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YangLiangwei

PersonalizationMCP

by YangLiangwei
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_user_comments

Retrieve user comments from connected platforms to enable personalized, context-aware interactions. Filter by username, sort order, and limit to get relevant comment history.

Instructions

    Get user's comments.
    
    Args:
        username: Username (optional, defaults to current user)
        access_token: Optional access token
        limit: Number of comments to return (1-100, default 100)
        sort: Sort order (new, hot, top, default: new)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNonew
limitNo
usernameNo
access_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden, but it only adds default behavior for username (defaults to current user). It omits authentication requirements, rate limits, failure behavior, and whether this endpoint works for other users or only the authenticated user.

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?

The description is concise and front-loaded, with a clear purpose line followed by a structured Args block. Every sentence earns its place and there is no redundant phrasing.

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

Completeness2/5

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

For a tool with four optional parameters and an output schema, the description is minimal. It omits the target platform, authentication prerequisites, and any usage context, making it insufficient for reliable tool selection among many similar sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It does explain all four parameters: username (optional, defaults to current user), access_token (optional), limit (1-100, default 100), and sort (new, hot, top, default new). This adds real meaning beyond the schema, though access_token lacks context about when it's needed.

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 states a specific verb ('Get') and resource ('user's comments'), and the parameter list clarifies scope. However, it does not distinguish this tool from siblings like get_user_overview or get_user_submitted_posts, nor does it name the platform (likely Reddit).

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of preferred use cases, exclusions, or links to sibling tools, so the agent must infer usage 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.

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