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ReelRecs

Find a movie or show

search_titles
Read-onlyIdempotent

Find a movie or TV show from its name, a remembered fragment or a typo. Resolve its exact version before recommendations or availability checks. Returns canonical IDs and rich title context: description, genres, subgenres, tags, subjects, keywords, cast, directors, language and runtime. Choices cover viewer-mentioned titles or assistant-chosen mood references.

Input Schema

NameRequiredDescriptionDefault
requestYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real behavioral context beyond that: fuzzy matching tolerates misspellings and fragments, results carry canonical IDs that must not be guessed, and the payload includes description, genres, tags, cast, directors, language and runtime. It does not mention result cap or ranking/ambiguity handling.

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 action, followed by sequencing, then return contents — a sensible order with little filler. The closing sentence about 'viewer-mentioned titles or assistant-chosen mood references' is vague and slightly dilutes an otherwise tight definition.

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?

An output schema exists, so the enumerated return fields are a bonus rather than a necessity. For a single-parameter search with a nested request object, the definition covers purpose, precondition, and fuzzy-match tolerance; the gap is the undocumented kind/limit controls inside the nested object.

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 reported at 0%, so the description must compensate; it explains the query semantics well ('remembered fragment or a typo') and gestures at version resolution, which maps to the year field. However, the nested request object's 'kind' (movie/show/any) and 'limit' controls are never mentioned, leaving half the nested surface undocumented.

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 ('Find a movie or TV show') and immediately broadens the input tolerance to fragments and typos. It also scopes the output ('canonical IDs and rich title context'), which separates it cleanly from siblings like get_title_peers or get_watch_options that consume an already-resolved title.

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?

Gives explicit sequencing guidance: 'Resolve its exact version before recommendations or availability checks,' which tells the agent to call this before recommend_titles/get_watch_options. It stops short of naming those siblings or stating when NOT to use it (e.g., browsing rather than searching).

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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