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ae_transcript_to_cuts

Convert a timed transcript into KEEP segments for editing: strip fillers and stutters, add padding around speech, and generate cleaned text plus SRT subtitles.

Instructions

From a timed transcript, remove fillers (um/uh/like/you know/…) and stutters (repeated words), then build KEEP timeline segments with pad_before/pad_after so cuts have a little breathing room. Pass segments to ae_build_smart_edit. Also returns cleaned text + SRT for subtitles (use ae_create_subtitle — no black bars).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
merge_gapNoMerge words into one run if gap under this (seconds)
pad_afterNoSeconds of handle after each speech run (default 0.18)
pad_beforeNoSeconds of handle before each speech run (default 0.12)
transcriptNoFull transcript object from ae_transcribe_video (full_transcript field)
extra_fillersNoAdditional filler words to strip
remove_fillersNo
remove_stuttersNo
transcript_pathNoPath to transcript JSON file instead of inline object
aggressive_fillersNoAlso strip discourse fillers: like/basically/actually/well/yeah (default false — keeps natural speech words)
Behavior4/5

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

With no annotations provided, the description carries the full burden of explaining behavior, and it does so clearly: it removes filler words and stutters, builds KEEP segments using pad_before/pad_after, and returns cleaned text plus SRT. It also signals that the tool does not directly build the final edit, since segments are passed to ae_build_smart_edit. It does not explicitly discuss side effects or project mutations, but its processing-oriented nature makes the behavior reasonably transparent.

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?

Three focused sentences front-load the core transformation, then give the downstream step and the subtitle output. There is no filler, and each sentence adds useful routing or behavioral 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?

Even without an output schema, the description explains the main outputs: KEEP segments to pass to ae_build_smart_edit, cleaned text, and SRT. It also clarifies that subtitle creation should go through ae_create_subtitle. It does not detail the exact return structure, but for a high-level pipeline tool the behavioral and routing information is largely sufficient.

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 78%, so most parameters are already explained in the schema. The description adds useful context for pad_before/pad_after ('so cuts have a little breathing room') and clarifies what filler/stutter removal means, but it does not systematically elaborate on every parameter. Baseline 3 is appropriate because the schema does most of the work.

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 states a specific transformation: turn a timed transcript into cleaned KEEP timeline segments with padding, while removing fillers and stutters. It names the input resource (timed transcript), the output artifact (segments, cleaned text, SRT), and points to a downstream sibling (ae_build_smart_edit), making its role in the pipeline unmistakable.

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 description gives clear workflow context: it is used after transcription and produces segments to pass to ae_build_smart_edit, and it explicitly routes subtitle creation to ae_create_subtitle instead. It does not explicitly state when not to use it relative to other edit-building tools like ae_build_youtube_edit or ae_analyze_cuts, so it lacks full exclusionary guidance.

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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