netintel_extract

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses the underlying model (Claude Haiku) and the exact output shape, but says nothing about how unparseable/ambiguous input is handled, latency, cost, or failure modes.

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?

A single front-loaded sentence that leads with the action and then the output fields; no redundant filler. It ends truncated ('for…'), which slightly undercuts the structure but the informative content is delivered up front.

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 usefully enumerates the return fields, so an agent knows what it will get back. The remaining gap is edge-case behavior on invalid input, which matters for a parser but is unaddressed.

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?

One required parameter with 0% schema description coverage, so the description must compensate. 'freeform address string' does add the key semantic (unstructured, any format accepted), but gives no format hints, limits, or examples to compensate for the empty schema.

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 pair (parse and normalize) and the resource is precisely bounded: a freeform address string. It enumerates the split outputs (street, city, state/region, postal code, country, normalized single-line), which clearly separates it from generic siblings like netintel_extract_contact, netintel_extract_invoice, and netintel_normalize.

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 trailing clause 'so agents can clean and standardize messy address data' implies the use case but gives no explicit when-to-use/when-not and names no alternative (e.g., when to prefer extract_contact for addresses embedded in documents). Usage is inferable but not stated.

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