Skip to main content
Glama
Crawlora-org

Crawlora MCP

Official

letterboxd_film_reviews

Fetch a Letterboxd film's popular reviews by slug, up to 50 per request. Get usernames, ratings, liked and spoiler flags, review text, dates, and like and comment counts as clean JSON.

Instructions

Get a Letterboxd film's popular reviews. Returns popular reviews for a Letterboxd film by slug, up to limit (default 10, max 50). Each review has the username, display name, rating from 0.5 to 5.0 when the reviewer gave one, liked flag, date, text, spoiler flag, and like and comment counts.

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does add real value by enumerating returned fields (rating range 0.5–5.0, liked/spoiler flags, counts) and clarifying these are 'popular' rather than all reviews. However, it omits what 'popular' means for ordering, pagination behavior beyond the limit cap, and any auth/rate-limit context.

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?

Front-loaded with the core purpose, then the scoping and return shape. The opening two sentences are mildly redundant ('popular reviews' stated twice), costing a little efficiency but not clarity.

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 simple two-parameter read tool with no output schema or annotations, the description is nearly self-sufficient, covering inputs and a thorough return-field list. Minor gaps remain around sorting semantics and pagination, but nothing critical 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 coverage is 100%, so the schema already documents both parameters including the default and max for `limit`. The description restates these without adding syntax or format detail beyond the schema, so the baseline 3 applies.

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 and resource (get a film's popular reviews) and names the exact scoping unit, `slug`. An agent can distinguish it from siblings like letterboxd_film, letterboxd_film_similar, or letterboxd_popular without opening a schema.

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?

Usage is implied (call it when you have a film slug and want its reviews), but the description never states when to prefer this over letterboxd_film or how to obtain a slug. No exclusions or alternative routing are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools