energy_search_bfe_datasets

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

The description adds valuable behavioral context beyond annotations: it returns metadata (title, description, formats, link) and not raw data, full-text search is metadata-only, and pagination uses offset. This complements the readOnlyHint and idempotentHint annotations without contradicting them.

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 short main sentence, use_case, important_notes, and example. It is slightly longer than the minimal two-sentence ideal but every section adds value and the information is tightly packed without redundancy.

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?

The description covers purpose, usage context, limitations, and gives an example. Since an output schema exists, return values need not be described. The combination of annotations and description is sufficient for an agent to understand the tool's behavior and constraints.

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 input schema already contains descriptions for limit, query, and offset. The description adds an example (query='wasserkraft', limit=10, offset=0) and notes that offset is used for pagination, but does not substantially extend parameter meaning beyond the schema. Given the schema description coverage is reported as 0%, the example and pagination note provide partial compensation.

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 searches the opendata.swiss catalog for datasets from the BFE, a specific verb+resource. It does not explicitly differentiate from siblings like energy_find_power_plants, but the focus on dataset search rather than specific asset types is evident from the description and name.

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 use_case clarifies when to use it (finding raw data and statistics beyond geo-layers), and important_notes state that it returns metadata only and that full-text search covers metadata, not raw data. This provides clear context for usage, though it does not explicitly name alternatives or when-not-to-use scenarios.

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