get_spam_stats

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

With no annotations, the description discloses a key behavioral trait: 'Cached 60 seconds,' indicating potential staleness. It also enumerates exactly which statistics are returned (total checks, SPAM, SUSPICIOUS), providing useful context beyond what an empty schema would imply.

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 sentences with immediate verb-first structure. The source, key metrics, and caching behavior are all stated without any filler or redundancy.

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 zero-parameter tool with no output schema, the description covers the data source, exact statistics, time scope ('today'), and cache lifetime. This is fully sufficient for an agent to know what to expect.

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 has zero parameters and 100% schema coverage (trivial). Baseline 4 applies because the description need not explain parameters that don't exist.

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?

Description opens with 'Get daily spam classification statistics' – a specific verb and resource. It distinguishes itself from siblings (check_spam_text, get_spam_examples) by focusing on aggregate metrics rather than text analysis or example retrieval.

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 context implies use when one needs general spam stats, but it does not explicitly state when to use it over alternatives or when not to use it. Sibling tools are listed separately but not referenced in the description.

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