check_data_freshness

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond that: it specifies output contents (last-updated timestamps, statuses) and the exact staleness thresholds per source. No contradictions with 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 concise sentences pack a clear purpose, return values, staleness thresholds, and usage guidance without redundancy. Every sentence earns its place, and the structure is front-loaded with the core action.

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 simple, read-only tool with one optional parameter, the description fully covers when to use, what it returns, and how to interpret results via thresholds. No output schema exists, but the description explicitly mentions the output format (timestamps, statuses), making it complete.

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 fully describes the optional 'source' parameter with enum values and the behavior when omitted. Schema description coverage is 100%, so the description adds no additional parameter meaning. The baseline of 3 is appropriate.

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 action ('Check the freshness (age) of each data source') and identifies the key resources (statutes, case_law, eu_references) and return values (timestamps, fresh/stale/unknown status). It clearly distinguishes from siblings like check_currency, which focuses on legal validity, not data age.

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 gives explicit usage context: 'Use this before relying on legal data for time-sensitive analysis.' It also specifies staleness thresholds, providing concrete decision criteria. However, it does not mention exclusions or alternative tools, so it falls short of a full 5.

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