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Remove filler words

remove_filler_words

Remove filler words (needs transcript). Default list: um, umm, uh, uhh, uhm, erm, er, ah, ahh, hmm, hm, mm, mhm, eh, ee, eee, eem, mmm, aaa, ja ja, äh, ähm, öh, eh, este, euh, bah. Pass fillers to replace or extra to extend (multi-word like "you know" OK).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "remove_filler_words"
  }
}

Input Schema

NameRequiredDescriptionDefault
extraNo
fillersNo
paddingNo
projectIdNoProject to act on (default: the open one)
rippleTrackIdsNoTracks to cut/ripple (default: all unlocked tracks). Lock a music track to keep it continuous.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the description's main added value is the prerequisite and the default word list. It does not say whether removal ripples the timeline, whether adjacent clips are joined, or whether the operation is reversible, which matters for a mutation on a transcript-driven edit.

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 action and prerequisite are correctly front-loaded, and the parameter guidance at the end earns its place. But roughly half the text is a 28-entry enumeration of filler words that an agent will almost never need to reason about, crowding out more valuable behavioral detail.

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

Completeness3/5

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

The definition is workable but leaves gaps for a 5-parameter mutation with no output schema: "padding" is unexplained, ripple semantics hinted at by rippleTrackIds are not described, and the result of the edit (what happens to the removed spans) is unstated. An agent can call it, but cannot fully predict the outcome.

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 coverage is only 40%, and the description usefully covers the two undocumented list parameters, explaining that "fillers" replaces the default set, "extra" extends it, and multi-word entries like "you know" are allowed. The other undocumented parameter, "padding", is never mentioned, leaving one of five parameters with no meaning in either schema or description.

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+resource ("Remove filler words") and disambiguates the scope with the parenthetical prerequisite "(needs transcript)". However, it does not distinguish itself from close siblings such as delete_words, keep_words, or remove_silences, so an agent cannot tell from the description alone which of those overlapping edit operations to pick.

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?

"needs transcript" is a genuine precondition the agent can act on, and "Pass fillers to replace or extra to extend" implies two usage modes. But there is no explicit when-to-use versus delete_words/remove_silences, no statement about what happens when no transcript exists, and no guidance on when the default list is sufficient.

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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