Get job-search statistics

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

Although annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, the description adds genuinely non-redundant behavior: counts are computed fresh from the local database on every call with no caching, and the tool takes no parameters. It also clarifies a non-obvious semantic ('response_rate' counts only real replies, not automatic acknowledgements) and defines 'needs_you' and 'last_reply_check'.

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 text is front-loaded with purpose and disambiguation before the behavior and return-value blocks, and each section is scannable. The long enumeration of return fields is justified because no output schema exists, though it is dense and could be grouped more tightly.

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?

There is no output schema, so the description carries the burden of describing returns, and it does so exhaustively across scalars, rate definitions, by_status/by_outcome/by_method groupings, daily series, and top_companies/top_titles/top_jobs. Combined with the read-only annotation profile, an agent has everything needed to call and interpret this tool.

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?

With zero parameters, the baseline is 4, and the description does confirm 'Takes no parameters', removing any ambiguity about whether filters or date ranges exist. There is no further parameter meaning to convey, so it cannot exceed the baseline meaningfully.

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 a specific verb and resource: 'Summarizes the user's job search in numbers', then enumerates the concrete metrics (applications, replies, interviews, offers, rates). It explicitly distinguishes itself from freeapply_list_jobs (individual jobs) and freeapply_status (whether FreeApply can run), so an agent can route correctly without opening any schema.

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?

It gives both a positive trigger ('Use it to report progress, for example when wrapping up a session') and a negative exclusion ('Not for finding a particular job'), plus named alternatives for the excluded case. Nothing about when to choose this tool is left to inference.

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