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YangLiangwei

PersonalizationMCP

by YangLiangwei
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_saved_content

Retrieve saved posts and comments from a user's connected accounts to enable personalized, context-aware responses.

Instructions

    Get user's saved posts and comments.
    
    Args:
        username: Username (optional, defaults to current user)
        access_token: Optional access token
        limit: Number of items to return (1-100, default 100)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
usernameNo
access_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention authentication requirements, read-only nature, rate limits, or any side effects. The description only restates the action without adding behavioral context beyond the purpose.

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 well-structured. The main action is front-loaded, and the parameter list is clearly formatted with explanations. There is no unnecessary verbiage, making it efficient for an agent to parse.

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 has an output schema, so return format is covered. All parameters are explained. However, it lacks authentication context (e.g., whether a token is required for private saved content) and does not mention the platform (Reddit, inferred from siblings). For a read operation with no annotations, this is a moderate gap.

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 description coverage is 0%, so the description must compensate. It explains all three parameters: username (optional, defaults to current user), access_token (optional), and limit (1-100, default 100). This adds meaning beyond the schema, though the access_token explanation is minimal and does not clarify its role.

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 clearly states the verb 'Get' and the resource 'user's saved posts and comments', which distinguishes it from sibling tools like get_user_submitted_posts and get_user_comments. The specificity leaves no ambiguity about what content is retrieved.

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

Usage Guidelines3/5

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

The usage is implied by the name and description (for retrieving saved content), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or alternative tool suggestions. The agent must infer from context.

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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