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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context beyond these: results are anonymized (no addresses), sourced from city open-data portals, and only Seattle is supported while other jurisdictions return jurisdictionSupported=false. This clarifies edge cases and data handling, which is especially useful given the openWorldHint. No contradiction with annotations.

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 three sentences with zero redundant phrases. It front-loads the core function in the first sentence, then details the output and source, and ends with practical use cases. Every sentence earns its place, making it efficient and easy to scan.

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 tool with a single parameter, comprehensive annotations, and an output schema (as indicated by context signals), the description covers all necessary aspects: what it does, what it returns, data provenance, jurisdiction limitations, and use cases. No critical information is missing for an agent to invoke it correctly.

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 schema already documents the 'address' parameter clearly (full street address in King, Pierce, or Snohomish County, WA). The description enhances this by specifying that the tool targets 'Seattle-area parcels' and noting that other jurisdictions return jurisdictionSupported=false, which tells the agent that addresses outside Seattle may not produce useful results. This nuance goes beyond the schema's generic county list, adding meaningful semantic guidance.

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 verb 'aggregate' and resource 'permit activity' with precise scope (within ~1500 ft, last 24 months, Seattle-area parcel). It also lists the return payload (count, category breakdown, anonymized example permits) and data source (Socrata). This differentiates it from siblings like get_neighborhood_project_activity, which focuses on projects rather than permits.

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: 'gauge neighborhood activity before quoting an unusual project' and 'set homeowner expectations on what neighbors have built.' However, it does not explicitly name alternatives or state when not to use this tool, such as differentiating from get_neighborhood_project_activity. The context is clear but lacks explicit exclusions, so it falls short of a 5.

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