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shauryajain21

Linkup Company Research MCP

company_risks

Assess risk factors for a company, covering competitive, regulatory, legal, technology, and market risks to identify vulnerabilities.

Instructions

Assess risk factors for a company.

Researches competitive risks, regulatory risks, legal exposure, key person dependency, customer concentration, technology risks, and market risks.

Args: company_name: The name of the company to research output_format: "answer" for natural language with sources, "structured" for JSON max_results: Maximum sources to consider (1-50)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_resultsNo
company_nameYes
output_formatNoanswer

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries full burden. It lists risk categories but lacks disclosure on side effects, authentication needs, rate limits, or data freshness, leaving behavioral traits unclear.

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?

The description is concise, front-loaded with purpose, and structured with a clear args list. Every sentence adds value with no redundancy.

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?

The description covers purpose, args, and output format options (answer vs structured). Given an output schema exists, it does not need to detail return values, but mentioning that sources are included would enhance completeness.

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

Parameters5/5

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

Schema coverage is 0%, and the description fully compensates by explaining each parameter: company_name (name), output_format (two options), and max_results (range 1-50, default 15), adding meaning beyond the schema.

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 starts with a clear verb and resource ('Assess risk factors for a company') and lists specific risk categories (competitive, regulatory, etc.), distinguishing it from siblings like company_financials or company_culture.

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

Usage Guidelines3/5

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

The description implies use when needing risk assessment but does not explicitly state when to avoid using it or mention alternative tools among the many siblings.

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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