symflow-mcp

sym_avatars

Search and filter avatars by type, name, or tags to retrieve avatar IDs, covers, and previews for use in TikTok video generation.

Instructions

Avatars: kind aigc (1400+ AI-generated presenters, default), real (licensed real people), tryon (avatars for apparel/product try-on), product (avatars holding a product). Filter by query (name/tags) or tagsAll (e.g. ["female","e-comm","western_europe"]). Returns avatarId, name, tags, cover, preview.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "sym_avatars"
  }
}

Input Schema

Name	Required	Description	Default
`kind`	No
`page`	No
`limit`	No
`query`	No
`tagsAll`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 20, 2026

TDQS

A4.2/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the default kind (aigc), the count range (1400+), and what fields are returned. It doesn't mention pagination behavior, rate limits, or whether results are sorted, but the core behavior is transparent.

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?

The description is compact and information-dense. Every sentence adds value: the first enumerates kinds, the second explains filtering, the third lists return fields. No wasted words.

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 list/query tool with no required parameters and no output schema, the description covers the essential semantics: kinds, filters, and return fields. It could mention pagination defaults or sort order, but the tool is simple enough that the description is nearly complete.

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 description coverage is 0%, so the description must compensate. It explains the meaning of kind values, query, and tagsAll, and gives a concrete example. It doesn't explain page/limit semantics, but those are self-evident from their names.

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 the tool lists avatars and enumerates the four kinds (aigc, real, tryon, product) with brief explanations. It distinguishes itself from sibling tools like sym_voices, sym_templates, and sym_generate by focusing specifically on avatar retrieval.

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 explains how to filter by kind, query, and tagsAll, giving a concrete example of tagsAll. It doesn't explicitly state when to use this tool versus alternatives, but the context signals and sibling names make the use case clear enough.

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