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rotten-tomatoes.tv_show_episode

Load a single episode by TV series slug (for example breaking-bad), season number, and episode number.

Returns episode title, air date, description, and episode Tomatometer score when available.

Cost = 5 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tv_show_slugYesTV series slug (for example breaking-bad).
season_numberYesSeason number as one or two digits (for example 1 or 01).
episode_numberYesEpisode number as one or two digits (for example 1 or 01).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoTV series slug.
titleNoEpisode title.
seasonNoSeason number.
episodeNoEpisode number.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the return payload (episode title, air date, description, Tomatometer score when available) and the cost (5 tokens). It also notes the 'when available' caveat, which is useful. It doesn't discuss error handling or rate limits, but for a read-only load tool this is adequate.

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 extremely concise: three short sentences that front-load the action. Every sentence adds useful information: what the tool loads, what it returns, and its cost. No filler or redundancy.

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

Completeness4/5

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

This is a simple, well-scoped tool with a complete input schema and an output schema (per context signals). The description covers the core functionality and return fields. It doesn't discuss edge cases or comparisons with sibling tools, but for a single-episode lookup, it is sufficiently complete.

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 input schema already provides 100% coverage with descriptions for all three parameters, including an example slug. The description recaps the parameters but adds minimal extra meaning beyond what the schema provides. Per the baseline rule, 3 is appropriate.

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 loads a single episode, using a specific TV series slug, season number, and episode number. It uses a specific verb ('Load') and resource ('single episode'), and its specificity distinguishes it from sibling tools like tv_show_season or tv_show_details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage: when you need a specific episode's data by series, season, and episode number. It does not explicitly name alternatives or exclusions, but the context is clear. The absence of alternative guidance keeps it from a 5, but it is sufficient for a simple lookup tool.

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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