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

Annotations provide readOnlyHint=true and openWorldHint=true, and the description adds behavioral context: it wraps an external aggregator (nexgendata/company-data-aggregator) and performs a Crunchbase free-tier funding scrape when include_funding=True. This goes beyond the annotations without contradicting them. It does not mention rate limits or authentication, but that is acceptable given the read-only hint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence, then lists sources, positions the tool among siblings, and provides parameter explanations in a clear 'Args' block. It is efficient and well-structured, though the parameter explanations could be integrated more concisely without losing clarity.

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

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

Given the tool's complexity (multi-source aggregation, external wrapper, funding scrape) and the absence of an output schema, the description should more fully explain the return structure. It mentions the fields covered but does not specify the exact JSON structure, nesting, or which fields are guaranteed. This leaves an agent uncertain about the output format.

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

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

The input schema has 0% description coverage, so the description must compensate. It explains name_or_domain as 'Company name or domain' and include_funding as 'Include Crunchbase + news-based funding lookup'. This adds meaning beyond the schema types and default values. A higher score would require more detail on allowed formats for name_or_domain.

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

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

The description clearly states the tool builds a full company profile by aggregating multiple public sources (homepage, /about, /careers, JSON-LD, Crunchbase) and lists the specific fields covered (industry, HQ, founded date, employee band, key people, social handles, funding history). It also distinguishes itself from siblings by calling itself 'the richest of the company-research tools'.

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

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

The description provides guidance on when to use: 'use this when you want one record covering...'. It implies alternatives through sibling tool names (e.g., detect_hiring_signal, detect_tech_stack), and mentions the include_funding parameter. However, it does not explicitly state when not to use it or compare directly to siblings like enrich_company.

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