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Builders in Fintech

Search companies and investors

search_organizations
Read-onlyIdempotent

Search fintech companies and investors by name, kind or country. Returns public profiles with canonical URLs. Arguments: q (or query): text to search for, matched against the name. With no q the tool returns a plain alphabetical list (first 25 by default). Unknown arguments are rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoq (or query): text to search for. Omit for a plain alphabetical list.
kindNoRestrict to companies or investors.
limitNoMax rows (≤200).
queryNoAlias of q; q wins if both are sent.
countryNoCountry as a slug ('italy') or a two-letter ISO code ('IT'); case-insensitive.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and non-openWorld semantics, and the description adds real behavioral detail on top: default page size of 25 and that unknown arguments are rejected. It also notes returns are public profiles with canonical URLs, though it says nothing about pagination beyond the default.

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?

Front-loads the purpose in the first sentence, then handles scope and arguments compactly with no filler. The 'Arguments:' enumeration is slightly list-like but every clause carries information.

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?

With no output schema, the description partially compensates by noting the return shape (public profiles with canonical URLs) and error behavior for unknown arguments. For a zero-required-param search tool this is close to complete, with only pagination beyond the default left implicit.

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 100%, so the schema already documents q, kind, limit, query alias, and country. The description only adds marginal value, notably that q is matched against the name, plus a restatement of the alias and no-q behavior; the baseline of 3 is correct here.

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?

States a specific verb (search) and resource (fintech companies and investors) plus the filterable facets (name, kind, country). This clearly distinguishes it from siblings like search_people, search_products, and search_content, which target different resource types.

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?

Explains the no-q case (plain alphabetical list, first 25 by default), which is useful context, but never states when to prefer this tool over the near-identically named siblings such as search_content or get_organization, nor any exclusions.

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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