Boxlist

Similar in feel

find_similar_in_feel

Read-onlyIdempotent

Titles that feel like a given film, TV series, book or game — matched on Boxlist's taste dimensions, story themes and subjects, not just genre or cast — across all four media or only the ones you choose. Each result says what it shares with the starting title. Good for "I loved X, what next?" and cross-media asks like "a book that feels like Succession".

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "title": "<title>"
    },
    "name": "find_similar_in_feel"
  }
}

Input Schema

Name	Required	Description
`limit`	No	How many titles (1-5, default 5).
`media`	No	Media to suggest from. Omit for all four (films, TV, books, games). Use ["book"] for "what should I read next".
`title`	Yes	The title to start from: a name, a boxlist.com URL, or a `ref` from another Boxlist tool.
`titleMedia`	No	Medium of the starting title, when the name is shared (e.g. "book" for Dune the novel).

Output Schema

Name	Required	Description
`note`	No	Present when Boxlist has little story data for the starting title, so matches are looser.
`seed`	Yes
`method`	Yes	"site" = the exact "Similar in feel" list shown on boxlist.com; "model" = the same model run live (cross-media).
`results`	Yes
`nextStep`	Yes
`matchedBy`	Yes
`didYouMean`	Yes
`attribution`	Yes	Required credit: show "Data from Boxlist" with the link wherever these results are used.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 11, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that — results state what they share with the starting title, and matching spans themes/subjects rather than surface genre — but says nothing about cost, rate limits, or result quality when the title is ambiguous.

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?

Two sentences, front-loaded with what the tool returns and the differentiator, followed by usage examples. The em-dash aside about 'not just genre or cast' is long but does real work in setting expectations.

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?

With four fully documented parameters, an output schema, and complete annotations, the definition has little structural burden left. The description covers matching basis and result content; only ambiguity handling for the starting title is unaddressed.

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 100%, so the baseline is 3. The description reinforces the media-filter behavior ('across all four media or only the ones you choose') but adds no syntax or edge-case detail beyond what the schema already documents for limit, media, title, and titleMedia.

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 names the resource (titles across film, TV, book, game) and the matching basis (taste dimensions, story themes, subjects rather than 'genre or cast'), which is specific enough to distinguish it from search_titles or get_title_taste_profile. It never names a sibling explicitly, so the differentiation is inferential rather than stated.

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?

Two concrete usage contexts are given: 'I loved X, what next?' and cross-media asks like 'a book that feels like Succession', plus the option to restrict media. It stops short of explicit when-not guidance or pointing at an alternative tool for plain title lookup or two-person matching.

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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