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rhettlong

USCardForum MCP Server

by rhettlong

get_user_summary

Fetch a user's profile summary to evaluate credibility, find valuable contributions, and understand participation level in the USCardForum community.

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

  • Primary MCP tool handler for 'get_user_summary'. Defines input schema with Pydantic Annotated Field, comprehensive docstring, and delegates execution to DiscourseClient.get_user_summary().
    @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 type UserSummary returned by the get_user_summary tool, 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"
  • Underlying client method called by the tool handler. Fetches raw user summary from UsersAPI and enriches top_topics with category names.
    def get_user_summary(self, username: str) -> UserSummary:
        """Fetch user profile summary.
    
        Args:
            username: User handle
    
        Returns:
            Comprehensive user summary
        """
        summary = self._users.get_user_summary(username)
        if summary.top_topics:
            self._enrich_with_categories(summary.top_topics)
        return summary
  • Server entrypoint imports the get_user_summary tool (line 35), along with all other tools. Importing triggers @mcp.tool() decorators to register the tool with the FastMCP server.
    from uscardforum.server_tools import (
        analyze_user,
        bookmark_post,
        compare_cards,
        find_data_points,
        get_all_topic_posts,
        get_categories,
        get_current_session,
        get_hot_topics,
        get_new_topics,
        get_notifications,
        get_top_topics,
        get_topic_info,
        get_topic_posts,
        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,
        login,
        research_topic,
        resource_categories,
        resource_hot_topics,
        resource_new_topics,
        search_forum,
        subscribe_topic,
    )
Behavior4/5

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

With no annotations provided, the description carries full burden and effectively discloses key behaviors: it's a read operation (implied by 'Fetch'), returns structured data (UserSummary object), and emphasizes efficiency ('quick overview'). However, it lacks details on error handling or rate limits.

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?

Well-structured with clear sections (Args, Returns, Use cases) and front-loaded purpose, but slightly verbose in listing return fields and use cases. Every sentence adds value, though some redundancy exists with the schema.

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, but a detailed output schema (implied by Returns section), the description provides complete context: purpose, usage, parameters, and return structure, compensating adequately for the lack of annotations.

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 schema already fully documents the single parameter. The description repeats the parameter info but adds no additional semantic context beyond what's in the schema, meeting the baseline for high coverage.

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 specific action ('Fetch a comprehensive summary') and resource ('user's profile'), distinguishing it from siblings like get_user_badges or get_user_topics by emphasizing a holistic overview rather than specific components.

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?

It explicitly states when to use this tool ('to evaluate credibility, find contributions, understand participation') and when not to use it ('without fetching individual post histories'), providing clear alternatives and context for selection.

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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