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Johnhyeon

StockLens

by Johnhyeon
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Remote

get_us_screener

Read-onlyIdempotent

Identify US stock opportunities with preset screeners for gainers, most actives, and undervalued growth. Optionally filter to common stocks to avoid warrants and rights.

Instructions

US stock screener — 미국 주식 프리셋 스크리너 (US predefined screener). "오늘 급등주", "top gainers", "가장 많이 거래된 종목", "저평가 성장주" 같은 질문에 사용합니다.

사용 가능 preset: day_gainers, day_losers, most_actives, most_shorted_stocks, aggressive_small_caps, growth_technology_stocks, undervalued_growth_stocks, undervalued_large_caps, small_cap_gainers, conservative_foreign_funds

각 행에 증권 유형(common_stock/warrant/right/unit/adr/etf/unknown)이 붙습니다. small_cap_gainers 같은 프리셋에는 GRABW(워런트)·KLXER(라이츠) 같은 파생 식별자가 섞여 나옵니다 - 보통주 후보만 원하면 common_stock_only=True. 유형을 확인할 수 없는 항목은 unknown 으로 남고 보통주로 치지 않습니다.

Args: preset: 스크리너 ID (기본 day_gainers) count: 반환 종목 수 (기본 20) common_stock_only: True 면 보통주만 남깁니다 (unknown 도 제외)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
presetNo
common_stock_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.1.3
    • removedInput schema / properties / common_stock_only / default
      Removed value: -false
    • removedInput schema / properties / count / default
      Removed value: -20
    • removedInput schema / properties / preset / default
      Removed value: -"day_gainers"
  2. Changed1 schema field changedv1.0.1
    • addedInput schema / properties / common_stock_only
      Added value: +{
+  "default": false,
+  "title": "Common Stock Only",
+  "type": "boolean"
+}
  3. First observedv0.4.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context beyond annotations: it discloses that each row includes a security type, that certain presets may contain derivative identifiers like warrants/rights, that common_stock_only filters them, and that unknown types remain as 'unknown'. It also provides default values for preset and count. This is valuable extra behavior not captured in annotations.

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 well-structured: it opens with a one-line purpose, gives example queries, lists presets, explains security-type behavior, and ends with an Args section. Every sentence adds value; there is no filler. It is slightly long due to the bilingual text and detailed notes, but the structure makes it scannable and front-loaded with the core purpose.

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?

Given the output schema exists (has_output_schema=true) and annotations cover safety, the description covers what an agent needs to call this tool correctly: it explains presets, count, the common_stock_only filter, and the security-type behavior. It does not describe the full return structure, but the output schema likely handles that. It also lacks error conditions or rate limits, but these are not critical for a read-only, idempotent screener. Overall, it is complete enough for correct usage.

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

Parameters5/5

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

Schema coverage is 0%, so the description fully carries the burden of explaining parameters. It does so comprehensively: preset is defined as a screener ID with a full list of allowed values and default 'day_gainers'; count is described as the number of stocks to return with default 20; common_stock_only is explained with the exact effect (only common stocks remain, unknown excluded). This goes beyond the bare schema and gives agents actionable semantics.

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 it's a US stock screener with predefined presets, giving concrete example queries ('오늘 급등주', 'top gainers', etc.) and a full list of 10 preset identifiers. It distinguishes itself from sibling tools like get_us_price or get_sector_stocks by focusing on preset-based screening rather than price, info, or sector data. The verb 'get' + resource 'screener' is specific and unambiguous.

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

Usage Guidelines4/5

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

The description provides clear when-to-use guidance via example queries and explicitly explains when to set common_stock_only=True (when only common stocks are wanted, filtering out warrants/rights/unknown). It does not explicitly mention when to use alternative tools, but the preset examples and parameter explanations give enough context for an agent to select this tool for preset-based screening. The guidance is functional but lacks explicit exclusions.

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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