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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses the row limit (at most 100 rows per call), the case-insensitive substring matching for ATS vendor and substring matching for industry, and points to the full dataset URL. These are meaningful behavioral details that help the agent predict output size and filter semantics.

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 three sentences, front-loaded with the main purpose, and each sentence adds essential information: the dataset, filter behavior, and output limit/source for full data. No 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?

The tool is a simple list with optional filters, read-only annotations, and no output schema. The description covers the source dataset, filter behavior, output limit, and full-data alternative. It does not describe the fields of each returned row, but given the known dataset and the link, this is a minor gap.

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 already covers all three parameters with descriptions. The description adds practical semantics for 'ats' by specifying case-insensitive substring matching with examples, and for 'industry' as substring matching. This goes beyond the schema's basic descriptions. The 'verified_only' parameter is not elaborated in the description, but the schema definition is sufficient.

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 'List employers from the State of ATS 2026 dataset', clearly stating the action (list), resource (employers from a specific dataset), and scope (optionally filtered by ATS and industry). This distinguishes it from siblings like ats_stats or which_ats, which focus on statistics or identification rather than listing companies.

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 provides clear context for use: it can list all companies or filter by ATS and industry. It also states the 100-row limit and advises narrowing filters or fetching the full dataset from the provided URL. However, it does not explicitly name sibling tools as alternatives or exclusions, so it lacks explicit when-not-to-use guidance.

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