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Crawlora MCP

Crawlora MCP

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by Crawlora-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

letterboxd_film_similar

Find films similar to a Letterboxd film by slug; returns up to 50 recommended titles with slugs, titles, and URLs for further lookup.

Instructions

Get films similar to a Letterboxd film. Lists films Letterboxd recommends as similar to the film given by slug, up to limit (default 10, max 50). Each film has its slug, title and Letterboxd URL. Use the slug to look up that film's details.

Input Schema

NameRequiredDescriptionDefault
slugYesLetterboxd film slug
limitNoMax films, default 10, max 50

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: the result count is bounded by `limit` (default 10, max 50) and each returned film carries `slug`, title, and URL. It doesn't state ordering or what happens if fewer than `limit` matches exist, but the core behavior and constraints are surfaced.

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?

Three tight sentences, front-loaded with the purpose, then the result-shape/limit detail, then the routing hint. Every sentence earns its place with no redundancy.

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

Completeness5/5

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

There is no output schema, so the description appropriately compensates by naming the returned fields (`slug`, title, URL) and the count constraint. For a two-parameter lookup tool with no annotations, nothing an agent needs to call it correctly is missing.

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 both parameters are already documented, including the default 10 / max 50 for `limit`. The description restates those facts and adds only the minor note that the slug identifies the source film, so baseline 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?

States a specific verb (get/list) and resource (films similar to a Letterboxd film), and immediately distinguishes itself from the film-detail sibling by scoping to 'similar' films. An agent can tell what this returns without opening the schema.

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 gives clear context ('films Letterboxd recommends as similar') and explicitly routes the agent onward: 'Use the slug to look up that film's details,' pointing at the sibling for detail lookups. It stops short of an explicit when-not-use statement or naming other siblings like reviews or rating histogram.

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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