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shigechika

jquants-mcp

by shigechika

get_comparison_chart_data

Read-onlyIdempotent

Retrieve time-series data to compare up to 10 stocks, normalised by return percentage or raw prices, for performance comparison charts.

Instructions

Return time-series data for a multi-stock comparison (複数銘柄比較データ). All plans.

Use for 比較チャート・パフォーマンス比較・リターン比較・relative performance queries (up to 10 codes). Returns JSON records suitable for React artifact rendering with Recharts LineChart. For ローソク足・candlestick charts use sibling get_candlestick_data (returns JSON).

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

Args: codes: 1–10 stock codes (e.g. ["7203", "8697"]). from_date: Range start (YYYYMMDD or YYYY-MM-DD), inclusive. to_date: Range end (YYYYMMDD or YYYY-MM-DD), inclusive. mode: "return_pct" (default, normalised to 0% at first bar) or "price" (raw adjusted close). labels: Custom legend labels per code. Omit for auto-generated names.

Returns: dict with keys: mode — echoes the requested mode from_date — normalised YYYY-MM-DD to_date — normalised YYYY-MM-DD records — list of {"date": str, : float, ...} rows (Recharts dataKey format) series_keys — ordered list of label strings matching records keys On error: {"error": ""}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codesYes
from_dateYes
to_dateYes
modeNoreturn_pct
labelsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Description adds context beyond annotations: cache-only, no API call, and details return format and error handling. Annotations already indicate readOnly, destructive, idempotent, and no contradiction.

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?

Well-organized with clear sections: purpose, usage, supported plans, Args list, Returns description. Front-loaded with main purpose. Every sentence provides essential information without redundancy.

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 5 parameters, output schema, and no nested objects, the description covers all aspects: purpose, parameters, return format, error format, and usage guidance. No gaps for effective tool invocation.

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?

All 5 parameters are fully documented in description with ranges, formats, defaults, and examples, compensating for 0% schema description coverage. For example, codes is documented as 1-10 stock codes with example.

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 clearly states 'Return time-series data for a multi-stock comparison' and distinguishes from sibling get_candlestick_data by explicitly naming it as the alternative for candlestick charts.

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 use cases for comparative charts and performance comparison, and provides alternative sibling tool for candlestick data. Also mentions plan support and cache-only behavior.

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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