Skip to main content
Glama

Trakt

by io.github.pipeworx-io

Get Episode

get_episode
Read-onlyIdempotent

"Episode [N] of season [M] of [show]" / "what happens in [show] S[X]E[Y]" / "episode info / runtime / title" — single episode record by show + season + episode number. Returns title, summary, runtime, air date, IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seasonYesSeason number
episodeYesEpisode number
show_idYestrakt show ID/slug
extendedNofull | images

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsNoTrakt, TVDB, IMDB IDs
titleNoEpisode title
votesNoNumber of votes
numberNoEpisode number
ratingNoEpisode rating
seasonNoSeason number
overviewNoEpisode plot
updated_atNoLast update timestamp
first_airedNoAir date

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds context by listing specific return fields, which is additional value beyond annotations.

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?

The description is concise (2-3 lines), front-loaded with example queries, and efficiently conveys purpose and output. Every sentence adds value.

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?

Given the presence of an output schema, the description adequately covers purpose, input, and output. For a simple retrieval tool, it is complete and self-contained.

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 baseline is 3. The description does not add new semantic meaning to parameters beyond the schema examples and field names.

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?

The description clearly states it retrieves a single episode record by show, season, and episode number, listing returned fields (title, summary, runtime, air date, IDs). This distinguishes it from siblings like get_movie, get_show, and list_seasons.

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 description implies usage for specific episode queries via example patterns, but does not explicitly state when to use this tool versus alternatives (e.g., list_seasons for all episodes). No exclusion criteria are provided.

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

All Trakt toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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