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7oMB2006

Bilibili Video Research

by 7oMB2006
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TypeScript
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Research a Bilibili Video

analyze_bilibili_video
Read-only

Analyze public Bilibili videos by URL: retrieve metadata, sample top comments, and research content via language, visual, or multimodal modes with explicit community-context status.

Instructions

Resolves a public Bilibili URL, always returns public metadata and an explicit community-context status, and optionally samples 20 most-liked root comments while displaying only 3 hot comments plus up to 2 distinct high-signal comments. Supports language-only, visual-only, and multimodal research.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic Bilibili video URL, including b23.tv short URLs.
modeYeslanguage: captions then audio only; vision: silent video only; multimodal: original video with both channels.
questionYesThe research question.
end_secondsNoOptional source-video interval end in seconds. Provide together with start_seconds.
media_detailNoUse low for a broad long-video pass and default for close inspection.default
start_secondsNoOptional source-video interval start in seconds. Provide together with end_seconds.
include_commentsNoInclude untrusted community context. Fetches at most 20 most-liked root comments, presents only 3-5 representative comments, and reports empty or fetch-failed status explicitly.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / end_seconds
      Added value: +{
+  "description": "Optional source-video interval end in seconds. Provide together with start_seconds.",
+  "exclusiveMinimum": 0,
+  "type": "number"
+}
    • changedInput schema / properties / include_comments / description
      Previous value: -"Attach untrusted community context. Fetches at most 20 most-liked root comments but presents only 3-5 representative comments."New value: +"Include untrusted community context. Fetches at most 20 most-liked root comments, presents only 3-5 representative comments, and reports empty or fetch-failed status explicitly."
    • addedInput schema / properties / start_seconds
      Added value: +{
+  "description": "Optional source-video interval start in seconds. Provide together with end_seconds.",
+  "minimum": 0,
+  "type": "number"
+}
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

The description goes well beyond the readOnlyHint annotation by disclosing that it 'always returns public metadata and an explicit community-context status', and it details the exact comment sampling behavior: at most 20 most-liked root comments fetched, only 3-5 presented, and empty/fetch-failed states reported explicitly. It also transparently enumerates the three research modes. This gives an agent a precise behavioral model without any contradiction.

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?

Two tightly packed sentences deliver the purpose, the guaranteed return behavior, the comment handling policy, and the supported research modes. Every clause conveys a distinct piece of information, and the most important scoping information appears first. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the rich 100%-covered schema, the readOnly annotation, and the absence of an output schema, the description provides a complete operational picture: what it always returns, what it optionally fetches and how it filters it, and which modes it supports. It leaves no ambiguity about whether comments are included, how many, or how failures are surfaced. The tool is complex enough that this level of detail is necessary and sufficient.

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 input schema already fully documents url, mode, question, start/end seconds, media_detail, and include_comments. The description's mention of 'language-only, visual-only, and multimodal' and 'optionally samples 20 most-liked root comments' adds some semantic color, but it does not add parameter-level meaning beyond the schema. Baseline 3 is appropriate.

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

Purpose5/5

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

The description uses a specific verb ('resolves') with a clear resource (public Bilibili URL) and states what it returns (public metadata and community-context status). It distinguishes itself from siblings like analyze_video and inspect_video_window by being Bilibili-specific and by emphasizing comment sampling and language/vision/multimodal modes. The title reinforces the purpose without being a mere tautology.

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?

The description clearly defines when to use the tool: when given a public Bilibili URL, including b23.tv short URLs, and when research requires language-only, visual-only, or multimodal analysis. It gives concrete scope and indicates the optional comment-related behaviorging, but it does not explicitly mention when to prefer a sibling tool instead. The context is clear enough for most agents to route correctly.

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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