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shigechika

jquants-mcp

by shigechika

detect_volume_surge

Read-onlyIdempotent

Detect stocks with abnormally high trading volume on a given date by comparing volume to a trailing baseline average.

Instructions

Identify stocks with abnormally high trading volume (出来高急増) on a given day. All plans.

Use for 出来高急増・出来高異常・売買活況・volume spike queries. surge_ratio = Vo / mean(prior baseline_days). For price extremes use detect_52w/ytd_high_low; for price limits use detect_price_limit. Data available ~17:15 JST on trading days.

[Supported plans] Free / Light / Standard / Premium (cache-only, no API call)

Args: date: Trading date (YYYYMMDD or YYYY-MM-DD). multiplier: surge_ratio threshold (default 2.0). baseline_days: Trailing sessions for baseline average (default 20). code: Optional stock code. Omit to scan all stocks. detail: Include full per-stock data array (default False).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYes
multiplierNo
baseline_daysNo
codeNo
detailNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Beyond annotations (readOnly, idempotent), description adds the surge ratio formula, data availability time, and plan restrictions, providing key behavioral context.

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?

Description is well-structured: purpose, usage, formula, timing, plans, then parameter details. Every sentence adds value; no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, usage, formula, timing, parameters, and output context (with output schema existing). All essential information for a detection tool is present.

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?

With 0% schema coverage, the description's 'Args' section explains all five parameters: format, defaults, and optionality, fully compensating for the schema gap.

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 starts with 'Identify stocks with abnormally high trading volume on a given day' and contrasts with sibling tools like detect_52w_high_low and detect_price_limit, making purpose unmistakable and distinguishing from alternatives.

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 states when to use ('Use for 出来高急増・出来高異常・売買活況・volume spike queries') and when not to ('For price extremes use detect_52w/ytd_high_low; for price limits use detect_price_limit'), plus timing details.

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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