USCardForum MCP Server

get_user_topics

Retrieve forum topics created by a specific user to analyze their discussion history, identify expertise areas, and research user interests in credit card communities.

Instructions

Fetch topics created by a specific user.

Args:
    username: The user's handle
    page: Page number for pagination (optional)

Returns a list of topic objects with:
- id: Topic ID
- title: Topic title
- posts_count: Number of replies
- views: View count
- created_at: When created
- category_id: Forum category

Use this to:
- See what discussions a user has initiated
- Find expert users in specific areas
- Research a user's areas of interest

Paginate by incrementing the page parameter.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`username`	Yes	The user's handle
`page`	No	Page number for pagination

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedDec 30, 2025

TDQS

A4.5/5.0

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: it's a read operation (implied by 'fetch'), returns paginated results, and specifies the exact structure of returned objects. It also explains pagination mechanics ('Paginate by incrementing the page parameter'), which is valuable behavioral context not captured elsewhere.

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 with clear sections (purpose, args, returns, use cases, pagination guidance). Every sentence adds value: the opening statement defines purpose, the args section clarifies parameters, the returns section details output structure, and the use cases provide practical guidance. No wasted words.

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 that there's an output schema (implied by 'Returns a list of topic objects'), the description provides excellent context. It covers purpose, parameters, return structure, use cases, and pagination behavior. For a read-only tool with good schema coverage, this description provides complete contextual understanding.

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 adds minimal value beyond the schema - it repeats the parameter descriptions verbatim and adds pagination guidance. This meets the baseline expectation when schema coverage is complete.

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 topics created by a specific user') and distinguishes it from sibling tools like get_user_replies or get_user_summary by focusing exclusively on topics initiated by the user. The verb 'fetch' combined with the resource 'topics created by a specific user' provides precise intent.

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 three use cases ('See what discussions a user has initiated', 'Find expert users in specific areas', 'Research a user's areas of interest'), giving clear context for when to use this tool. It also distinguishes from alternatives by focusing on user-created topics rather than replies or other user data available in sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.