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viraj43

INDUSS Research Intelligence MCP Server

by viraj43

litigation_history

Read-only

Screens Indian legal and regulatory sources to uncover litigation, penalties, insolvency proceedings, and director disqualifications tied to a company or promoter.

Instructions

Screens SEBI, NCLT, and legal-journalism sources (IndianKanoon, LiveLaw, Bar & Bench) for litigation, regulatory penalties, insolvency proceedings, and director disqualification records tied to a company or promoter name. Distinct from negative_news, which screens general press/employee sentiment rather than hard legal/regulatory records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds meaningful behavioral context by specifying the exact sources screened and the categories of legal/regulatory data returned, which goes beyond the bare annotations. It does not describe output format or pagination, but that is not critical given the read-only research nature.

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, zero fluff. The purpose is front-loaded, and the sibling distinction is given in a single clause. Every word earns its place.

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

Completeness3/5

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

The tool has a nested required parameter (context.company) plus several optional fields, but the description does not explain when to set 'sector', 'listed', 'country', or 'companyDomain', nor what the output looks like. The sources are India-specific, yet the schema allows 'country' to be 'global', which could confuse an agent. This is a moderately complex tool that needs more operational detail to be fully usable.

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

Parameters1/5

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

Schema description coverage is 0%, meaning the description provides no guidance on any parameter. The schema itself only describes 'date' and 'companyDomain', leaving 'company', 'sector', 'listed', and 'country' undocumented. The description does not compensate by explaining how to fill the context object, making parameter usage entirely unclear. This is a significant gap for a required nested parameter.

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 states a specific verb ('screens'), names the exact sources (SEBI, NCLT, IndianKanoon, LiveLaw, Bar & Bench), and enumerates the record types found (litigation, regulatory penalties, insolvency, director disqualification). It also explicitly distinguishes itself from the sibling negative_news, so an agent can reliably tell them apart.

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

Usage Guidelines5/5

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

The description explicitly names the alternative tool (negative_news) and the condition that selects it: use this tool for hard legal/regulatory records, use negative_news for general press/employee sentiment. This gives clear when-to-use guidance and prevents mis-selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.