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Compare companies

compare_companies

Compare two or more Japanese listed companies on financial metrics like revenue and net income, with computed ratios. Input company codes to get side-by-side results in JPY.

Instructions

Compare multiple companies side by side on selected metrics (default: revenue, operating_income, net_income, total_assets, total_equity, operating_cash_flow). Also returns derived_ratios (operating_margin_pct, net_margin_pct) computed from the served values. All monetary values in JPY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codesYesTwo or more 4-digit codes, e.g. ['7203','7974']
metricsNoEnglish metric keys to compare (default: common set)
Behavior3/5

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

No annotations are provided, so the description is the sole source. It states it computes derived ratios and returns metrics in JPY, but does not disclose error handling, rate limits, or behavior for missing data. Adequate but could be more transparent.

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?

Two tight sentences: first states purpose and default metrics, second adds derived ratios and currency. No wasted words, front-loaded with key info.

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?

Given no output schema, the description covers returned metrics and currency but omits output structure (e.g., array of company objects). For a comparison tool with moderate complexity, it is mostly complete.

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?

Schema documentation covers both parameters fully (100% coverage). The description adds value by explaining default metrics, derived ratios, and currency, providing context beyond the schema's property descriptions.

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 explicitly states the tool compares multiple companies side by side on selected metrics, lists default metrics (revenue, operating_income, etc.), and notes derived ratios and currency (JPY). This clearly distinguishes it from siblings (get_financials for single company, list_companies for listing, search_company for search).

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 clearly indicates when to use the tool (for comparing companies on metrics) but does not explicitly state when not to use it or provide exclusions. However, given sibling tool names, the usage context is implied.

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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