Search Documents

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

Annotations declare readOnlyHint=true and idempotentHint=true, so safety is clear. The description adds behavioral context like requiring an existing dataset, plan-based mode restrictions, and a clear upgrade message for insufficient plans. This enriches transparency beyond 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 well-structured with a front-loaded purpose sentence and an organized Args block. It is informative without unnecessary verbosity, though slight tightening could improve conciseness.

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 complexity (6 params, plan restrictions, and preconditions) and the presence of an output schema, the description covers all essential aspects: purpose, usage guidance, parameter details, plan dependencies, and return value expectations.

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?

Despite 0% schema description coverage, the Description's Args block thoroughly explains each parameter, including defaults, max values, options, and plan dependencies for mode. This fully compensates for the schema's lack of descriptions.

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 'Search across all indexed FlexOrch datasets by keyword or meaning.' It uses a specific verb (Search) and resource (datasets), and distinguishes from sibling tools like dataset.build or document.process.

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 advises when to use ('to find specific documents or records without processing a new file') and mentions prerequisites ('Requires at least one dataset to exist'). It also details plan restrictions for modes, though lacks explicit 'when not to use' beyond plan limitations.

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