Namaste America

get_indian_movies_in_theaters

List Indian-language movies currently playing in US theaters (Hindi, Telugu, Tamil, Malayalam, Kannada, Punjabi, Bengali, Marathi, Gujarati).

Optional `language` filters to one (e.g. "Telugu"). Each movie includes `title`, `language`,
`poster_url`, `overview`, `release_date`, `genres`, and a `ticket_url` — a "find showtimes / buy
tickets" search link (per-theater showtimes are not available via a free source). Data from TMDB.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`language`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

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

First observedJul 8, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries full transparency burden. It discloses the data source (TMDB) and a key limitation (no per-theater showtimes, ticket_url is a search link). This is informative, though it could note any update frequency or rate limits.

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 concise and well-structured: a short first sentence for purpose, then a paragraph with details. Every sentence adds value, with no repetition or fluff.

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?

Given the existence of an output schema, the description appropriately lists the returned fields (title, language, etc.) and explains the ticket_url limitation. It lacks mention of pagination or ordering, but is otherwise complete for a listing tool.

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?

Schema description coverage is 0%, so the description must add meaning. It clarifies the 'language' parameter with an example, but does not explicitly describe the 'limit' parameter beyond its default. Some value is added, but more detail on 'limit' would help.

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 it lists Indian-language movies currently playing in US theaters, specifies the languages included, and distinguishes itself from the sibling tool 'get_movie_details' by focusing on current listings rather than individual movie 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 explains the optional language filter and the data each movie includes, providing clear context. However, it does not explicitly mention when to use alternatives like 'get_movie_details', leaving it implied rather than explicit.

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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