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Trakt

by io.github.pipeworx-io

Trending

trending

Read-onlyIdempotent

"What's trending on TV / movies right now" / "popular shows this week" / "what people are watching" — currently-trending movies or shows on Trakt (ranked by active watchers). Pass type="movies" or "shows". Use for "what should I watch" recommendations.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`page`	No	1-based page
`type`	Yes	movies \| shows
`limit`	No	1-100 (default 10)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`count`	Yes	Number of items returned.
`items`	Yes	Array of trending movies or shows

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds context about the data source (Trakt) and ranking method (active watchers), which provides value beyond the annotations. No contradictions.

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?

The description is concise and front-loaded with the purpose. It is a single effective sentence, though the use of quotes and slashes makes it slightly less clean. Every part is relevant.

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?

Given the existence of an output schema, the description adequately covers the tool's purpose, data source, and ranking. It could mention pagination or result format, but these are covered by the schema. Overall sufficient.

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 description adds little beyond what the schema already provides. It reiterates the type parameter but does not offer additional semantic meaning for the parameters.

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 it returns currently-trending movies or shows ranked by active watchers, using specific verb and resource. However, it does not explicitly distinguish from sibling tools like 'popular' or 'pipeworx_trending', which may also provide trending content.

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 provides clear context for using the tool: pass type='movies' or 'shows', and use for 'what should I watch' recommendations. It does not, however, include when not to use it or mention alternatives.

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

All Trakt tools Inspect

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TDQS

A3.8/5.0

Disambiguation2/5

The tool set has significant overlap among query and research tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research) and among entity/company tools (entity_profile, compare_entities, recent_changes). Despite detailed descriptions, an agent would struggle to select the correct tool without careful reading, especially for nuanced differences.

Naming Consistency2/5

Tool naming is inconsistent: some start with verbs (ask_, generate_, validate_, scan_, subscribe) while others are nouns (entity_profile, popular, trending, search, recent_alerts, recent_changes). The snake_case style is consistent, but the verb_noun pattern is not, making predictions of tool names difficult.

Tool Count3/5

38 tools is on the high side for a single server, but the scope is broad (general query, research, Trakt, subscriptions, memory). The count is appropriate for the wide range of functionality, though some tools could be merged to reduce cognitive load.

Completeness4/5

The tool set covers a very wide range of tasks: querying, research, entity profiles, comparisons, subscriptions, memory, Trakt operations, etc. For the Trakt domain, it has all essential operations (search, get, list, trending). The Pipeworx side has a comprehensive set for data access, grounding, and validation. Minor gaps exist (e.g., no update for subscriptions), but overall it is well-covered.

Resources