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find_imdb_candidates

Turn any IMDb list URL into a set of candidate title IDs for torrent discovery.

Instructions

Scrape an IMDb list page (e.g. a "coming this year" list) for title ids.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool scrapes an external IMDb page, which implies a network read, but it does not mention whether the operation is read-only, potential rate-limit or page-block risks, error behavior, or any side effects. For a scrape operation, this is a significant disclosure gap.

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?

One sentence, front-loaded with the action verb, includes a clarifying example, and contains no redundant filler. Every word contributes to understanding the tool's purpose.

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

Completeness3/5

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

The tool is simple with a single parameter and has an output schema to define return values, so the description need not explain output. However, it omits usage boundaries and behavioral caveats that would help an agent select and invoke it safely. It is adequate for a simple tool but not complete.

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?

The schema only defines list_url as a required string with no description (0% coverage). The description compensates by specifying that it must be an IMDb list page and offers a concrete example, so the agent knows the expected URL shape. However, it leaves ambiguity about URL format and supported list types, so compensation is only partial.

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 clearly states the action (scrape), the target resource (IMDb list page), and the outcome (title ids). The example ('coming this year' list) makes the function immediately understandable. It does not explicitly name sibling tools, but the operation is clearly distinct from the title-search and queue-management siblings.

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 example 'coming this year list' implies when to use the tool, but there is no explicit statement of when to prefer it over alternatives like search_title, lookup_title, or check_candidates. No exclusions are given, so guidance is inferred rather than stated.

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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