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uncheck_episode

Unmark TV show episodes as unwatched by episode ID to correct viewing history or manage watch status in batch operations.

Instructions

Unmarks a specific episode as watched by its ID. Supports both single episode ID and list of episode IDs for batch operations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
episode_idYes

Implementation Reference

  • MCP tool handler for uncheck_episode. Decorated with @mcp.tool() for registration and @tool_handler for error handling. Delegates execution to the MyShowsAPI client.
    @mcp.tool()
    @tool_handler
    async def uncheck_episode(episode_id: Union[int, List[int]]):
        """Unmarks a specific episode as watched by its ID.
        Supports both single episode ID and list of episode IDs for batch operations."""
        return await api_client.uncheck_episode(episode_id=episode_id)
  • Core implementation in MyShowsAPI class that prepares parameters and makes the JSON-RPC call to 'manage.UncheckEpisode' endpoint.
    async def uncheck_episode(self, episode_id: Union[int, List[int]]) -> Dict[str, Any]:
        """Unmarks an episode as watched by its ID.
        :param episode_id: The ID of the episode to uncheck, or a list of episode IDs for batch operation.
        :return: A dictionary containing the result of the uncheck operation.
        """
        if isinstance(episode_id, list):
            params = [{"id": int(ep_id)} for ep_id in episode_id]
        else:
            params = {"id": int(episode_id)}
    
        return await self._make_request(
            "manage.UncheckEpisode", params=params, id=111
        )
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 mentions batch operation support, which adds some context, but fails to address critical aspects like permissions needed, whether the action is reversible, or any rate limits. This leaves significant gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded and concise, consisting of two sentences that efficiently convey the core functionality and batch support without any wasted words. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, error handling, and return values, making it inadequate for safe and effective use by an AI agent.

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 by explaining that 'episode_id' can be a single integer or a list of integers for batch operations, which clarifies the 'anyOf' structure in the schema. With 0% schema description coverage and 1 parameter, this compensates well, though it could specify format or constraints.

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 ('unmarks') and resource ('a specific episode as watched'), and distinguishes it from sibling tools like 'check_episode' by indicating an opposite action. It is precise and avoids tautology.

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, such as 'check_episode' or 'set_movie_watch_status', nor does it mention any prerequisites or exclusions. Usage is implied but not explicitly stated.

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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