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get_reposted_by

Retrieve users who reposted a specific Bluesky post to analyze engagement and identify content amplifiers.

Instructions

Get users who reposted a post.

Args:
    ctx: MCP context
    uri: URI of the post to get reposts for
    cid: Optional CID of the post (not strictly required)
    limit: Maximum number of results to return (1-100)
    cursor: Optional pagination cursor

Returns:
    List of users who reposted the post

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uriYes
cidNo
limitNo
cursorNo

Implementation Reference

  • The main handler function for the 'get_reposted_by' tool, decorated with @mcp.tool(). It authenticates the Bluesky client, processes parameters, calls the underlying bluesky_client.get_reposted_by method, and returns the results or error.
    @mcp.tool()
    def get_reposted_by(
        ctx: Context,
        uri: str,
        cid: Optional[str] = None,
        limit: Union[int, str] = 50,
        cursor: Optional[str] = None,
    ) -> Dict:
        """Get users who reposted a post.
    
        Args:
            ctx: MCP context
            uri: URI of the post to get reposts for
            cid: Optional CID of the post (not strictly required)
            limit: Maximum number of results to return (1-100)
            cursor: Optional pagination cursor
    
        Returns:
            List of users who reposted the post
        """
        try:
            bluesky_client = get_authenticated_client(ctx)
    
            # Convert limit to int if it's a string
            if isinstance(limit, str):
                limit = int(limit)
            limit = max(1, min(100, limit))
    
            # Call get_reposted_by with positional arguments as per the client signature
            reposts_response = bluesky_client.get_reposted_by(uri, cid, cursor, limit)
            reposts_data = reposts_response.dict()
    
            return {"status": "success", "reposts": reposts_data}
        except Exception as e:
            error_msg = f"Failed to get reposts: {str(e)}"
            return {"status": "error", "message": error_msg}
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions pagination via 'cursor' and a 'limit' range (1-100), which adds some context, but fails to describe authentication needs, rate limits, error conditions, or what the returned user list structure looks like. For a read operation with zero annotation coverage, this leaves significant behavioral gaps.

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 core purpose stated first followed by structured parameter and return sections. Every sentence adds value, though the 'Args' and 'Returns' headers are slightly redundant given the schema context, keeping it from a perfect score.

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 (4 parameters, no output schema, no annotations), the description is partially complete. It covers parameters well but lacks output details, error handling, and behavioral context like authentication or rate limits. It's adequate as a minimum viable description but has clear gaps for a read operation in a social media context.

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 substantial meaning beyond the input schema, which has 0% description coverage. It explains that 'uri' is for the post to get reposts for, 'cid' is optional and not strictly required, 'limit' has a range (1-100) and default behavior, and 'cursor' enables pagination. This compensates well for the schema's lack of descriptions, though it doesn't detail parameter formats or interactions.

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 ('Get') and resource ('users who reposted a post'), distinguishing it from siblings like get_likes, get_followers, or get_post which target different resources. The opening sentence directly answers what the tool does without ambiguity.

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 like get_likes or get_post_thread, nor does it mention prerequisites or contextual constraints. While the purpose is clear, usage guidance is absent, leaving the agent to infer when this specific retrieval is appropriate.

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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