detail
Retrieve detailed information from Douyin (TikTok China) API for comprehensive data analysis and platform insights.
Instructions
detail
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve detailed information from Douyin (TikTok China) API for comprehensive data analysis and platform insights.
detail
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. The single word 'detail' gives no insight into whether this is a read or write operation, what resources it accesses, potential side effects, rate limits, or authentication needs. It fails to convey any behavioral characteristics beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely concise (one word), it is under-specified rather than efficiently informative. Conciseness should not come at the cost of clarity; here, the brevity results in a lack of useful content. It fails to front-load essential information, making it ineffective despite its short length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by many sibling tools and the lack of annotations and output schema, the description is completely inadequate. It provides no context about functionality, behavior, or use cases, leaving the agent unable to understand or invoke the tool effectively. This is insufficient for any meaningful operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% description coverage, meaning no parameters need documentation. The description does not add parameter semantics, but this is acceptable given the absence of parameters. A baseline score of 4 reflects that the description need not compensate for missing parameter info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. With numerous sibling tools present (e.g., detail variants, list tools, search tools), there is no indication of context, prerequisites, or distinctions. This leaves the agent with no actionable information for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/BACH-AI-Tools/bachai-douyin-api-new'
If you have feedback or need assistance with the MCP directory API, please join our Discord server