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Hermoso

by io.github.hermoso-ai

Change narrator voice

change_voice

Swap the narration of a finished video into a different voice — keeps the performance, lip-sync, and background sound. Use when the user likes the video but wants a different narrator voice; use dub_video only for language translation. Paid; returns the served URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoYesthe source video URL
voiceNotarget narrator voice preset name, e.g. 'Aria', 'George', 'Rachel', 'Sarah', 'Brian', 'Charlotte' (defaults to a warm female read)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations provide only basic hints (readOnlyHint=false, destructiveHint=false). The description adds valuable context: it reveals the tool is paid, returns the served URL, and preserves performance/lip-sync/background sound. While it doesn't detail all side effects, it covers key behavioral traits beyond annotations.

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 with zero waste. The core action is front-loaded, followed by usage guidance and then practical details (cost, return). Every sentence earns its place, and the structure leads with the most critical information.

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 simple tool with 2 parameters, no output schema, and basic annotations, the description covers all essential aspects: what it does, when to use it, what it returns, and the cost. Nothing an agent needs to invoke it correctly is missing.

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 100%, so both parameters (video and voice) are fully documented in the schema. The description mentions the voice parameter's default and example presets but adds no new meaning beyond what the schema already provides. Baseline 3 is appropriate.

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 clearly states a specific action ('Swap the narration'), a specific resource ('a finished video'), and what is preserved ('performance, lip-sync, and background sound'). It also distinguishes itself from dub_video, making the purpose unambiguous even among many sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use this tool ('when the user likes the video but wants a different narrator voice') and when not to ('use dub_video only for language translation'). This direct routing to the alternative leaves no ambiguity for the agent.

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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TDQS

A3.7/5.0
Disambiguation2/5

With 293 tools, the surface is enormous and many tools have overlapping purposes—multiple posting tools (post_to_meta, post_to_linkedin, schedule_post, etc.), multiple analytics tools per channel, and several search tools (search_meta_ads, search_instagram, search_reddit...). While each description is detailed, the volume makes it difficult for an agent to reliably distinguish between similar tools without careful reading, leading to frequent misselection.

Naming Consistency4/5

The naming is largely consistent with a verb_noun pattern (post_to_*, list_*, create_*, delete_*, update_*, manage_*). There are clear families for major operations. A few outliers like 'google_business_account', 'hermoso_capabilities', and 'store_get' break the pattern, but the overwhelming majority follow a predictable structure, making navigation somewhat easier.

Tool Count1/5

293 tools is far beyond any reasonable scope for a single MCP server, even for a comprehensive marketing platform. The calibration guide flags 50+ as an extreme mismatch, and this is nearly six times that threshold. Such a large surface overwhelms context windows, increases the probability of misselection, and makes it impractical for agents to learn or use effectively.

Completeness4/5

The tool set covers a vast domain: ad creation and rendering, posting across nine+ social channels, analytics and reporting, file management (Drive/OneDrive), competitor research, brand management, and more. It appears to provide CRUD and lifecycle coverage for most resources. While there may be minor gaps given the immense scope, the overall coverage is impressively comprehensive.

Resources