top_watched
Top 100 games by current live Twitch viewership (15-min updates). Optionally scoped to one Steam genre.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| genre | No |
Top 100 games by current live Twitch viewership (15-min updates). Optionally scoped to one Steam genre.
| Name | Required | Description | Default |
|---|---|---|---|
| genre | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does disclose useful traits: results are limited to 100, reflect current live Twitch viewership, update every 15 minutes, and can be genre-scoped. However, it does not describe the return structure, sort behavior beyond 'top,' or handling of invalid genre values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one tight sentence that front-loads the core result ('Top 100 games') and then adds the cadence and optional filter. Every clause adds value and there is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple optional-parameter list tool, the description covers the essential context: what is returned, update frequency, and the one available filter. It is slightly incomplete by not describing the returned fields or what happens when no genre is supplied, and there is no output schema to fill that gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only provides the raw property name 'genre' with no textual description and 0% coverage. The description compensates meaningfully by stating that the parameter is optional, is a Steam genre, and scopes the result set to one genre. It still stops short of enumerating accepted genre values or format, but it is sufficient for basic invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific output: 'Top 100 games by current live Twitch viewership.' It also names the optional scope ('one Steam genre') and the 15-minute update cadence. This distinguishes it from likely siblings like top_played without needing to open schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the description: use this tool when the agent needs current Twitch viewership rankings, optionally filtered by genre. However, it does not explicitly contrast this with alternatives such as top_played or state when not to use it, so the guidance is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a clearly distinct slice of the domain: per-game detail, genre aggregates, top lists, released-game aggro, unreleased-game hype, search, and warehouse status. Even the two 'board' tools are unambiguous because one is explicitly for live/released games and the other for unreleased anticipation.
Tool names are all lowercase snake_case and generally readable, but they mix conventions: noun-style names like game_detail and genre_rollup sit alongside verb-style names like get_summary and search_games, plus adjective-style names like top_played and top_watched. The pattern is not chaotic, but it is inconsistent enough to be a minor usability issue.
Eight tools is a well-scoped size for an analytics server covering catalog lookup, detailed game profiles, genre rollups, top lists, and specialized signal boards. Each tool earns its place and there is no obvious redundancy.
The surface covers the core workflows: understand data coverage, search for games, inspect a game, view rankings, see genre-level aggregates, and check both released-game and unreleased-game attention signals. A minor gap is the lack of a direct per-game aggro score endpoint, though the underlying data in game_detail makes this derivable.