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

With no annotations, the description must carry the full behavioral burden. It discloses that the tool is FREE, names data sources (Greenhouse/Lever/Ashby), and lists return fields, but does not explicitly state read-only status, rate limits, pagination, or authentication requirements.

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?

A single compact paragraph that is front-loaded with cost and purpose, then usage, sources, and input format. Every sentence adds value with no filler.

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 one-parameter, no-output-schema read tool, it covers purpose, usage examples, data sources, returned fields, and input formatting. It is slightly incomplete on behavioral details like read-only guarantees and rate limits, but overall sufficient.

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 coverage is 0%, so the description must compensate. It does so by explaining the exact accepted formats for the company parameter: 'gh:<h>, lever:<h>, ashby:<h> or bare company handle.' That is essential meaning not present in the schema.

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?

States a specific resource ('current job openings / who is hiring at one company right now') and enumerates returned fields (teams, locations, remote, employment type). Clear purpose, but it never differentiates itself from sibling tools like hiring_batch_scan or hiring_changes.

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?

Provides explicit usage contexts via example queries ('what jobs is X hiring for', open roles, talent demand, headcount signals). No when-not conditions or direct comparison to 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.