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shigechika

jquants-mcp

by shigechika

detect_price_limit

Read-onlyIdempotent

Identify stocks that hit daily price limits (upper/lower) on a trading date. Returns triggered rows, or per-stock UL/LL status when a specific code is provided.

Instructions

Find stocks that hit the daily price limit (ストップ高/安) on a trading day. All plans.

Use for ストップ高・ストップ安・値幅制限 queries. UL=1 → upper limit touched; LL=1 → lower. For volume spikes use detect_volume_surge; for VWAP pressure use compare_close_vs_vwap. 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). code: Optional stock code. Omit to scan all stocks (returns only triggered rows). When a code is given, that stock's row is always returned, even if it did not hit the limit, so callers can read its UL/LL state directly. detail: Include full per-stock data array (default False).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNo
dateYes
detailNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Despite strong annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds substantial context: data available ~17:15 JST, cache-only (no API call), supported plans, and the behavioral nuance that when a code is provided the row is always returned even if no limit hit. This goes well beyond the 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 organized into clear sections (purpose, usage, alternatives, timing, plans, args) and front-loaded with the main action. It is slightly longer than strictly necessary due to the plan list and detailed param explanations, but every sentence contributes value.

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?

Given the output schema exists, return values need not be detailed. The description covers usage, exclusions, timing, plan availability, cache behavior, and parameter semantics, making it complete for successful invocation. The only minor omission is a direct statement about the output schema, but it's not required.

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 description coverage is 0%, but the description fully compensates by explaining each parameter: date format (YYYYMMDD or YYYY-MM-DD), code's optional behavior and the consequence of omitting vs specifying it, and detail's purpose (include full per-stock data array). This adds meaning the schema alone lacks.

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 opens with a specific verb and resource: 'Find stocks that hit the daily price limit (ストップ高/安) on a trading day.' It clearly distinguishes this tool from siblings by explicitly naming detect_volume_surge and compare_close_vs_vwap as alternatives for different queries.

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?

Provides explicit when-to-use guidance: 'Use for ストップ高・ストップ安・値幅制限 queries.' It also names alternatives for other scenarios ('For volume spikes use detect_volume_surge; for VWAP pressure use compare_close_vs_vwap'), making the choice between tools unambiguous.

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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