'generate a rough cut' without disclosing side effects (e.g., file modification, permissions, destructiveness). The input schema hints at output_path but does not reveal behavior beyond creation.

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 description is a single sentence, concise but overly brief for a tool with 9 parameters. It covers the essential purpose but omits necessary details, making it efficient but under-informative.

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

Completeness2/5

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

With 9 parameters, no output schema, and no annotations, the single-sentence description is clearly incomplete. It fails to explain how segments, priorities, transitions, or other options affect the rough cut.

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

Parameters2/5

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

Schema coverage is 56%, yet the description only mentions three parameters (keywords, duration, pacing) without adding meaning to the others (e.g., filepath, output_path, segments, priority). It fails to compensate for the moderate coverage gap.

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?

Description clearly states the verb 'generate' and resource 'rough cut' from source clips, and mentions key parameters (keywords, duration, pacing). It distinctly differs from sibling tools like 'generate_montage' or 'analyze_pacing'.

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

Usage Guidelines3/5

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

No explicit guidance on when to use this tool versus alternatives such as 'generate_montage' or 'analyze_timeline'. The description implies usage for rough cut creation but lacks when-not-to-use context or prerequisites.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DareDev256/fcpxml-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server