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

Annotations already cover readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is settled. The description adds genuinely non-structured behavior: the dataset holds only recent SHAB publications plus Zefix history for the companies those name, so absence from search results does not mean nonexistence — crucial interpretive context. It stops just short of stating rate limits or refresh cadence beyond the last-success timestamp.

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?

Front-loaded with the scope statement and the 'call it before concluding...' directive. The middle enumerates return fields somewhat densely, and the final two sentences about coverage limits and load_company are slightly run-on, but every clause carries actionable meaning rather than 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?

An output schema exists, so return formatting need not be explained, yet the description still summarizes the coverage fields an agent needs to interpret results. For a zero-parameter read tool, nothing an agent needs to call it correctly is missing, including the critical caveat about search coverage.

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 tool takes zero parameters, so there is nothing to document and the baseline is 4. The description correctly spends its space on return semantics instead of inventing parameter guidance.

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?

It states precisely what the tool returns (date range held, last successful fetch, company/publication counts, analysed-company counts and start point, per-canton equivalents) and scopes the dataset contents. It also distinguishes itself from sibling search tools by clarifying that searches only cover the analysed part, and names load_company as the path for absent companies.

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?

Explicit when-to-use: 'call it before concluding something does not exist.' Explicit when-not and workaround: an older unchanged company is absent from a search but is not gone, so use load_company by UID instead. The relationship to every AI filter/search sibling is stated directly.

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