INDUSS Research Intelligence MCP Server

ratio_analysis

Read-onlyIdempotent

Compute profitability, liquidity, leverage, and return metrics plus multi-period CAGR from financial statements. Deterministic calculation without search or LLM tokens.

Instructions

Performs deterministic financial ratio analysis (profitability, liquidity, leverage, returns) plus multi-period CAGR trend over a set of FinancialStatement objects (Income Statement / Balance Sheet / Cash Flow). Pure calculation — no search, no LLM tokens.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "statements": "<statements>"
    },
    "name": "ratio_analysis"
  }
}

Input Schema

Name	Required	Description	Default
`statements`	Yes	Chronologically ordered (oldest first) financial statements, e.g. from the financial_statements tool
`companyName`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already mark readOnlyHint, idempotentHint, and openWorldHint, and the description adds 'deterministic' and 'Pure calculation — no search, no LLM tokens', reinforcing and extending the behavioral profile. It does not contradict annotations. It could add edge-case or output-format details, but the annotations carry part of the burden.

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 sentences, front-loaded with the primary purpose, with no redundant filler. The behavioral qualifier 'Pure calculation — no search, no LLM tokens' is compact and earns its place.

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 calculation tool with a detailed input schema, the description covers the key inputs, the computation scope, and the output themes. There is no output schema, so a little more detail about the returned structure would improve completeness, but the description is still sufficient for selection and invocation.

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?

The schema describes the main 'statements' parameter with ordering and source context, and the description adds the notion of multi-period CAGR and the financial statement categories. However, optional fields like companyName and the exact required financial metrics (revenue, netProfit) are not explained beyond the schema, and schema description coverage is only 50%.

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 uses a specific verb ('performs') with a clear resource ('financial ratio analysis over FinancialStatement objects') and lists the exact ratio categories and CAGR trend. The phrase 'Pure calculation — no search, no LLM tokens' also helps distinguish it from sibling tools that generate narratives or search data.

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 clear context for when to use it: when deterministic financial ratio analysis or multi-period CAGR is needed, not when search or LLM-driven output is required. It does not explicitly name sibling alternatives or state when-not-to-use conditions, so it stops short of a 5.

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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