parcel-owner-lookup

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

With no annotations, the description carries the transparency burden. It discloses read-only behavior ('Reads live from the official government source'), cost per lookup, the fallback to Census geocoding, and the guarantee that each input yields one output row with a 'match_confidence' field. It lacks explicit rate limits or failure modes, but covers key behaviors.

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 description is dense but not overly verbose. It leads with a clear summary, then details scope, use cases, cost, and data source. The structure is logical, though the repeated phrasing about addresses and output rows could be tightened slightly.

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?

Given the absence of an output schema, the description gives a high-level list of fields but not the exact response structure. It also doesn't specify error handling, rate limits, or authentication requirements. For a read-only lookup tool, this is a moderate gap that could leave users uncertain about response format in edge cases.

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?

The input schema already includes detailed descriptions for both parameters. The tool description reinforces the address parameter's behavior (one row per input, fallback) and explains the maxResults cap. This adds meaningful context beyond the schema, especially regarding output consistency.

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 clearly states the tool's function: converting street addresses into parcel IDs, owner names, mailing addresses, assessed values, and coordinates. It specifies geographic coverage (Chicago/Cook County, Philadelphia, NYC) and distinguishes from sibling tools by focusing on parcel ownership data.

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 provides explicit use cases (address-grounding for AI agents, proptech, skip tracing) and mentions the scope and fallback behavior. While it doesn't directly compare to sibling tools, the domain-specific nature and geographic limits make it clear when this tool is appropriate.

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