open_data_search

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

No annotations are provided, so the description carries the burden; it does establish a read-only, non-mutating search and adds the limit ceiling of 1-50, which is useful context. It says nothing about result ordering, pagination, or whether the query matches titles vs. metadata fields, leaving behavioral gaps for a no-annotation tool.

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 purpose sentence is front-loaded and the Args block adds concrete value through examples. Slightly listy but nothing is padded or 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?

An output schema exists, so return values need not be described, and all three parameters are documented despite zero schema coverage. What is missing is guidance on the natural follow-up (open_data_dataset / open_data_preview), which would complete the workflow picture.

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?

Schema description coverage is 0%, so the description does the work: it defines query as a topic keyword with concrete examples, organization as an optional publisher filter with examples ('INE'), and limit as a bounded 1-50 range with a default. Only the semantics of how query matching works is left unstated.

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?

States a specific verb and resource plus the exact data source ('Search the datasets of Portugal's national open-data portal (dados.gov.pt)'), which lets an agent separate it from generic search tools. It does not, however, distinguish it from its own siblings like open_data_dataset or open_data_preview, which an agent could easily confuse it with.

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 example queries ('acidentes rodoviários', 'escolas') imply the intended use for topic discovery, and the organization param hints at narrowing by publisher. There is no explicit when-to-use or when-to-prefer-a-sibling statement, so an agent must infer that this is the discovery step before open_data_dataset.

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