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

Annotations already establish read-only, idempotent, open-world, non-destructive behavior, so the safety profile is covered. The description adds genuinely useful behavioral context absent from structured fields: the shape of the return payload (dataset_ids, titles, themes, record counts), which is important since no output schema exists.

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?

Two compact sentences, front-loaded with the action and scope before the downstream routing hint. Every clause carries information; 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 read-only search with no output schema, the description covers purpose, corpus, and returned fields adequately, and annotations carry the safety profile. It omits pagination behavior beyond the schema defaults, which is a minor gap rather than a blocker.

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 100%, so all three parameters (query, limit, offset) are already documented with ranges and defaults. The description clarifies that search targets titles/descriptions via 'keyword', adding marginal value but not exceeding the schema baseline.

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 (Search) and resource (datasets) within a named corpus (ODRE Energy Open Data) and scopes the covered topics. It also locates itself in the workflow by naming the consumers of its output (query, dataset_info), which separates it from dataset_info and the generic query tool.

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?

Explicitly tells the agent what to do with results ('pass to query/dataset_info'), which is actionable routing guidance. It does not state when NOT to use it (e.g., vs. search_within or dataset_info for direct lookup), so it falls short of full alternative coverage.

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