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

Beyond the read-only annotation, the description reveals meaningful behavior: recommendations are matched to profile, exclude jobs already applied to, and fall back to location-based results if the profile is incomplete. This is exactly the kind of behavioral context that helps an agent predict tool behavior.

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?

Three sentences, each earning its place: purpose, matching/filtering behavior, and fallback behavior. The most important information is front-loaded and the description is free of 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?

Given the output schema is present and the annotations already signal a safe read-only operation, the description is complete. It covers the core use case, filtering behavior, fallback logic, and leaves pagination semantics to the 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 input schema already fully documents both parameters (limit and pageToken) with descriptions. The description adds no parameter-specific meaning, but with 100% schema coverage, the baseline of 3 is appropriate.

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 uses a specific verb and resource: 'Get personalized job recommendations'. It clearly states what the tool returns and differentiates it from general job search and application-related tools by mentioning profile matching and exclusion of already-applied jobs.

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 gives clear context: this is for personalized, profile-matched recommendations, not general search or application history. It does not explicitly name alternatives or state when not to use it, but the use case is well defined.

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