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Juuuuuuni

Stock MCP Server

by Juuuuuuni

screen_us_momentum

Screen US stocks for momentum by detecting volume surges within a lookback period and verifying trend alignment using Minervini Trend Template and optional filters like 52-week high proximity and relative strength outperformance.

Instructions

미국 주식에서 '최근 N일 내 거래량 급증 + 추세 정합' 종목을 필터링합니다.

[시드] symbols 미지정 시 Yahoo most_actives + day_gainers + small_cap_gainers [사전필터] 순차 적용: · 당일 과열 제외: 오늘 등락률이 exclude_if_up_pct 이상이면 제외 (추격 매수 방지) · 거래량 급증: max(최근 lookback일) / 이전 baseline일 평균spike_threshold · Minervini Trend Template (옵션): Stage 2 상승추세 6조건 · 52주 고점 근접 (옵션): 현재가 ≥ 52주고점 × high_proximity · RS vs SPY (옵션): 3개월 초과수익률 ≥ min_rs_outperformance (pp) [전략] 10가지 기술적 전략 적용

Args: symbols: 스크리닝할 티커 목록. None이면 Yahoo 스크리너에서 시드 수집 top_n: 시드 후보 상한 exclude_if_up_pct: 오늘 등락률이 이 값(%) 이상이면 제외. None이면 미적용 (기본 10.0) lookback_days: 거래량 급증 룩백 spike_threshold: 급증 배율 baseline_days: 비교 기준 기간 enable_trend_template: Minervini Trend Template 사용 여부 enable_near_52w_high: 52주 고점 근접 필터 사용 여부 high_proximity: 52주 고점 대비 허용 비율 (0.75 = 고점의 75% 이상) enable_rs_filter: SPY 대비 RS 필터 사용 여부 rs_period_days: RS 수익률 계산 기간 (기본 63 ≈ 3개월) min_rs_outperformance: 벤치마크 초과수익 하한 (pp)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolsNo
top_nNo
exclude_if_up_pctNo
lookback_daysNo
spike_thresholdNo
baseline_daysNo
enable_trend_templateNo
enable_near_52w_highNo
high_proximityNo
enable_rs_filterNo
rs_period_daysNo
min_rs_outperformanceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It details the step-by-step filtering logic (exclusion, volume spike, trend template, etc.) and mentions 10 technical strategies, but omits specifics about the strategies and does not disclose if the tool has any side effects (e.g., rate limits).

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 with a summary, subsections, and parameter list. It is fairly long but every section adds value. Could be slightly more concise without losing info.

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?

Covers the filtering logic and all 12 parameters comprehensively. Output is not described but output schema exists. Missing details on the 10 technical strategies, but overall adequate for the complexity.

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%, but the description thoroughly explains each parameter with defaults and meaning (e.g., exclude_if_up_pct, spike_threshold). This adds substantial value beyond the raw schema.

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 explicitly states it filters US stocks based on volume surge and trend alignment, with specific references to Yahoo data sources. It clearly differentiates from sibling tools like screen_kr_momentum and screen_us_breakout by specifying 'US' and 'momentum' criteria.

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?

Provides clear context on when to use (filtering momentum stocks from Yahoo) and details the sequential pre-filters. However, lacks explicit 'when not to use' or direct comparison to siblings like diagnose_stock.

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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