analyze_interaction_data
Analyzes Douyin video interactions, including likes and comments, to provide engagement insights.
Instructions
分析视频互动数据(点赞、评论等)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Analyzes Douyin video interactions, including likes and comments, to provide engagement insights.
分析视频互动数据(点赞、评论等)
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It only states the general purpose and examples, omitting details like whether it is read-only, what data it operates on, or any side effects. This is insufficient for a tool with zero annotation coverage.
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?
The description is a single, concise sentence that immediately communicates the tool's purpose. Every word is necessary and nothing is superfluous.
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?
For a parameterless tool, the description is minimally adequate: it explains what the tool does. However, it does not specify the output format, scope, or how it relates to sibling tools like get_data_summary. Given the simplicity, a score of 3 is appropriate.
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 tool has zero parameters, so the baseline is 4. The description does not add parameter-specific meanings, but the lack of parameters makes this less critical.
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?
Description clearly states the tool analyzes video interaction data, using a specific verb ('analyze') and resource ('interaction data'). It lists examples (likes, comments) but does not differentiate from sibling tools like get_data_summary or analyze_keywords.
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?
No guidance on when to use this tool versus alternatives such as analyze_content_length or search_douyin_videos. The description provides no context about prerequisites or intended scenarios.
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/kk520879/undoom-douyin-data-analysis'
If you have feedback or need assistance with the MCP directory API, please join our Discord server