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ohadf2015

stoquant-mcp

by ohadf2015

List prebuilt screens

stoquant_list_prebuilt_screens
Read-only

List curated prebuilt stock screens with IDs and descriptions. Pick a strategy from value, momentum, growth, or ML-driven screens to run for optimized screening.

Instructions

List the curated prebuilt screens with their id, name, and description. Available screens: 'undervalued-gems' (low P/E, P/B value plays), 'momentum-leaders' (strong price momentum), 'oversold-bounce' (RSI reversal setup), 'ml-outperform' (ML-predicted S&P 500 outperformance), 'hidden-gems' (small-cap value with confirmation signals), 'growth-explosion' (high-growth micro/mid-caps before discovery), 'pre-explosion' (multibagger pattern: revenue acceleration + insider + fundamentals). Call this first, then run one with stoquant_run_prebuilt_screen — it is faster and better-tuned than hand-built filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
universeNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds the expected return fields (id, name, description) and the full inventory of screens. It does not contradict the annotations, though it omits how the optional universe parameter might affect results, which is more of a parameter-semantics gap.

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 efficiently structured, leading with the core purpose, then listing each screen with a useful parenthetical, and ending with actionable usage advice. Every sentence earns its place with no filler.

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 simple read-only list tool, the description provides the return structure and the complete set of screen names. The only notable gap is the unexplained universe parameter, but overall the description is sufficiently complete for the tool's low complexity.

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

Parameters1/5

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

Schema description coverage is 0%, and the description never mentions the 'universe' parameter. The agent is left without any guidance on what this parameter does or whether it filters the list, so the description completely fails to compensate.

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 clearly states 'List the curated prebuilt screens with their id, name, and description,' which is a specific verb+resource construction. It enumerates each available screen, making it easy to distinguish from sibling tools like stoquant_run_prebuilt_screen.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Call this first, then run one with stoquant_run_prebuilt_screen' and contrasts with 'hand-built filters,' giving clear when-to-use and alternative guidance.

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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