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Hermoso

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by hermoso-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

Generate talking avatar

generate_avatar

Turn a portrait image and a script into a lip-synced talking avatar video. Provide the presenter photo and the words to speak, and get a rendered clip ready for use.

Instructions

Render a TALKING-AVATAR / creator lip-sync clip from a portrait image + a script. Blocks until done (1–3 min). Requires the avatar capability (canAvatar in hermoso_capabilities). Spends credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYeslocal path or URL of the presenter portrait
voiceNovoice name (Rachel/Sarah/George/Adam)
scriptYesthe words the avatar speaks
resolutionNo'1080p' (default) or '480p'/'720p' draft

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.161
    • changedInput schema / properties / resolution / description
      Previous value: -"'720p' (default) or '480p' draft"New value: +"'1080p' (default) or '480p'/'720p' draft"
    • changedOutput schema / (root)
      Previous value: -{
-  "$schema": "http://json-schema.org/draft-07/schema#",
-  "additionalProperties": false,
-  "properties": {
-    "jobId": {
-      "description": "the render job id — poll get_job with this id to resume or inspect",
-      "type": "string"
-    },
-    "model": {
-      "anyOf": [
-        {
-          "type": "string"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "description": "the product-facing label of the model that rendered it"
-    },
-    "raw": {
-      "description": "the raw job result payload (e.g. images[] for carousel template ads)"
-    },
-    "stillRendering": {
-      "description": "true when the render is still in progress — keep polling get_job with jobId",
-      "type": "boolean"
-    },
-    "url": {
-      "anyOf": [
-        {
-          "type": "string"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "description": "the served URL of the finished media (absent/null while still rendering)"
-    }
-  },
-  "type": "object"
-}New value: +null
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Beyond annotations, it discloses three important behaviors: blocking with a 1–3 min wait, capability gating (canAvatar in hermoso_capabilities), and credit consumption. This goes well beyond the false readOnly/idempotent/destructive hints. It does not describe the return artifact, though no output schema is provided.

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?

Three sentences, each carries distinct value: what it does, how long it blocks, and what prerequisites/costs apply. No redundant filler; the core action is front-loaded.

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?

Given the schema covers all parameters and annotations capture mutation/idempotency hints, the description supplies the missing operational context: duration, capability requirement, and credits. It leaves out what the tool returns or where the clip is saved, but the other essential context is complete enough for an agent to call it correctly.

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 the schema already explains image, script, voice, and resolution. The description adds no new parameter-level meaning beyond hinting the image should be a portrait, so 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 uses a specific verb/resource: 'Render a TALKING-AVATAR / creator lip-sync clip from a portrait image + a script.' This clearly differentiates it from siblings like generate_video, generate_voice, or make_explainer by naming the unique output type and inputs.

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 communicates when to invoke: when the user needs a talking-avatar/lip-sync clip from a portrait and script. It also gives prerequisites ('Requires the avatar capability...') and cost/duration context. It does not explicitly name alternatives or exclusions, so it is not 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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