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jlucasmcrell

Apify Public Data & Leads

twitch_live_streams

Extract live Twitch streams, viewer counts, and game categories by game or language to track current streaming trends.

Instructions

Scrape live streaming channels, viewer counts, and game categories from Twitch. Backed by captainhandsome/twitch-live-streams-scraper.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoen
game_nameNoe.g. 'Fortnite' or 'Just Chatting'
max_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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, and it discloses almost nothing: no rate limits, no auth or credential needs, no latency/availability caveats, no pagination or result-ordering behavior, and no note on what happens when game_name matches nothing. The provenance line ('Backed by captainhandsome/twitch-live-streams-scraper') is the only added context, which is minor.

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?

Two short sentences, and the functional content is front-loaded ahead of the provenance sentence. Nothing is padded, though the second sentence contributes little to correct invocation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description partially covers the return shape by naming channels, viewer counts, and game categories. It is still silent on result structure, pagination, and error behavior, and two of three parameters are undocumented, leaving the definition just barely sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33% — game_name carries an example but language and max_results are bare types with defaults. The description does not compensate: it never mentions language filtering, result caps, or the meaning of the default values, so an agent must guess whether max_results is a hard cap or a hint.

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 states a specific verb (scrape) and a specific resource (live streaming channels, viewer counts, and game categories) tied to a named source (Twitch). That is enough for an agent to know exactly what comes back, though it offers no differentiation from siblings — which here is moot since every sibling covers an unrelated domain (maps, jobs, SEC filings, contracts, rentals).

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?

Usage is only implied: 'online live streaming channels ... from Twitch' makes the triggering scenario reasonably obvious, but there is no explicit when-to-use statement, no prerequisites, and no guidance on defaults such as language='en' or max_results=10. No alternative tool is named or excluded.

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