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j-quants-doc-mcp

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by J-Quants

fetch_spec_page

Fetch J-Quants API specification pages by path. Retrieve endpoint details or reference data like holiday divisions and market codes, and follow Markdown links for extra information.

Instructions

指定されたパスのSpecificationページを取得する。

エンドポイント詳細だけでなく、参照データページ(例: 休日区分、市場コード等)も取得できます。 Markdown内のリンクを辿って追加情報を取得する際に使用してください。

Args: path: Specificationページのパス(例: /spec/mkt-cal/holiday-division)

Returns: Specificationページの情報を含む辞書: - content: Markdownテキスト - source_url: 取得元URL - path: リクエストされたパス - cached: キャッシュから取得したかどうか - instruction: LLMへの指示

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the return dictionary fields, including a 'cached' flag indicating potential caching behavior, but does not mention authentication, error handling, or rate limits. The safety profile is implied as read-only, but not explicitly stated.

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 brief purpose statement, usage note, and separately labeled Args/Returns sections. It is not overly verbose, and each section contributes necessary information. Slightly longer than the ideal two-sentence format, but still efficient.

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?

For a simple tool with one parameter and no output schema, the description covers the essential aspects: purpose, usage, parameter example, and return fields. It lacks explicit error or authentication details, but overall it gives an agent enough to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero description coverage, but the description defines the 'path' parameter with an example ('/spec/mkt-cal/holiday-division'), adding meaning that the schema lacks. It does not go into exhaustive detail about path construction, but the example is sufficient for most cases.

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 clearly states that the tool retrieves a Specification page for a given path, and explicitly notes it can also fetch reference data pages (e.g., holiday divisions, market codes). This distinguishes it from sibling tools like describe_endpoint by emphasizing raw page retrieval and link-following scenarios.

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?

The description provides a clear usage context: 'Use when following links in Markdown to obtain additional information.' However, it does not explicitly mention alternatives like describe_endpoint or state when not to use this tool, so it falls short of a perfect score.

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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