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

With no annotations, the description carries the full burden and does so thoroughly. It discloses methodology (USD-only salary blending, remote-friendly classification reading remote-prefixed locations), output fields (n, smallSample, canonicalUrl, methodologyUrl), and interpretation cautions. This is exceptionally transparent.

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?

The description is long and dense, but every clause adds a specific metric or caveat. It is front-loaded with the core purpose and then elaborates. Slightly run-on in structure but each sentence earns its place given the complexity.

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 no-parameter, no-output-schema tool, the description covers all apparent behaviors: what statistics are included, how salary is computed, how to interpret sample sizes, and where to find underlying methodology. It is complete without needing an output schema.

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 schema has zero parameters with 100% coverage, so the description appropriately focuses on output semantics and data interpretation rather than parameter details. Baseline for 0 params is 4, and the description adds value by explaining the meaning of returned fields.

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 opens with 'Aggregate statistics across devrel.directory in one call' and lists specific metrics (listing counts, job count, salary stats), clearly distinguishing it from sibling tools like get_listing or list_jobs that return individual items. It is a specific verb+resource with detailed scope.

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 phrase 'in one call' implies this is a one-stop alternative to multiple list calls, and there is explicit guidance on how to use salary figures ('always cite n', 'qualify' small samples). However, it does not explicitly state when not to use this tool or name alternatives, so it falls short of a 5.

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