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rajyash205

INDUSS Research Intelligence MCP Server

by rajyash205

comparables_valuation

Read-onlyIdempotent

Apply supplied peer multiples (EV/EBITDA, P/E, EV/Sales) to target metrics to derive low/median/high valuation bands and a blended equity range. No peer picking or missing-data guessing.

Instructions

Applies a supplied set of peer trading multiples (EV/EBITDA, P/E, EV/Sales) to the target company's own financial metrics to derive an implied low/median/high valuation band per multiple type, plus a single blended equity-value range (enterprise-value bands are bridged to equity via netDebt). This tool picks no peers and invents no multiples — pass real peer figures (e.g. from listed_peer_comparison) and it does the banding/blending arithmetic deterministically. A multiple type is silently omitted (see issues) if you didn't supply both the peer multiples and the matching target metric — it never guesses a missing input.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
peersYesPeer multiples — e.g. sourced from listed_peer_comparison output or your own research
targetYes
companyNameNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses that missing inputs cause silent omission of a multiple type and reports via an 'issues' field. It also emphasizes deterministic arithmetic, fully aligning with annotations with no contradictions.

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 a bit long but each sentence adds distinct value: the first defines the function, the second clarifies inputs and determinism, and the third explains missing-data behavior. It is not excessively redundant.

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 the nested schema and no output schema, the description adequately describes the output (valuation bands and blended range) and the issues mechanism. It does not specify exact output fields, but enough context is provided for a basic understanding.

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?

Schema description coverage is only 33%, with descriptions only on peers and target.netDebt. While the tool description explains the roles of the multiples and netDebt, it doesn't clarify all parameters (e.g., sharesOutstanding, companyName, revenue, netProfit) individually. The names are semi-intuitive, but not fully compensated.

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 applies peer trading multiples to target financial metrics to derive valuation bands, naming specific multiples and the output. It differentiates from sibling tools like dcf_valuation by focusing on peer-based comparables.

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?

It explicitly instructs to pass real peer figures (e.g., from listed_peer_comparison) and notes that it picks no peers, giving a clear prerequisite and source. While it doesn't explicitly contrast with DCF or other valuation methods, the condition for use is well 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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