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raidenrock

USCardForum MCP Server

by raidenrock

get_user_summary

Fetch a user's profile summary to evaluate credibility, identify valuable contributions, and understand participation level on USCardForum.

Instructions

Fetch a comprehensive summary of a user's profile.

Args:
    username: The user's handle (case-insensitive)

Returns a UserSummary object with:
- user_id: User ID
- username: Username
- stats: UserStats with posts, topics, likes given/received, etc.
- badges: List of recent Badge objects
- top_topics: Most successful topics
- top_replies: Most successful replies

Use this to:
- Evaluate a user's credibility and experience
- Find their most valuable contributions
- Understand their participation level

The summary provides a quick overview without fetching
individual post histories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesThe user's handle (case-insensitive)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoDisplay name
statsNoUser statistics
badgesNoRecent badges
user_idNoUser ID
usernameNoUsername
created_atNoAccount creation date
top_topicsNoTop topics
top_repliesNoTop replies
last_seen_atNoLast seen online

Implementation Reference

  • The MCP tool handler for 'get_user_summary'. Decorated with @mcp.tool(), it defines the input schema (username parameter with description), output type UserSummary, includes comprehensive docstring, and delegates execution to the API client via get_client().
    @mcp.tool()
    def get_user_summary(
        username: Annotated[
            str,
            Field(description="The user's handle (case-insensitive)"),
        ],
    ) -> UserSummary:
        """
        Fetch a comprehensive summary of a user's profile.
    
        Args:
            username: The user's handle (case-insensitive)
    
        Returns a UserSummary object with:
        - user_id: User ID
        - username: Username
        - stats: UserStats with posts, topics, likes given/received, etc.
        - badges: List of recent Badge objects
        - top_topics: Most successful topics
        - top_replies: Most successful replies
    
        Use this to:
        - Evaluate a user's credibility and experience
        - Find their most valuable contributions
        - Understand their participation level
    
        The summary provides a quick overview without fetching
        individual post histories.
        """
        return get_client().get_user_summary(username)
  • Pydantic BaseModel defining the output schema/structure for the get_user_summary tool response, including fields for user profile, stats, badges, and top content.
    class UserSummary(BaseModel):
        """Comprehensive user profile summary."""
    
        user_id: int | None = Field(None, description="User ID")
        username: str | None = Field(None, description="Username")
        name: str | None = Field(None, description="Display name")
        created_at: datetime | None = Field(None, description="Account creation date")
        last_seen_at: datetime | None = Field(None, description="Last seen online")
        stats: UserStats | None = Field(None, description="User statistics")
        badges: list[Badge] = Field(default_factory=list, description="Recent badges")
        top_topics: list[Any] = Field(default_factory=list, description="Top topics")
        top_replies: list[Any] = Field(default_factory=list, description="Top replies")
    
        class Config:
            extra = "ignore"
  • Package-level import of the get_user_summary tool from users.py submodule, exposing it for use and MCP registration when the package is imported.
    from .users import (
        get_user_actions,
        get_user_badges,
        get_user_followers,
        get_user_following,
        get_user_reactions,
        get_user_replies,
        get_user_summary,
        get_user_topics,
        list_users_with_badge,
    )
Behavior4/5

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 effectively describes the tool's behavior by specifying what data is returned (UserSummary object with detailed fields), its purpose for evaluation, and its efficiency advantage over fetching individual histories. However, it doesn't mention potential limitations like rate limits or authentication needs.

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 well-structured and front-loaded, starting with the core purpose, followed by parameter and return details, and ending with usage guidelines. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 tool's moderate complexity, no annotations, and the presence of an output schema (implied by the Returns section), the description is complete. It covers purpose, parameters, return values, and usage context adequately, leaving no significant gaps for an AI agent to understand and invoke the tool correctly.

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 100%, so the baseline is 3. The description adds value by reiterating the parameter's purpose ('The user's handle') and noting it's case-insensitive, which provides useful context beyond the schema's basic documentation, though it doesn't introduce new parameter details.

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 tool's purpose with a specific verb ('Fetch') and resource ('comprehensive summary of a user's profile'), distinguishing it from siblings like get_user_badges or get_user_topics by emphasizing it provides a holistic overview rather than specific data points.

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

Usage Guidelines5/5

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

The description explicitly outlines when to use this tool ('to evaluate credibility, find valuable contributions, understand participation level') and distinguishes it from alternatives by noting it provides 'a quick overview without fetching individual post histories,' which helps differentiate it from more granular sibling tools.

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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