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Ukenn2112

Bangumi TV MCP Service

by Ukenn2112

get_daily_broadcast

Retrieve the daily broadcast schedule for the current week from Bangumi TV. The schedule is grouped by day, providing a clear overview of anime and show timings.

Instructions

Get the daily broadcast schedule for the current week on Bangumi.

Returns:
    The broadcast schedule grouped by day of the week, or an error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • main.py:328-376 (handler)
    The handler function decorated with @mcp.tool() registers and implements the get_daily_broadcast tool. It fetches the Bangumi /calendar API, processes the response grouping by weekday, formats using format_subject_summary, and returns a string schedule or error.
    @mcp.tool()
    async def get_daily_broadcast() -> str:
        """
        Get the daily broadcast schedule for the current week on Bangumi.
    
        Returns:
            The broadcast schedule grouped by day of the week, or an error message.
        """
        response = await make_bangumi_request(method="GET", path="/calendar")
    
        error_msg = handle_api_error_response(response)
        if error_msg:
            return error_msg
    
        # Expecting a list of dictionaries, where each dict represents a day
        if not isinstance(response, list):
            return f"Unexpected API response format for /calendar: {response}"
    
        calendar_data = response
        if not calendar_data:
            return "Could not retrieve daily broadcast calendar."
    
        formatted_schedule = ["Daily Broadcast Schedule:"]
    
        # The API returns days in a specific order, we can just iterate through the list
        for day_entry in calendar_data:
            weekday = day_entry.get("weekday", {})
            items = day_entry.get("items", [])
    
            # Get readable weekday name, default to English if others are missing
            weekday_name = (
                weekday.get("cn")
                or weekday.get("ja")
                or weekday.get("en")
                or f"Weekday ID {weekday.get('id', 'N/A')}"
            )
            formatted_schedule.append(f"\n--- {weekday_name} ---")
    
            if not items:
                formatted_schedule.append("  No broadcasts scheduled.")
            else:
                formatted_results = [format_subject_summary(s) for s in items]
                results_text = (
                    f"Found {len(items)} subjects.\n"
                    + "---\n".join(formatted_results)
                )
                formatted_schedule.append(results_text)
    
        return "\n".join(formatted_schedule)
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 mentions the return format ('grouped by day of the week') and error handling, but doesn't cover important aspects like rate limits, authentication needs, data freshness, or whether it's a read-only operation. 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 concise and well-structured, consisting of two sentences: one stating the purpose and one describing the return format. It's front-loaded with the main function and avoids unnecessary details. However, it could be slightly more efficient by integrating the return info into the first sentence.

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 (simple read operation with no parameters) and lack of annotations/output schema, the description is minimally complete. It covers the basic purpose and return format, but misses behavioral details like error types or data scope. For a tool with no structured data, it's adequate but has clear gaps in providing full 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 tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The description doesn't add parameter semantics, but this is acceptable given the lack of parameters. A baseline score of 4 is appropriate as it doesn't need to compensate for any gaps.

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 the daily broadcast schedule for the current week on Bangumi.' It specifies the verb ('Get'), resource ('daily broadcast schedule'), and scope ('current week on Bangumi'), which is clear and specific. However, it doesn't explicitly differentiate from sibling tools like 'get_episodes' or 'browse_subjects', which might also involve scheduling or content retrieval.

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 any prerequisites, exclusions, or comparisons to sibling tools such as 'get_episodes' or 'search_subjects', which could be related. This lack of context makes it harder for an agent to decide when this tool 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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