Retrieve audience retention data for a specific YouTube video, showing watch ratio and relative retention at each elapsed-time point. Use this to identify where viewers drop off.
Audience retention curve for one video: a list of points {ratio, watch_ratio, relative} across the video's elapsed-time ratio.
| Name | Required | Description | Default |
|---|---|---|---|
| refresh | No | ||
| video_id | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so the description does not need to restate safety. The description adds useful context about the output structure (list of points with ratio, watch_ratio, relative), but it does not disclose details like whether the curve is normalized, how missing data is handled, or whether refresh forces a recomputation.
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 front-loads the core purpose and includes the key output structure. Every word earns its place, and there is no redundant restating of the tool name or schema.
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 read-only single-video tool with a simple schema, the description is mostly adequate. However, with no output schema and no explanation of the 'refresh' parameter or the meaning of the returned fields, an agent may not know how to interpret the response or when to set refresh. It is minimally viable but has clear gaps.
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?
Schema description coverage is 0%, so the description must compensate for parameter meaning. It explains the output semantics but does not explain the 'refresh' parameter or the expected format of video_id beyond the schema's basic type. The description adds some value by clarifying the output fields, but leaves parameter-level meaning mostly to the schema.
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?
The description states a specific verb ('get') and resource ('audience retention curve for one video') and defines the returned data shape as a list of points with ratio, watch_ratio, and relative fields. It is clear what the tool does, though it does not explicitly distinguish it from sibling tools like get_channel_metrics or analyze_pillar_performance.
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 implies usage for retrieving retention data for a single video, and the required video_id parameter makes the context clear. However, it does not state when to prefer this over siblings or mention any exclusions, such as not being suitable for channel-level retention analysis.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.