score_job_fit

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a numeric score, matched/missing skills, and a recommendation. This is sufficient for a read-only scoring tool, though it doesn't explicitly state that no mutations occur.

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?

Two sentences, no redundant information. The first sentence states the core purpose and output range; the second lists return fields. Every word earns its place.

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?

With no output schema, the description adequately covers what is returned. For a simple scoring tool, it provides sufficient context about inputs (parsed CV, job object) and outputs. Minor gap: no explanation of how to interpret the recommendation.

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 100% with clear descriptions. The description adds value by noting that candidate_profile comes from parse_cv, providing cross-tool context. This goes beyond what the schema alone offers.

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 ('Score'), identifies the resource ('candidate profile matches a job listing'), specifies the output range (0–100), and lists return items. This clearly distinguishes it from sibling tools like auto_apply or generate_cover_letter.

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 implies use after parse_cv and before applying, but it does not explicitly state when to use it over alternatives or provide a when-not scenario. Sibling tools are listed but not contrasted.

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