search_datasets

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

With no annotations provided, the description carries the behavioral burden and handles it well: it discloses that this searches a curated local index of verified datasets and provides a fallback path when nothing matches. It also clarifies that results are matching datasets, though it doesn't describe potential failure modes or whether the local index is refreshed.

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 organized into purpose, usage timing, fallback, and parameters, making it easy for an agent to parse. Every sentence adds information; nothing is redundant.

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 2-parameter tool with an existing output schema, the description covers the key points: what it returns, when to invoke it, what to do if nothing matches, and how to onboard new datasets. This is sufficient for correct tool selection and invocation.

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 no descriptions (0% coverage), but the description fully compensates with a clear Args section. query is explained with plain-language examples, and limit is described as the max result count with a default value for schema coverage 0%.

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 states a specific action ('Find datasets'), a concrete resource (India's Open Government Data platform), and the method (by keyword). It also distinguishes the tool from get_dataset_info and query_dataset by noting that this tool returns resource_id, which the other tools need.

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 clearly says to use this tool FIRST when the user asks about Indian public data and no resource ID is already known. It implies the alternative tools are used when a resource ID is already available, though it never names them explicitly, so a direct comparison is missing.

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