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get_author_feed

Retrieve posts from a specific Bluesky user with options for filtering, pagination, and including pinned content.

Instructions

Get posts from a specific user.

Args:
    ctx: MCP context
    actor: Handle or DID of the user
    cursor: Optional pagination cursor
    filter: Optional filter for post types
    limit: Maximum number of results to return
    include_pins: Whether to include pinned posts

Returns:
    Feed with posts from the specified user

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorYes
cursorNo
filterNo
limitNo
include_pinsNo

Implementation Reference

  • The handler function for the 'get_author_feed' tool. It is registered via the @mcp.tool() decorator and implements the core logic by calling the Bluesky client's get_author_feed method, handling errors, and returning the feed data in a standardized dictionary format.
    @mcp.tool()
    def get_author_feed(
        ctx: Context,
        actor: str,
        cursor: Optional[str] = None,
        filter: Optional[str] = None,
        limit: Optional[int] = None,
        include_pins: bool = False,
    ) -> Dict:
        """Get posts from a specific user.
    
        Args:
            ctx: MCP context
            actor: Handle or DID of the user
            cursor: Optional pagination cursor
            filter: Optional filter for post types
            limit: Maximum number of results to return
            include_pins: Whether to include pinned posts
    
        Returns:
            Feed with posts from the specified user
        """
        try:
            bluesky_client = get_authenticated_client(ctx)
    
            feed_response = bluesky_client.get_author_feed(
                actor, cursor, filter, limit, include_pins
            )
    
            # Convert the response to a dictionary
            if hasattr(feed_response, "model_dump"):
                feed_data = feed_response.model_dump()
            else:
                feed_data = feed_response
    
            return {"status": "success", "feed": feed_data}
        except Exception as e:
            error_msg = f"Failed to get author feed: {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 ('cursor') and filtering options, but doesn't describe important traits like rate limits, authentication requirements, error conditions, or whether this is a read-only operation. For a feed-fetching tool with 5 parameters, this leaves significant gaps in understanding how it behaves.

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) and uses only essential sentences. The front-loaded purpose statement is immediately followed by parameter details. While efficient, the 'Args' section could be more integrated with the main description rather than appearing as a separate documentation block.

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?

For a 5-parameter tool with no annotations and no output schema, the description provides basic purpose and parameter listing but lacks important context. It doesn't explain the return format beyond 'Feed with posts,' doesn't mention authentication requirements, and doesn't differentiate from sibling tools. The parameter explanations are too brief to fully understand usage.

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?

The description includes an 'Args' section that lists all 5 parameters with brief explanations, providing semantic meaning beyond the 0% schema description coverage. However, the explanations are minimal ('Handle or DID of the user', 'Optional filter for post types') and don't elaborate on format, constraints, or examples. This partially compensates for the schema gap but doesn't fully document parameter behavior.

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 from a specific user.' It specifies the verb ('Get') and resource ('posts from a specific user'), making it immediately understandable. However, it doesn't explicitly differentiate from siblings like 'get_posts' or 'get_timeline' which might have overlapping functionality.

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 siblings like 'get_posts' (which might get posts more broadly) or 'get_timeline' (which might show a chronological feed). There's no context about prerequisites, authentication needs, or typical use cases.

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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