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datasets_boxofficemojo_search

Search theatrical box-office records from Box Office Mojo by title, year, franchise, genre, or gross band; filter by worldwide/domestic gross and lifetime top-1000 status.

Instructions

Search the Box Office Mojo dataset. Searches theatrical box-office records from public Box Office Mojo charts and title pages, stored in a search index. Filter by title id, year, franchise/brand/genre, gross band, lifetime top-1000 membership, hydration status, and worldwide/domestic gross ranges. Sort enum: relevance, worldwide_desc, domestic_desc, peak_worldwide_desc, lifetime_rank_asc, year_desc, year_asc. gross_band enum: under_50m, 50_100m, 100_250m, 250_500m, 500m_1b, over_1b.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over title and taxonomy names, max 256 characters
pageNoPage number, defaults to 1
sortNoSort enum: relevance, worldwide_desc, domestic_desc, peak_worldwide_desc, lifetime_rank_asc, year_desc, year_asc
yearNoYear that must appear in years_active
brandNoBrand name filter, max 128 characters
genreNoGenre name filter, max 128 characters
hydratedNoOnly titles with hydrated release groups and market grosses
title_idNoExact title id (IMDb tt… id used by Box Office Mojo), max 32 characters
franchiseNoFranchise name filter, max 128 characters
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
gross_bandNoGross band enum: under_50m, 50_100m, 100_250m, 250_500m, 500m_1b, over_1b
min_domesticNoMinimum lifetime domestic gross in whole USD dollars
lifetime_yearNoPrimary lifetime chart year
max_worldwideNoMaximum lifetime worldwide gross in whole USD dollars
min_worldwideNoMinimum lifetime worldwide gross in whole USD dollars
is_billion_dollarNoOnly titles with worldwide gross of at least $1B
min_foreign_shareNoMinimum foreign share of worldwide gross, 0 through 1
max_domestic_shareNoMaximum domestic share of worldwide gross, 0 through 1
in_lifetime_top_1000NoOnly titles in the lifetime worldwide top 1000 chart

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / gross_band / enum
      Added value: +[
+  "under_50m",
+  "50_100m",
+  "100_250m",
+  "250_500m",
+  "500m_1b",
+  "over_1b"
+]
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "relevance",
+  "worldwide_desc",
+  "domestic_desc",
+  "peak_worldwide_desc",
+  "lifetime_rank_asc",
+  "year_desc",
+  "year_asc"
+]
  2. Added

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the data provenance ('public Box Office Mojo charts and title pages, stored in a search index') and filter scope, which is useful. However, it does not describe the result shape, default pagination behavior beyond schema, or how filters combine, leaving an agent to infer what a search actually returns.

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 compact for a tool with 19 parameters, front-loading the core purpose in the first sentence and then summarizing filters and enums. The only minor redundancy is the near-duplicate 'Search'/'Searches' opening, but it is not padding.

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?

For a complex search tool with no output schema and no annotations, the description covers the essential context: the dataset, the source material, available filters, and sort ordering. Its main gap is not describing what the returned records look like or any usage constraints beyond the schema, but the provided overview is sufficient to decide when to call the tool.

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?

Schema description coverage is 100%, so the baseline is 3, but the description adds value by grouping the 19 parameters into meaningful categories ('title id, year, franchise/brand/genre, gross band, lifetime top-1000 membership, hydration status, and worldwide/domestic gross ranges') and by surfacing the sort and gross_band enums. This gives the agent a mental model of the search capabilities beyond the individual schema entries.

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 opens with 'Search the Box Office Mojo dataset' and elaborates that it 'Searches theatrical box-office records from public Box Office Mojo charts and title pages, stored in a search index.' This clearly identifies a specific verb (search), resource (Box Office Mojo theatrical records), and scope, distinguishing it from sibling item-retrieval or chart-specific tools.

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

Usage Guidelines3/5

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

The description implies usage by enumerating the available filter dimensions and sort options, but it never explicitly states when to prefer this tool over siblings like datasets_boxofficemojo_item or boxofficemojo_lifetime_grosses. The 'search a dataset' framing gives context, but there is no exclusion or alternative routing.

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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