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Premiere Pro MCP Server

Analyze Dialogue Edit Candidates

analyze_dialogue_edit_candidates
Read-onlyIdempotent

Analyze transcript segments and local silence ranges to generate deterministic dialogue-edit candidates, flagging filler words and silence gaps for review.

Instructions

Analyze caller-supplied, revision-bound transcript segments and optional local silence ranges for deterministic dialogue-edit candidates. It never calls a model, persists transcript text, or changes Premiere.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
segmentsYesNormalized transcript segments with stable IDs, source IDs, transcript revisions, time ranges, text, and optional speaker labels.
filler_wordsNoExact normalized filler words or phrases to flag for review.
silence_rangesNoOptional source-time silence ranges returned by local analysis.
minimum_silence_secondsNoMinimum silence duration to return; defaults to 0.7 seconds.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether the tool completed successfully.
dataNoTool-specific result data when ok is true; on failure, diagnostic detail when the tool provides it.
toolYesThe registered MCP tool name.
errorNoFailure detail when ok is false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.18.6
    • changedOutput schema / properties / data / description
      Previous value: -"Tool-specific result data when ok is true."New value: +"Tool-specific result data when ok is true; on failure, diagnostic detail when the tool provides it."
  2. Addedv1.14.9

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: it never calls a model (deterministic), never persists transcript text (privacy), and never modifies Premiere. That is real added context, though return-value characteristics are left to the output schema.

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?

Two tight sentences, front-loaded with the purpose and followed by the negative guarantees. No filler; every clause earns its place.

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 annotations, a rich 100%-covered schema, and an output schema, the description supplies the remaining pieces an agent needs (determinism, no persistence, no Premiere mutation). It is complete for invocation; it stops short of describing expected output shape or pitfalls like oversized segment arrays.

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%, so the schema documents all four parameters, including the revision pattern and default minimum_silence_seconds. The description only echoes 'revision-bound transcript segments and optional local silence ranges' without adding syntax or format detail beyond the schema, which is the baseline-3 case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (analyze) and resource (dialogue-edit candidates), and pins down the inputs as caller-supplied, revision-bound transcript segments plus optional silence ranges. It's clear what the tool does, though it does not name the adjacent siblings (plan_filler_word_removal, plan_pause_tightening, detect_silence) that an agent might confuse it with.

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?

Usage is implied by the required inputs (you need transcript segments from get_clip_transcript_uxp), but there is no explicit when-to-use vs. alternatives guidance or exclusion criteria. The agent can infer the context but is not routed.

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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