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

Annotations already provide read-only and open-world hints. The description adds value by disclosing provenance details (disclosed %, high-confidence %, ECB reconciliation Δ) and the default to the current year, enriching the behavioral profile without contradicting annotations.

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 dense sentences: the first lists all key outputs and quality metrics, the second gives the performance benefit and default. No wasted words, front-loaded purpose.

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?

With a single optional parameter and no output schema, the description succinctly enumerates all output categories (totals, concentration, breakdowns, provenance) and the default period, making it self-sufficient for invoking the tool.

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 single 'period' parameter is fully described in the schema with format examples and default. The description repeats the default and adds context, but provides no new semantic information beyond what the schema already covers.

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 it aggregates the European funding picture for a period in one call, enumerating totals, concentration, breakdowns, and provenance. It distinguishes itself from sibling search tools by offering a market-level aggregate rather than individual records.

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 description explicitly contrasts with paging through every round to sum client-side, indicating the intended use case for aggregate market stats. It implies when to use (high-level funding analysis) but doesn't name sibling tools as alternatives; still, the context is clear.

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