swiss_grid_energy_data

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It doesn't mention what data freshness/recentness is, whether a setup/api key is required (sibling swiss_set_api_key and swiss_check_setup exist, suggesting auth may be needed), data granularity, or response structure. For a data-fetching tool with zero annotation coverage, this is a notable gap.

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 a single efficient sentence that packs in the data source, the specific data types, and scope. No wasted words. Could be front-loaded with the differentiation from siblings, but the length is appropriate.

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 single-param tool with 100% schema coverage and no output schema, the description provides a reasonable understanding of what data is retrievable. However, given the title is null and no annotations exist, it could strengthen by noting data time-window, refresh cadence, or required setup steps (given sibling setup tools exist). It's adequate but leaves room for improvement.

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 the schema already documents the 'query' parameter. The description adds context about what data types the query can fetch (consumption, production mix, cross-border flows), which is a mild enhancement over the bare 'Search query' schema description. Baseline 3 is appropriate since the schema handles documentation and the description adds only marginal value.

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 verb ('Get') and resource ('Swiss energy grid data from Swissgrid') with concrete data types (actual electricity consumption, production mix, cross-border flows). It distinguishes itself well from siblings like swiss_snb_financial_data or swiss_energy_search_datasets, though it doesn't explicitly draw that contrast.

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?

No guidance on when to use this tool vs alternatives. There's a sibling swiss_energy_search_datasets (likely for searching energy datasets) and this tool could be confused with it, but the description doesn't clarify the distinction or when to prefer one over the other. Usage context is entirely implied by the name/description.

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