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run_eustartups_directory

Retrieve detailed profile data for a single EU startup by slug or URL, including funding, location, tags, and social links.

Instructions

Get one startup from the EU-Startups database by slug or URL: tagline, description, country, city, tags, founding year, total funding, website, status, social links and related articles. Flat 5 points per successful run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesStartup slug or EU-Startups URL. e.g. vista-ai

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.1

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the returned field set and the cost model ('Flat 5 points per successful run'), which is genuinely useful context, but it says nothing about failure behavior when a slug is invalid, auth requirements, or rate limits.

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?

One sentence, front-loaded with the action and source, with the field list and cost note appended. The field enumeration is long but earns its place since no output schema exists to describe the return shape.

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?

No output schema or annotations exist, so the description must carry the return-value and behavior load; it lists the returned fields and discloses cost, covering most of the gap. Only error/edge-case behavior is unaddressed.

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?

Schema coverage is 100% and the schema already documents the single 'company' parameter with an example. The description adds marginal value by confirming slug OR URL are both acceptable, reinforcing the schema's single example. With one well-documented parameter, semantics are effectively complete.

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?

States a specific verb and resource ('Get one startup from the EU-Startups database') plus the lookup key (slug or URL), which distinguishes it functionally from run_eustartups_directory_search. It stops short of naming the sibling search tool, so differentiation is inferred rather than explicit.

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 'by slug or URL' phrasing implies this is for direct single-entity lookups and that search should be used otherwise, but no when-to-use or when-not-to-use guidance is stated. The agent must infer when this beats run_eustartups_directory_search.

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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