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jkingsman

https://github.com/jkingsman/qanon-mcp-server

get_posts_by_author_id

Retrieve QAnon posts by a specific author ID for sociological analysis, with optional result limit.

Instructions

Get posts/drops by a specific author ID.

Args:
    author_id: The author ID to search for
    limit: Maximum number of results to return (default: 10)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
author_idYes
limitNo

Implementation Reference

  • The handler function decorated with @mcp.tool(), implementing the core logic to retrieve and format posts by author ID. This serves as both the handler and registration point for the MCP tool.
    @mcp.tool()
    def get_posts_by_author_id(author_id: str, limit: int = 10) -> str:
        """
        Get posts/drops by a specific author ID.
    
        Args:
            author_id: The author ID to search for
            limit: Maximum number of results to return (default: 10)
        """
        if not author_id:
            return "Please provide an author ID."
    
        results = []
        for post in posts:
            post_author_id = post.get("post_metadata", {}).get("author_id", "")
            if post_author_id == author_id:
                results.append(post)
    
        if not results:
            return f"No posts found with author ID '{author_id}'."
    
        total_found = len(results)
        results = results[:limit]
    
        output = f"Found {total_found} posts with author ID '{author_id}'. Showing top {len(results)} results:\n\n"
    
        for i, post in enumerate(results, 1):
            output += f"Result {i}:\n{format_post(post)}\n\n" + "-" * 40 + "\n\n"
    
        if total_found > limit:
            output += f"... and {total_found - limit} more posts."
    
        return output
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves posts, implying a read-only operation, but doesn't disclose other traits like rate limits, authentication needs, pagination behavior, or what happens if the author_id is invalid. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded, with the purpose stated clearly in the first sentence. The Args section is structured but slightly redundant as it repeats parameter names; however, it adds value by explaining semantics. There's minimal waste, 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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and parameter semantics adequately but lacks usage guidelines, behavioral details, and output information. It's sufficient for basic use but leaves gaps for more advanced agent decision-making.

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?

The description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that author_id is 'The author ID to search for' and limit is 'Maximum number of results to return (default: 10)', clarifying their roles. Since the schema lacks descriptions, this compensates well, though it doesn't detail format constraints (e.g., author_id format).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get posts/drops by a specific author ID.' It specifies the verb ('Get') and resource ('posts/drops'), and distinguishes it from siblings like get_posts_by_date or search_posts by focusing on author filtering. However, it doesn't explicitly differentiate from get_post_by_id_tool, which might also involve authors, so it's not a perfect 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over search_posts (which might allow author filtering) or get_posts_by_date, nor does it specify prerequisites or exclusions. The only implied usage is based on the purpose, but no explicit guidelines are given.

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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