Bilibili Comments MCP
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools have clearly distinct purposes: one targets dynamic comments and the other targets video comments, with no overlap in functionality. The descriptions reinforce this by specifying different contexts (dynamic vs. video) while sharing similar features like pagination and nested replies.
Naming Consistency5/5Both tools follow a consistent verb_noun pattern (get_dynamic_comments and get_video_comments), using the same verb 'get' and similar noun structures. This makes the naming predictable and easy to understand across the tool set.
Tool Count2/5With only 2 tools, the server feels thin for a comments-focused domain, lacking operations like creating, updating, deleting, or searching comments. This minimal set may limit agent workflows, as it only supports retrieval without full CRUD coverage.
Completeness2/5The tool set is severely incomplete for a comments domain, missing essential operations such as posting comments, replying to comments, or deleting comments. While retrieval is covered for dynamics and videos, there are significant gaps that will hinder agents from performing common comment-related tasks.
Average 4/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
Tools from this server were used 16 times in the last 30 days.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating this is a safe read operation. The description adds valuable behavioral context beyond annotations: it discloses the authentication requirement (Bilibili Cookie needed for functionality) and mentions pagination and threaded reply capabilities. While it doesn't describe rate limits or detailed error behavior, it provides meaningful operational context that complements the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured in just two sentences. The first sentence states the core functionality, while the second provides critical operational context (authentication requirement). Every word earns its place with zero redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with complete schema documentation and annotations, the description provides adequate context. It covers the core purpose, key capabilities (pagination, threaded replies), and critical operational requirement (Cookie authentication). While no output schema exists, the description doesn't need to explain return values. The main gap is lack of explicit differentiation from the sibling video comments tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the input schema already documents all 6 parameters thoroughly. The description doesn't add significant parameter semantics beyond what's in the schema - it mentions pagination and threaded replies which correspond to 'page', 'pageSize', and 'includeReplies' parameters already well-described in the schema. The baseline of 3 is appropriate when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '获取 B 站动态的评论内容' (get Bilibili dynamic comments). It specifies the resource (Bilibili dynamic comments) and key capabilities (pagination and threaded replies). However, it doesn't explicitly differentiate from its sibling 'get_video_comments' - both retrieve comments but for different content types (dynamic vs video).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context with the authentication requirement note ('需要有效的 B 站 Cookie 才能正常工作'), but doesn't explicitly state when to use this tool versus its sibling 'get_video_comments' or other alternatives. It implies usage for Bilibili dynamic comments specifically, but lacks clear comparative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond annotations. While annotations indicate read-only and closed-world operations, the description specifies authentication requirements ('需要有效的 B 站 Cookie 才能正常工作'), which is crucial for the agent to understand prerequisites. It also mentions support for pagination, sorting, and nested replies, providing operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences) and front-loaded with the core purpose. Every sentence earns its place: the first states what the tool does and key features, the second provides critical authentication information. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with comprehensive parameter documentation (100% schema coverage) and clear annotations, the description provides good contextual completeness. It covers authentication requirements and key behavioral features. The main gap is the lack of output schema, but the description mentions output format options, partially compensating.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the input schema already documents all 8 parameters thoroughly. The description does not add any additional parameter semantics beyond what's in the schema. The baseline score of 3 is appropriate since the schema carries the full burden of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '获取 B 站视频的评论内容' (get Bilibili video comments). It specifies the resource (Bilibili video comments) and distinguishes from its sibling tool 'get_dynamic_comments' by focusing on video comments rather than dynamic comments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: for retrieving Bilibili video comments with pagination, sorting, and nested replies. It mentions the requirement for valid Bilibili cookies. However, it does not explicitly state when NOT to use it or compare it to the sibling tool 'get_dynamic_comments'.
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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