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AwesomeVideo

by com.awesomevideoeditor
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Remove silences and filler words

remove_silences
Idempotent

Paid: 3 credits per kept minute, plus 4 per kept minute with burnCaptions (same as burn_captions). Removes silences and filler words from a talking video and returns the cut MP4, retimed SRT/VTT/JSON captions, and stats (sourceSeconds, keptSeconds, removedSeconds, cuts, fillersRemoved). Needs a transcript: pass transcriptionJobId (from transcribe or caption_video) or subtitles. Silences: gaps between words over silenceGapSeconds (default 0.5 s) are cut, keeping paddingSeconds (default 0.08 s) on each side; ffmpeg silencedetect (silenceNoiseDb, default -35) also cuts long pauses inside word timings (detectSilences:false to skip). Fillers (default fillerMode 'clear'): uh, um, er, ah, eh, ehm, em, hmm, mm, and Spanish 'este' only when said on its own. fillerMode 'aggressive' also cuts like, you know, I mean, basically, kind of, sort of, o sea, bueno, pues, digamos, tipo, como que, a ver, only when they stand alone (comma or pause). fillers adds words or phrases; keepFillers keeps some; removeFillers:false keeps all. Every cut gets a short audio fade so joins do not click. burnCaptions:true burns the retimed captions in the same job with preset/brandPresetId/platform/autoFit (same renderer as burn_captions). Billed on the kept duration.

Input Schema

NameRequiredDescriptionDefault
fileIdNo
presetNoWith burnCaptions: preset id or name (or custom:cp_...). Default Clarity.
autoFitNo
fillersNoExtra fillers to always cut, words or phrases.
mediaUrlNo
platformNoWith burnCaptions: tiktok, reels, shorts, ... for safe zones.
faceAvoidNotrue = move captions off faces (samples faces at 2 fps, same price; result.faceAvoid.faceLayout). Shortcut for styleOverrides.faceAvoid.
quoteOnlyNoFree: return the price for durationSeconds without starting a job or charging (upper bound: every second kept).
subtitlesNo
fillerModeNo
maxCreditsNo
keepFillersNoFillers to keep, e.g. ['like'].
burnCaptionsNoBurn the retimed captions in the same job.
brandPresetIdNo
removeFillersNo
detectSilencesNoDefault true: ffmpeg silencedetect also cuts long pauses.
highlightColorNo#RRGGBB for highlightWords. Default #FACC15.
highlightWordsNoShortcut: words or phrases to color in every caption (accent/case-insensitive), e.g. ["AwesomeVideo", "gratis"]. Maps to styleOverrides.wordHighlights rule {id:"custom", words, color}. Same price.
paddingSecondsNoKept on each side of a cut. Default 0.08.
silenceNoiseDbNoSilence threshold in dB. Default -35.
styleOverridesNoPer-call style changes deep-merged onto the preset (same fields as list_presets style; null removes a field), validated with the renderer schema and bundled fonts. Example {"fontSize":72,"maxWordsPerCaption":2,"wordEntrance":"bounce"}. Same price. No need to save_custom_preset. Every field with examples: get_style_reference.
durationSecondsNoSource length for quoteOnly.
silenceGapSecondsNoCut pauses longer than this. Default 0.5.
transcriptionJobIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations, the description discloses pricing and billing basis, returned outputs and stats, the transcript requirement, fade-on-cut behavior, and how optional caption burning reuses the burn_captions renderer. These are material behavioral details for a paid media-processing job.

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

Conciseness4/5

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

The description is dense but front-loads cost, output, and transcript requirements before moving into silence and filler mechanics. The length is largely justified by 24 parameters, though the long single block could be easier to scan with clearer segmentation.

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

Completeness5/5

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

For a complex 24-parameter tool with no output schema, the description is sufficiently complete: it enumerates the return artifacts and stats, states the transcript requirement, explains billing, and covers the main processing modes. Remaining gaps are covered by schema descriptions.

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

Parameters4/5

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

With schema coverage at 63%, the description compensates substantially by explaining defaults and effects for silenceGapSeconds, paddingSeconds, silenceNoiseDb, fillerMode, fillers/keepFillers/removeFillers, burnCaptions, transcriptionJobId, and subtitles. It leaves source selection (fileId/mediaUrl), maxCredits, quoteOnly, highlightWords, faceAvoid, and styleOverrides mostly to the schema, so it is strong but not complete.

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 verb and resource: removes silences and filler words from a talking video. It distinguishes itself from burn_captions by making caption burning optional and by requiring a transcript, and it names the returned artifacts, so an agent can identify the tool without opening the schema.

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?

It clearly states the transcript prerequisite (transcriptionJobId from transcribe or caption_video, or subtitles) and explains several behavioral switches such as detectSilences:false, removeFillers:false, and fillerMode 'aggressive'. It does not explicitly compare the tool against trim or burn_captions for adjacent use cases, which keeps it from a 5.

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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