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Finewisdom 社媒与电商数据接口

by io.github.yy05idiot
OverviewDiscussionsAdmin

tiktok_keyword_search

Read-onlyIdempotent

TikTok综合搜索。返回视频列表，含每条内容ID与基础互动数据。做关键词监测、内容发现或构建候选集时用，ID可继续调详情与评论接口。单价¥0.1/次，仅成功调用计费，失败或空结果自动退回。

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "keyword": "<keyword>"
    },
    "name": "tiktok_keyword_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
_tokenNo备用鉴权：fw_ 开头的 token。推荐改用 HTTP Header X-FW-Token。
keywordYes关键词

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful context beyond annotations: it describes the return content, downstream ID usage, per-call pricing, and refund behavior for failures or empty results. Pagination and rate limits are not described.

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 front-loaded: purpose, return shape, use cases, downstream linkage, and billing are each stated once. There is no redundant or filler wording.

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 two-parameter search tool with no output schema, the description supplies enough context about the result shape and how IDs are reused. It could be more complete by mentioning pagination or result limits, but the core calling context is present.

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 keyword and token parameters are already documented in the schema. The description does not add keyword syntax, format, or filtering semantics beyond the schema baseline.

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

Purpose4/5

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

The description states a specific verb and resource: a TikTok keyword search returning a video list with content IDs and basic engagement data. It is clear enough to distinguish this from detail/comment tools, but it does not explicitly contrast itself with sibling tools like tiktok_user_posts.

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 gives clear usage contexts: keyword monitoring, content discovery, and building candidate sets, plus notes that returned IDs can feed into detail and comment APIs. It does not state when not to use it or name alternative search approaches.

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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