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

With no annotations, the description carries the full behavioral burden. It does add genuinely useful context: output is deduplicated and categorized, and the call costs $0.01 USDC via x402 on eip155:8453. It omits input size limits, rate limits, and failure behavior, so the disclosure is partial.

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?

Three short sentences, front-loaded with the capability and ending with the cost caveat, so nothing buries the key fact. The entity list is repeated verbatim in sentences one and two, a small redundancy.

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, no-output-schema tool the description covers capability, categories, output character (deduplicated, categorized, machine-ready) and pricing. Missing only input constraints such as maximum text length, which is a minor gap at this complexity.

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 description coverage is 100%, so the baseline is 3. The schema's own descriptions are terse ("Text", "Extract"), and the description only echoes the enum values as a category list; it adds no guidance on combining `what` values or text formatting expectations.

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 precise verb+resource (extract structured entities from unstructured text) and enumerates the five entity classes, which cleanly separates it from siblings that operate on single items (dev_email_validator, dev_url_parser) or on different inputs (dev_table_extract). An agent can tell at a glance what this tool returns.

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?

"Use this when an agent needs to pull emails, URLs, IPs, phones and domains from raw text" gives a trigger condition but merely restates the purpose and names no alternatives or exclusions (e.g. validating a known email vs. harvesting from a blob). Usage is implied rather than specified.

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