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QuantApe Markets

get_smart_list

Read-only

Symbols currently in a stock screen — e.g. today's earnings, golden-cross buy signals, AI beneficiaries (paged, max 200 per call). Descriptive, not a recommendation. Free within your daily allowance (anonymous 5/day by IP, signed-in users 10/day, power users 50/day); beyond that $0.01 per call via x402 (USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoSymbols per page, 1-200 (default 200).
offsetNoZero-based offset into the screen for paging.
list_idYesScreen id from list_smart_lists (e.g. day_gainers, golden_cross, ai_beneficiaries).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the readOnlyHint=true annotation, the description discloses additional behavioral traits: it is 'Descriptive, not a recommendation,' it is paged with a 200-per-call maximum, and it includes specific free-allowance tiers plus overage pricing via x402. This adds meaningful operational and reliability context.

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?

The description is a single informative sentence that front-loads the core purpose and then expands with examples and cost details. Each element is relevant, though the pricing breakdown adds some length; it remains reasonably concise and well ordered.

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 three-parameter, read-only tool with no output schema, the description fully equips the agent: it explains what data is returned (symbols), that results are paged, and when extra cost may apply. It could add a bit more about the return shape or paging semantics, but nothing critical is missing.

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 description coverage is 100%, so the necessary parameter information is already in the JSON schema. The main description adds example screen aliases such as 'golden-cross buy signals' (tying to list_id examples like golden_cross) and mentions paging, but does not materially extend the schema's own descriptions.

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: 'Symbols currently in a stock screen' with clear examples (today's earnings, golden-cross buy signals, AI beneficiaries). This distinguishes it from sibling tools like get_smart_list_changes, get_smart_list_metrics, and list_smart_lists by indicating it retrieves the current screen membership.

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 implied through phrasings like 'Symbols currently in a stock screen' and 'paged, max 200 per call,' but there is no explicit when-to-use vs. alternatives or exclusions. It does not name sibling tools or state when to prefer get_smart_list_changes or get_list_criteria.

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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