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raidenrock

USCardForum MCP Server

by raidenrock

get_user_replies

Fetch user replies across forum topics to analyze contributions, find data points, and evaluate participation quality in USCardForum discussions.

Instructions

Fetch replies/posts made by a user in other topics.

Args:
    username: The user's handle
    offset: Pagination offset (0, 30, 60, ...)

Returns a list of UserAction objects with:
- topic_id: Which topic they replied to
- post_number: Their post number in that topic
- title: Topic title
- excerpt: Preview of their reply
- created_at: When they replied

Use this to:
- See a user's contributions across topics
- Find their data points and experiences
- Evaluate the quality of their participation

Paginate with offset in increments of 30.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesThe user's handle
offsetNoPagination offset (0, 30, 60, ...)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • MCP tool handler for 'get_user_replies'. Defines the tool function with input schema (username, optional offset) and delegates to the API client to fetch the user's replies as a list of UserAction objects. Includes detailed docstring explaining usage.
    @mcp.tool()
    def get_user_replies(
        username: Annotated[
            str,
            Field(description="The user's handle"),
        ],
        offset: Annotated[
            int | None,
            Field(default=None, description="Pagination offset (0, 30, 60, ...)"),
        ] = None,
    ) -> list[UserAction]:
        """
        Fetch replies/posts made by a user in other topics.
    
        Args:
            username: The user's handle
            offset: Pagination offset (0, 30, 60, ...)
    
        Returns a list of UserAction objects with:
        - topic_id: Which topic they replied to
        - post_number: Their post number in that topic
        - title: Topic title
        - excerpt: Preview of their reply
        - created_at: When they replied
    
        Use this to:
        - See a user's contributions across topics
        - Find their data points and experiences
        - Evaluate the quality of their participation
    
        Paginate with offset in increments of 30.
        """
        return get_client().get_user_replies(username, offset=offset)
  • Imports the get_user_replies handler from users.py as part of the users tools group, making it available for registration when the __init__ 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,
    )
  • Imports get_user_replies in the main server entrypoint, ensuring the @mcp.tool()-decorated function is loaded and registered with the MCP 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 the full burden of behavioral disclosure. It effectively describes key behaviors: it's a read operation (implied by 'Fetch'), pagination details (offset increments of 30), and the return format (list of UserAction objects with specific fields). It doesn't mention rate limits, authentication needs, or error conditions, but provides substantial operational context.

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 well-structured with clear sections (purpose, args, returns, usage, pagination note) and appropriately sized. Every sentence adds value, though the parameter section slightly duplicates schema information. It's front-loaded with the core purpose first.

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, 100% schema coverage, and the presence of an output schema (implied by the detailed return description), the description is complete enough. It covers purpose, parameters, return format, usage scenarios, and pagination behavior, providing all necessary context for effective tool selection and invocation.

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 both parameters. The description repeats the parameter information verbatim without adding additional semantic context beyond what's in the schema (e.g., format examples for username, constraints for offset). The baseline of 3 is appropriate when the schema does the heavy lifting.

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 ('replies/posts made by a user in other topics'), distinguishing it from siblings like 'get_user_topics' (which would fetch topics created by the user) and 'get_user_actions' (which might include other action types). It precisely defines what the tool retrieves.

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 provides usage guidelines with 'Use this to:' followed by three specific scenarios (see contributions, find data points, evaluate participation), giving clear context for when to use this tool. It also mentions pagination behavior, which is a practical usage instruction.

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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