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send_video

Post videos to Bluesky Social with text, alt descriptions, and engagement features like replies and mentions.

Instructions

Send a post with a video.

Args:
    ctx: MCP context
    text: Text content of the post
    video_data: Base64-encoded video data
    video_alt: Optional alternative text description for the video
    profile_identify: Optional handle or DID for the post author
    reply_to: Optional reply information dict with keys uri and cid
    langs: Optional list of language codes
    facets: Optional list of facets (mentions, links, etc.)

Returns:
    Status of the post creation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
video_dataYes
video_altNo
profile_identifyNo
reply_toNo
langsNo
facetsNo

Implementation Reference

  • The send_video MCP tool handler, registered via @mcp.tool(). Decodes base64-encoded video data and sends a Bluesky post with the video using the authenticated client.
    @mcp.tool()
    def send_video(
        ctx: Context,
        text: str,
        video_data: str,
        video_alt: Optional[str] = None,
        profile_identify: Optional[str] = None,
        reply_to: Optional[Dict[str, Any]] = None,
        langs: Optional[List[str]] = None,
        facets: Optional[List[Dict[str, Any]]] = None,
    ) -> Dict:
        """Send a post with a video.
    
        Args:
            ctx: MCP context
            text: Text content of the post
            video_data: Base64-encoded video data
            video_alt: Optional alternative text description for the video
            profile_identify: Optional handle or DID for the post author
            reply_to: Optional reply information dict with keys uri and cid
            langs: Optional list of language codes
            facets: Optional list of facets (mentions, links, etc.)
    
        Returns:
            Status of the post creation
        """
        try:
            bluesky_client = get_authenticated_client(ctx)
    
            # Decode base64 video
            try:
                video_bytes = base64.b64decode(video_data)
            except Exception as e:
                return {
                    "status": "error",
                    "message": f"Failed to decode video data: {str(e)}",
                }
    
            # Send the post with video
            post_response = bluesky_client.send_video(
                text=text,
                video=video_bytes,
                video_alt=video_alt,
                profile_identify=profile_identify,
                reply_to=reply_to,
                langs=langs,
                facets=facets,
            )
    
            return {
                "status": "success",
                "message": "Post with video created successfully",
                "post_uri": post_response.uri,
                "post_cid": post_response.cid,
            }
        except Exception as e:
            error_msg = f"Failed to create post with video: {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 the full burden of behavioral disclosure. It states the tool creates a post (implying a write/mutation operation) but doesn't cover critical aspects like required permissions, rate limits, error conditions, or what 'Status of the post creation' entails. For a mutation 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 well-structured with clear sections (Args, Returns) and uses bullet-like formatting for parameters. It's appropriately sized—each sentence adds value without redundancy. Minor improvements could include front-loading more critical context about the tool's behavior or sibling differentiation.

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 complexity (7 parameters, mutation operation) and lack of annotations/output schema, the description is moderately complete. It covers parameters adequately but lacks behavioral context, usage guidelines, and output details. For a post-creation tool in a social media context, more information about authentication, error handling, or response structure would enhance completeness.

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 provides a comprehensive list of all 7 parameters with brief explanations (e.g., 'Base64-encoded video data', 'Optional alternative text description for the video'). Since schema description coverage is 0%, this compensates well by adding meaning beyond the bare schema. However, some parameters like 'facets' and 'reply_to' could benefit from more detailed examples or formatting guidance.

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: 'Send a post with a video.' It specifies the verb ('send') and resource ('post with a video'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'send_post' or 'send_image', which would require more specific context about when to use video vs. other media types.

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 'send_post' or 'send_image'. It doesn't mention prerequisites (e.g., authentication status), use cases, or exclusions. The agent must infer usage from the tool name alone, which is insufficient for optimal selection.

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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