Skip to main content
Glama

switch

by ai.switchapp

Suggest Speech Seconds

suggest_speech_seconds
Read-onlyIdempotent

How many seconds a video clip should be for a spoken line, so the words are never rushed or dragged. Give it the spoken text (or a word_count) and it returns a suggested duration for four delivery energies: slow and dramatic, natural, upbeat, and super charismatic talking-with-your-hands. Fewer seconds is a faster more excited delivery; more seconds is slower and more dramatic. Deterministic, free, no charge. Use it whenever a user asks how long to make a clip for their narration or dialogue, or which duration to pick for a given energy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoThe spoken words. The tool counts them for you.
word_countNoUse instead of text if you already know the number of spoken words.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint; the description adds 'Deterministic, free, no charge' and explains that the tool returns a set of four duration values keyed to delivery energy. It does not cover edge cases like omitting both inputs, but it does not contradict the annotations.

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?

Four sentences front-load the purpose, then cover input options, output semantics, and intended usage. 'Deterministic, free, no charge' adds useful cost and reliability context, though it is slightly extra; overall the description is tight and scannable.

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?

For a simple read-only calculator with 100% parameter coverage and helpful annotations, the description covers inputs, output content, and usage context. It could clarify what happens if neither text nor word_count is provided or detail the exact response shape, but neither is essential for selecting and invoking it.

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 100% and both parameters are already well-described: text is the spoken words and word_count is an alternative when the count is known. The description mostly restates this relationship ('Give it the spoken text (or a word_count)') without adding significant new parameter-level detail.

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 opening sentence states what the tool computes: 'How many seconds a video clip should be for a spoken line.' It further specifies that it returns suggested durations for four named delivery energies, making its function distinct from the many media-generation and analysis siblings.

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 explicitly says 'Use it whenever a user asks how long to make a clip for their narration or dialogue, or which duration to pick for a given energy.' It gives clear context but does not mention when not to use it or name alternatives, though none of the siblings appear to serve this exact purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All switch toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

Several tools occupy nearly identical semantic ground: apply_iphone_realism and apply_ugc both describe casual phone-shot looks, upload_media and upload_reference_asset both accept uploads, and analyze_video overlaps heavily with analyze_video_report. The many apply_* style tools are essentially one tool parameterized by style, so agents can easily select the wrong one.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern such as generate_image, list_my_videos, get_editor_run, and upscale_video. A few outliers like voice, talking_avatar_video, and video_to_prompt do not use the same verb-first convention, but they are still readable and do not create significant confusion.

Tool Count1/5

At 55 tools, the surface is far beyond what is appropriate for an MCP server; many of these be collapsed or parameterized, especially the 10 apply_* style wrappers and several overlapping upload/status helpers. Even for a broad media platform, this scale forces a huge context window and makes selecting the right tool impractical.

Completeness2/5

The surface covers generation, media display, video analysis, and Editor workflows well, but there are obvious gaps in library lifecycle management: move_asset and create_folder are referenced in tool descriptions without being exposed, and there is no clean way to delete or reorganize media assets. Agents following the descriptions will try to call tools that do not exist.

Resources