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Scottcjn

RustChain + BoTTube MCP Server

by Scottcjn

Bottube Vote

bottube_vote

Cast an upvote or downvote on a BoTTube video to influence its ranking. Provide the video ID and direction to submit your vote.

Instructions

Vote on a BoTTube video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoBoTTube API key for authentication
video_idYesThe video ID to vote on
directionNo"up" for upvote, "down" for downvoteup

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.4.0
    • addedInput schema / properties / api_key / description
      Added value: +"BoTTube API key for authentication"
    • addedInput schema / properties / direction / description
      Added value: +"\"up\" for upvote, \"down\" for downvote"
    • addedInput schema / properties / video_id / description
      Added value: +"The video ID to vote on"
  2. First observedv0.2.1

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses that the tool 'vote[s]' but does not say whether votes are mutate state, whether api_key authentication is required, or whether votes can be changed or retracted. For a mutating action, this is a meaningful transparency gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence with zero filler and it front-loads the core action. It is appropriately sized for a simple tool, though the brevity contributes to the lack of behavioral detail. On conciseness alone it is well-structured.

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

Completeness3/5

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

The tool is low-complexity and the input schema fully documents all parameters, while an output schema is reportedly present, so return-value details are not required. Even so, the absence of behavioral context and usage guidance leaves the definition merely adequate. An agent could invoke the tool but would be guessing about side effects and preconditions.

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 baseline is 3 even though the description adds nothing about parameters. The schema already documents video_id, direction, and api_key with adequate descriptions. The description does not need to compensate but also does not enrich the parameters.

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

Purpose4/5

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

The description uses a concrete verb and resource: 'Vote on a BoTTube video.' It clearly identifies the action and distinguishes it from related siblings like upload, comment, or search. However, it does not mention up/down semantics or explicitly differentiate itself from sibling voting-related tools, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to choose this tool over alternatives like bottube_comment or bottube_trending. The description merely names the action without stating preconditions, exclusions, or situational context. The agent must infer applicability from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.