Valmera — AI Video Editor

Remove filler words

remove_filler_words

Idempotent

Removes timestamped filler tokens from speech using detected word boundaries. The default targets non-word hesitations; an explicit word list can select other tokens.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

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

Input Schema

Name	Required	Description	Default
`words`	No
`project_id`	Yes	Explicit project identifier for this request. The connection's navigation pointer does not select the target.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 6, 2026

changedInput schema / properties / project_id / description

Previous value: -"Required immutable scope for this call. Copy the id from list_projects/open_project/project_state; the active-project pointer is never used to guess."New value: +"Explicit project identifier for this request. The connection's navigation pointer does not select the target."

First observedSep 9, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare idempotentHint=true, destructiveHint=false and readOnlyHint=false, so the agent knows it is a repeatable in-project edit. The description adds the useful dependency that removal relies on "detected word boundaries" (transcript-derived), but says nothing about what happens when no boundaries exist or whether the edit is reversible beyond the idempotency hint.

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 sentences, front-loaded with the action and mechanism, then the default/override behavior. No filler wording of its own; every clause carries information.

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?

For a small two-parameter mutation with an annotated safety profile and no output schema, the description covers what is removed and how the parameter alters behavior. It still leaves out prerequisites (does a transcript/word-boundary pass need to run first?) and the result of the operation, which an agent must know before calling.

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?

Schema coverage is 50%: project_id is well documented in the schema, while the undocumented `words` parameter is exactly what the description explains - that omitting it targets non-word hesitations and supplying it selects other tokens. That adds genuine meaning the schema lacks, though it doesn't address matching rules (case, phrases, multi-word entries).

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?

"Removes timestamped filler tokens from speech using detected word boundaries" gives a specific verb and resource with scope (speech/transcript tokens). It implicitly separates itself from sibling cleanup tools like remove_punctuation and cut_silences, but never names them, so differentiation is by inference rather than explicit contrast.

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?

The second sentence explains the default behavior (non-word hesitations) versus supplying an explicit word list, which is real usage guidance for the optional parameter. It does not say when to prefer this tool over remove_punctuation or cut_silences, nor any prerequisite such as an existing transcript.

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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