Skip to main content
Glama

AdsTurbo

ai_actor_perform

演员演出(系统演员或 Persona)

actor_id 既可为系统演员 ID,也可为自定义 Persona 的 actor_id,共用同一套演出参数与异步任务响应。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
speedNo
styleNo
scriptNo
actor_idNo系统演员 ID,或 Persona 的 actor_id
stabilityNo
similarityNo
callback_idNo自定义追踪 ID,webhook URL 后台配置
auto_emotionNo
speaker_boostNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, destructiveHint=false, so the safety profile is covered. The description adds one genuinely useful trait beyond the annotations: the invocation returns an asynchronous task response ('异步任务响应'), telling the agent not to expect an inline result. It does not, however, explain how to poll for completion (get_work_status/get_persona_status) or how the callback_id webhook fits in.

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?

Two short sentences, purpose front-loaded and the actor_id clarification second; nothing in the text is redundant padding. It is tight, though arguably tighter than a 9-parameter async tool warrants.

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

Completeness2/5

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

For a complex, zero-required-parameter mutation with no output schema and 78% of parameters undescribed, the description is far too thin. It signals async behavior but omits the polling/webhook follow-up and leaves most inputs unexplained, so an agent cannot call it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 22% — just actor_id and callback_id are documented. The description adds meaning for actor_id (system actor ID vs Persona actor_id sharing one parameter set), but the remaining seven parameters (speed, style, script, stability, similarity, auto_emotion, speaker_boost) are undocumented in both schema and description, and 'shared performance parameters' is too vague to fill that gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening '演员演出(系统演员或 Persona)' largely restates the tool name and adds only the scope qualifier that the actor may be a system actor or a custom Persona. It never says what a 'performance' actually produces (audio, video, animation) and does not distinguish this from the sibling ai_actor_say or ai_actor_list. Purpose is inferable but thin.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance and no mention of alternates such as ai_actor_say (which sounds like the synchronous counterpart) or ai_actor_list. The only usage hint is that actor_id accepts either a system actor or a Persona, which is a compatibility note rather than routing guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources