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makiichikawa

stock-mcp-server

by makiichikawa

summarize_ir_information

Generate comprehensive investor relations summaries from local PDF documents for Japanese and US stocks. Input a stock symbol, optional language, and document type to get tailored IR insights.

Instructions

Generate comprehensive IR summary from local PDF documents for Japanese and US stocks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock symbol (e.g., 9202 for ANA, AAPL for Apple)
languageNoOutput languageja
companyNameNoCompany name (optional)
marketRegionNoMarket region for environment dataUS
documentTypeFilterNoFilter by specific document type (optional)
includeMarketEnvironmentNoInclude market environment data in the summary
Install Server

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It reveals that local PDF documents are the data source and the output is a summary, but it does not state prerequisites, side effects, failure modes, document selection behavior, or output format. This is under-disclosed for a tool with no annotation safety profile.

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?

One short sentence front-loads the main function and is appropriately compact. 'Comprehensive' is somewhat vague filler, but the description earns its place without unnecessary bulk.

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

Completeness2/5

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

For a tool with no output schema and 6 parameters, the description is thin. It omits what the summary contains, how local PDFs are discovered/selected, how language/documentTypeFilter affect behavior, and what an agent should prepare before invoking. Schema fills parameter meaning but not operational context.

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

Parameters3/5

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

All six parameters have schema descriptions, so the baseline is 3. The tool description does not add parameter-level guidance; 'Japanese and US stocks' broadly aligns with symbol/marketRegion but does not explain parameter behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Generate') and resource ('comprehensive IR summary') and scopes the source to local PDF documents for JP/US stocks, which distinguishes it from sibling data-retrieval tools. However, 'IR' is never expanded and it does not name the sibling it complements, such as extract_local_pdf.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to choose this tool instead of get_financial_data, get_10k_earnings_guidance, or extract_local_pdf. The only usage signal is the description's own semantics, leaving an agent to infer context.

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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