Scan Gmail for tracker updates

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

With no annotations, the description carries full burden and it excels: it explicitly says 'Read-only', states it 'never updates the tracker itself', and explains that it only produces a `suggestedCall`. This fully discloses the non-mutating, advisory nature of the tool.

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 two sentences long, front-loaded with the main action, and every clause adds value. It efficiently communicates scope, method, side effects, and follow-up action without 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 has no output schema and the description gives a hint about return values via `suggestedCall`, which implies a suggestion object. It covers the core workflow and side effects well, though a detailed explanation of the return structure could improve completeness.

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?

All three parameters already have descriptions in the schema (100% coverage), so the description adds little new param-level meaning. It only re-emphasizes the 'one company' option, while days_back and max_per_company are not mentioned beyond schema coverage.

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 clearly states the tool's function: cross-referencing open applications against Gmail and flagging keyword-based signals. It uses specific verbs like 'cross-reference' and 'searches', and distinguishes itself from siblings by emphasizing it only suggests status changes rather than updating the tracker.

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 when to use the tool: for each open job or optionally one company, scanning recent email for signals. It also gives post-usage guidance (review emails and call update_job_status if the suggestion looks right), though it doesn't explicitly compare to sibling tools like search_gmail_for_job.

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