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

Annotations already indicate read-only, open-world, idempotent, non-destructive behavior. The description adds valuable transparency by listing the exact return fields (name, summary, record_count, owner/org, URL) and clarifying that the URL is a pointer for further queries, which is not captured in the schema or 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 two sentences with zero wasted words. It front-loads the core purpose, then immediately provides actionable return-value details and a downstream pointer. Every sentence 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?

The description is complete for a search tool of this complexity: it explains what is searched, what is returned, and how to use the result. It covers the search scope, output structure, and integration with sibling tools, leaving no significant gaps beyond what the schema already defines.

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 schema provides 100% coverage with clear descriptions for all three parameters (query, limit, org_id). The description adds domain context (examples of dataset types) but does not add parameter-specific semantics beyond what the schema already offers. Per rubric, the baseline is 3 for high schema coverage.

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 purpose: searching City of Phoenix GIS open geospatial datasets by keyword. It specifies the resource (GIS datasets), the action (search), and highlights the key output (Feature Service URL), distinguishing it from sibling tools like query_layer and layer_info.

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 clear usage context by indicating that the returned URL should be passed to query_layer or layer_info, establishing a workflow. However, it does not explicitly discuss when to avoid this tool or compare it to alternatives like search_within, so it falls short of full explicit guidance.

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