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Rafał Doniec: AI for companies

Contact details

get_contact
Read-only

How to reach Rafał Doniec: e-mail, booking a call, LinkedIn, and the company details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
emailYes
companyYes
websiteYes
linkedinYes
locationYes
book_a_callYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds content-level context (which contact channels are included), but says nothing about response shape or limits — acceptable since an output schema is present.

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?

A single compact sentence that leads with the subject (how to reach the person) and enumerates the returned channels. No filler, though the sentence fragment style reads slightly informally.

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

Completeness5/5

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

With no parameters, read-only annotations, and an output schema handling return details, the description covers everything an agent needs: what entity it concerns and what contact information comes back.

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?

The tool takes zero parameters, so there are no parameter semantics to document. Baseline 4 applies; the description cannot add or detract value here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the concrete resource (contact channels for a specific person: e-mail, call booking, LinkedIn, company details) and is easily distinguished from all siblings, which are quote/service/blog tools. It lacks an explicit verb (e.g. 'Returns'), so it stops short of a 5.

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?

Usage is only implied: an agent infers this is the tool for 'how do I reach this person' questions. No when-not or alternative routing is stated, though no sibling overlaps this domain, so the omission is low-risk.

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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