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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds meaningful behavioral context by enumerating the exact return fields (name, summary, record_count, owner/org, url) and explaining how the output should be consumed, going beyond what annotations provide.

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?

Two tightly-packed sentences deliver the purpose, scope, return value, and downstream usage without any fluff. The information is front-loaded and every clause earns its place.

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?

Even without an output schema, the description fully explains what the tool returns and how to use that result with sibling tools. It provides sufficient context for an agent to know when to invoke this tool and what to do with the output, making it complete for its 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?

The input schema already covers all three parameters with clear descriptions (query, limit, org_id), achieving 100% coverage. The description adds minimal extra semantics—mainly context about the types of datasets searched—but does not illustrate parameter examples or edge cases beyond the schema examples.

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 identifies the tool as a search over City of Flagstaff GIS open geospatial datasets by keyword, with specific examples of dataset types. It distinguishes itself from sibling tools by explicitly noting that the returned Feature Service URL should be passed to query_layer/layer_info, which is unique and actionable.

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 implies the primary use case (discovering datasets by keyword) and provides a clear next-step guidance by telling the agent to pass the resulting URL to query_layer or layer_info. It does not explicitly state when not to use this tool, but the naming and sibling context make the intended scope clear.

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