screener
Read-only
Cross-venue top-of-book snapshot for all assets across Polymarket, Kalshi, and Binance — a one-shot overview of the current state. No arguments.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
DepthFeed
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A4.2/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. Description adds value by specifying it is a cross-venue, top-of-book snapshot and a one-shot overview, providing context beyond structured fields.
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?
Single sentence with clear front-loaded purpose. Every word adds value; no wasted text.
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?
For a no-parameter snapshot tool, the description covers scope and behavior. However, it does not describe the return format or data structure, which could be useful given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage, the description simply states 'No arguments,' which is sufficient. Baseline for 0 params is 4, and the description adds clarity without redundancy.
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?
Description explicitly states it provides a cross-venue top-of-book snapshot for all assets across Polymarket, Kalshi, and Binance. This is a specific verb+resource and clearly distinguishes from sibling tools that target single venues or specific order books.
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?
Description implies usage for a one-shot overview with no arguments, but does not explicitly state when to avoid using it or suggest alternatives like venue-specific order book tools. Usage context is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
A4.1/5.0
Disambiguation5/5
Each tool targets a distinct venue and data type: Polymarket/Kalshi/Limitless-specific search, orderbook, and snapshot tools are clearly separated by prefix, while bars, backtest_paths, screener, and whoami serve unique purposes. No two tools could plausibly be confused in agent selection.
Naming Consistency4/5
Most tools follow a clear `<venue>_<action>_<object>` pattern (e.g., kalshi_get_orderbook, limitless_get_snapshots, polymarket_search_markets). A few like backtest_paths, bars, screener, and whoami break the pattern, but they are descriptive and consistent with their domain. Overall predictable and legible.
Tool Count5/5
15 tools is well-scoped for a multi-venue market data API. Each tool adds meaningful functionality—search, snapshots, candles, orderbooks, screener, session info—without redundancy. The count aligns well with the apparent coverage of prediction markets, crypto, and equities.
Completeness5/5
The surface covers read operations for all major venues: search, market detail, orderbook, historical snapshots, and OHLCV bars. It also includes backtesting, cross-venue screener, and session introspection. No obvious dead ends or missing critical operations for a data-centric server.