analyze_video
Initiates asynchronous analysis of a YouTube video, returning a job_id to retrieve structured timestamped reports.
Instructions
啟動異步分析,返回 job_id。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| profile | No | standard | |
| video_id | Yes |
Initiates asynchronous analysis of a YouTube video, returning a job_id to retrieve structured timestamped reports.
啟動異步分析,返回 job_id。
| Name | Required | Description | Default |
|---|---|---|---|
| profile | No | standard | |
| video_id | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden, and it does disclose two useful traits: the operation is asynchronous and it returns a job_id rather than results. However, it says nothing about expected duration, whether analysis consumes billed resources (a get_cost_summary sibling exists), whether re-analysis overwrites prior results, or what job states to expect.
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?
A single front-loaded clause with no filler, so nothing is wasted, but the brevity crosses into under-specification rather than economy. The one sentence that exists is well-ordered (action then result).
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 an async mutation-style tool with zero annotations, no output schema, and 0% schema coverage on two parameters, the description leaves out the polling workflow, the meaning of profile, and any expectation about results. What is present is correct but far from sufficient.
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% for both parameters, so the description must compensate and does not: video_id is only inferable from the tool name, and the 'profile' parameter with its 'standard' default is completely unexplained — an agent cannot know what alternative profiles exist or what they change.
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?
States a specific verb+resource ('啟動異步分析') and even the return value (job_id), which lets an agent distinguish it from read-only siblings like get_video or list_videos. It never says what the analysis produces or how it differs from sibling get_report/get_conflicts, so it stops short of full differentiation.
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 call this versus ingest_video, get_video, or get_report, and no mention of the obvious workflow partner get_job_status for polling the returned job_id. The agent must infer the entire usage context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.