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

With no annotations to lean on, the description carries the full burden and does so well: it discloses the payment model ($0.5 USDC per call via _meta["x402/payment"]), the free 3-row sample escape hatch, per-source data freshness (data_as_of), guaranteed source URLs on every item, and a hard privacy constraint (facts only, no personal records). It also pins scope in time (Certificate Transparency, last 30 days; past CISA due dates), which bounds what the agent should expect.

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 core claim is front-loaded in the first sentence, followed by the evidence enumeration, then routing and pricing — a sensible order with no filler sentences. It is dense and runs long as a single block, so an agent must parse a wall of text, but every clause contributes a distinct fact.

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 complex, multi-source, paid data tool with no output schema and no annotations, the description covers what is returned, freshness, provenance, cost, and a free preview path. Remaining gaps are minor: no indication of response structure or shape beyond prose, and no error or payment-failure behavior.

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, but the generic schema only says 'One of: /brief' with an untyped string-valued params bag. The description adds real meaning by listing the actual parameters for that route (domain*, stack, lookalikes, limit) and marking domain as required with an asterisk, and by explaining sample=true as a free 3-row preview. That materially compensates for the schema's vague nested object.

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 names a concrete deliverable (a finished exposure brief) and its two input abstractions (company domain or tech stack), then enumerates exactly what that answer contains: breach history, actively exploited CVEs, ransomware use, EPSS-ranked recent CVEs, lookalike hostnames with new certificates, and a prioritised action list. That is far more specific than a restated name. It does not, however, differentiate itself from the very close sibling tool `security`, so an agent cannot be certain which of the two to pick from purpose alone.

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?

Usage is implied rather than stated: 'One call returns a ready answer about a company or a tech stack' and the route/params summary make clear what to call it with, and the sample=true free preview tells the agent how to try before paying. But there is no explicit when-to-use / when-not-to-use guidance and no contrast with the `security` sibling, so selection between the two remains inference.

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