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

Goes well beyond the annotations by disclosing the API-key requirement, that fetch_emails=true performs lookups and COSTS CREDITS, and that nothing is persisted to the account. These are cost and side-effect facts the readOnly/idempotent hints cannot express.

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?

Five short sentences with zero filler; the entity scope, the sibling routing, the filter-combination rule and the cost warning are each front-loaded in their own sentence.

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?

With no output schema, the description correctly summarizes the return ('matching companies with firmographics') and covers auth, cost and persistence. Everything an agent needs to invoke this correctly is present.

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?

Schema coverage is 100%, so the baseline is 3; the description still adds real semantics by explaining AND-combination of filters and the cost consequence of fetch_emails. It does not add syntax detail for query or the headcount bounds, so it is above but not far above baseline.

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?

States a specific verb+resource ('Find COMPANIES matching firmographic criteria') and immediately scopes the entity level ('company-level discovery'). It explicitly distinguishes itself from search_leads, so an agent can route without opening either schema.

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?

Gives explicit when-to-use triggers (targeting organisations by industry, location, headcount, tech stack) and names the alternative plus its selecting condition ('when they want named people, use search_leads'). Also explains that filters AND together, which shapes how an agent should build a query.

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