Skip to main content
Glama

Get season cast

get_cast
Read-only

Full cast of a season with per-platform follower counts, baselines, growth windows (24h/7d/30d/since premiere), elimination status, and Instagram milestone projections. Time series are summarized as historyPoints counts — use get_follower_history for the series itself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
showYesSeason ID or slug, e.g. "12" or "love-island-usa-season-8". Use list_shows to discover.
searchNoCase-insensitive name filter.
statusNoFilter by contestant status, e.g. "active", "eliminated", "winner".

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint annotation already establishes that this is a safe read operation, and the description adds useful behavioral detail beyond that: it clarifies that time series are summarized as historyPoints counts, so an agent will not expect full underlying series that are available only via get_follower_history. This is especially valuable because there is no output schema.

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 front-loaded with the essential phrase 'Full cast of a season' and uses two efficient sentences that make it clear what is returned and when to use an alternative tool. There is no fluff or redundant explanation.

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?

With no output schema, the description adequately inventories the core returned fields and explicitly flags that time series data is summarized. It could mention things like default ordering or response shape, but as a cast listing tool with well-documented parameters, the description is sufficiently complete for correct invocation.

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 input schema already provides 100% coverage with descriptions for all three parameters (show, search, status), so the tool description does not need to re-explain them. The description adds context about the returned data, but not additional meaning for the parameters themselves.

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 states a specific verb and resource: it returns the full cast of a season with concrete data fields such as per-platform follower counts, growth windows, elimination status, and Instagram milestone projections. It also differentiates itself from get_follower_history by noting that time series are merely summarized here.

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 gives clear context: use this tool for a season-wide cast overview with summarized metrics. It explicitly steers the agent to get_follower_history when the full time series is needed. However, it does not directly contrast with all nearby siblings like get_contestant or get_engagement, so the when-to-use guidance is good but not exhaustive.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct resource or analysis need: cast summaries, single-contestant details, follower time series, follow/unfollow events, follow graph, trend events, and export output are cleanly separated. The descriptions explicitly cross-reference related tools, so an agent should be able to pick the right one without ambiguity.

Naming Consistency5/5

Tool names follow a consistent get_/noun and list_noun pattern, with export_season_csv as the only slight variation—but it still clearly uses verb_noun convention. camelCase is avoided, and duplicate or vague verbs are absent.

Tool Count5/5

Twelve tools is a well-scoped size for a read-only analytics data API. Each tool contributes a meaningful slice of the domain—discovery, show details, cast metrics, raw series, events, graphs, trends, usage, and export—without redundancy or bloat.

Completeness5/5

The surface covers the full read-only workflow: discover shows and seasons, list episodes, inspect contestants and cast, retrieve follower histories, engagement, follow relationships, trend events, and export a citation-ready CSV. No obvious lifecycle dead ends exist since the API is inherently data-access-oriented rather than CRUD.

Resources