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

With no annotations, the description carries the burden and does well: it discloses the deterministic no-AI ANZSCO extraction, the ranking order (best first), the broadening-to-related-occupations fallback, and the privacy guarantee ('Nothing is stored'). It stops short of describing result size, pagination, or rate limits, which matters for an 8-parameter query 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?

Front-loaded with the core purpose, then the input contract, then the pipeline behaviour, then the LinkedIn URL prohibition. Dense but nearly every clause carries information; the ANZSCO/no-AI parenthetical is the only slightly expendable detail.

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 an 8-parameter tool with zero annotations and no output schema, the description covers inputs and ranking behavior but omits how results are shaped or bounded (count, pagination, what a returned job includes) and how the optional filters interact. Adequate to invoke, not fully complete.

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 description coverage is only 13% (only 'text' is documented), so the description must compensate and largely does not. It clarifies the text-vs-signals input modes but leaves 'limit', 'min_pay', 'location' and 'work_type' unexplained — the phrase 'likely pay band and work type' describes extracted signals, not these filter parameters, which risks confusion about what they do.

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 verb and resource ('Find live Australian jobs that match a resume or LinkedIn profile') and explains the matching mechanism (ANZSCO extraction plus overlap ranking). It is distinguishable from search_jobs by being a profile-driven match rather than a keyword search, though that contrast is implied rather than stated.

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?

Gives real input guidance: supply either 'text' or derived signals, and 'Never send LinkedIn URLs: paste text or a Save-to-PDF export.' However, it never says when to prefer this over search_jobs or find_adjacent_roles, nor what happens if both text and signals are supplied.

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