zia_url_lookup

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

The description discloses critical behavioral traits beyond the readOnlyHint annotation: it returns only predefined categories (not custom), unknown URLs come back as 'MISCELLANEOUS_OR_UNKNOWN', and it supports up to 100 URLs per request. It also warns about the query parameter's field naming pitfalls. These details add significant context that annotations alone do not provide, and nothing contradicts the 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 long but every sentence earns its place. It opens with the core question and a direct statement of use, then gives an example, then explains limitations and alternatives, and finally the capacity and fallback behavior. The structure is front-loaded and logical, with no filler.

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 2 parameters and no output schema, the description is remarkably complete. It covers the tool's purpose, usage context, output format example, limitations, and alternative tool path. It also addresses the query parameter's potential pitfalls. There is essentially no gap left for the agent.

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?

Although the schema only formally describes the 'query' parameter, the description thoroughly explains both parameters: 'urls' as the list to look up, and 'query' as an optional JMESPath expression with examples, warning about snake_case field names, and advising to call without query first if uncertain. This goes well beyond the schema and provides essential usage detail.

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: to return Zscaler's predefined category classification for given URLs. It uses specific verbs ('look up', 'returns') and explicitly distinguishes itself from the sibling tool zia_list_url_categories by clarifying it handles predefined categories only, not custom ones. The example output further cements the purpose.

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 gives explicit when-to-use and when-not-to-use guidance. It says to use this tool for predefined category questions, and for custom category questions to call zia_list_url_categories(custom_only=True, contains_url=...). It also instructs to stop after this tool unless the user says 'custom', and warns against answering custom category questions from this tool's output. This is exemplary usage guidance.

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