email_verifier_catch_all_validator

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: the DNS-over-HTTPS resolution path, the specific checks run, and the degraded free-preview mode when CEA_API_KEY is absent, plus the backing Apify actor. However, it omits cost/rate behaviour for paid runs, what a 'catch-all score' actually returns, and whether results are cached or persisted.

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?

One front-loaded sentence names the operation and the check pipeline, followed by a short parenthetical on the free preview and provider. Dense but efficient, with only mild waste in the Apify actor slug, which is operational metadata rather than usage information.

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?

For a two-parameter tool with no output schema and no annotations, the description covers the method, the checks, and the auth/key precondition, which is most of what an agent needs to invoke it correctly. The remaining gap is return-value shape (what fields a verification result contains), which the absence of an output schema makes slightly more costly.

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, and the description adds little beyond signalling that the query is an email address (the default 'patrick@stripe.com' example reinforces this). The 'secondary' parameter remains semantically opaque for an email validator, since its schema text lists unrelated filters like permit type and language, and the description does nothing to resolve that mismatch.

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 ('Validate') and resource ('B2B emails') and enumerates the exact checks performed: MX/SPF/DMARC via Cloudflare DNS-over-HTTPS, disposable, role-account, and catch-all scoring. No sibling tool in the list performs email validation, so the resource alone cleanly separates it from the surrounding scrapers.

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 never says when to reach for this tool versus another, nor when not to use it. The only conditional statement is operational ('Free 1-row preview automatic when CEA_API_KEY is unset'), which tells the agent what happens on invocation, not when to choose the tool over alternatives.

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