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shigechika

jquants-mcp

by shigechika

get_sector_briefing

Read-onlyIdempotent

Evaluate sector valuations with median PER, PBR, ROE, and margin ratios to find undervalued industries.

Instructions

Return sector-level median PER, PBR, ROE, and margin ratio (業種別ブリーフィング). All plans.

Use for セクターバリュエーション・業種別PER/PBR・割安セクター・業種別信用倍率 queries. PER excludes net-loss stocks (EPS≤0); PBR excludes negative-book stocks. ROE does not exclude net-loss stocks -- neither the native ROE value (returned regardless of EPS sign) nor the EPS/BPS fallback (unlike PER's guard, it never required EPS>0) filters them out. See also get_market_briefing (market-wide), get_stock_briefing (single stock), get_sector_performance (騰落率).

[Supported plans] Free / Light / Standard / Premium (cache-only, no API call) Note: margin_ratio fields are null unless Standard/Premium margin cache is populated.

Args: sector_type: "s33" (default, 33 TSE sub-sectors) or "s17" (17 top-level sectors).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sector_typeNos33

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Annotations already declare read-only, non-destructive, idempotent behavior. The description adds substantial context: cache-only with no API call, supported plans, margin_ratio null unless Standard/Premium cache is populated, and detailed PER/PBR/ROE exclusion rules. This goes far 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 structured into clear sections (purpose, usage, plan support, args) and every sentence carries relevant info. It is slightly dense but not wasteful; no filler. A 4 is appropriate as it is informative without being bloated.

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?

For a single-parameter tool with an output schema, the description covers plan limitations, data nullability, filtering rules, and sibling references. It gives the agent complete enough context to decide when and how to invoke the tool correctly.

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?

The input schema provides no description for sector_type (0% coverage), but the description compensates fully by explaining the two possible values ('s33' default, 33 TSE sub-sectors; 's17' 17 top-level sectors). This gives the agent all necessary parameter context.

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?

Begins with a specific verb and resource: 'Return sector-level median PER, PBR, ROE, and margin ratio', which clearly states the tool's function. It distinguishes itself from siblings by explicitly naming get_market_briefing (market-wide), get_stock_briefing (single stock), and get_sector_performance (騰落率), making the purpose unmistakable.

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 explicit use cases ('Use for セクターバリュエーション・業種別PER/PBR・割安セクター・業種別信用倍率 queries') and lists alternative tools with their scopes. However, it lacks an explicit 'when-not' statement, though the context and alternatives clearly guide selection.

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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