validate_data_freshness

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

No annotations are provided, so the description carries the full burden. It discloses it checks timestamps, staleness, and update frequency, and states the outcome purpose (prevent acting on outdated info), but doesn't describe return format, what constitutes 'valid', or whether it fails hard or soft. Moderate disclosure for a read-style check tool.

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 with no wasted words. The second sentence effectively frames the purpose. It's appropriately sized for the tool's complexity, though could arguably add a note about return behavior without much cost.

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 5 parameters, 100% schema coverage, no annotations, and no output schema, the description handles the purpose but leaves ambiguous what the return value looks like and how staleness/update-frequency signals interact with max_age_hours. For a validation tool, the outcome semantics are important for an agent to interpret the result.

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 each of the 5 parameters is already documented in the schema. The description adds a general framing and the 'Prevents acting on outdated information' rationale but does not add syntax, defaults rationale, or interaction details beyond the schema. Baseline 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 verb+resource ('Check if data...is recent and valid') and mentions the key signals (timestamps, staleness indicators, update frequencies). It's clear and distinct from siblings like validate_json_schema or cross_reference_check, which handle different validation concerns.

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 implies the tool is used before acting on data ('Prevents acting on outdated information') which gives context, but it doesn't explicitly compare against alternatives or state when NOT to use it. No exclusions or alternative tool references are present.

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