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

The credit-consumption warning is genuinely useful context not present in the annotations. However, 'Changes nothing' sits in tension with readOnlyHint=false (plausibly because credits are debited), and the description does not clarify what state, if any, is altered or whether results are persisted, leaving the agent to reconcile the two signals.

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 short, front-loaded sentences with no filler: scope first, safety second, cost third. Nothing is wasted, though the terse phrasing of 'Changes nothing' trades precision for brevity.

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 a one-parameter extraction tool with an output schema, the core is covered, but the description omits how this fits into a workflow (e.g., feeding score_resume or cover-letter generation) and how large the credit cost is. Adequate, not 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?

There is a single parameter at 100% schema description coverage, so the schema already defines 'job_description' fully. The description adds no syntax, length, or format guidance (e.g., the 50-char minimum / 50,000-char maximum), so baseline 3 applies.

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 gives a specific verb and resource ('Extracts a job description's keywords and requirements') plus a distinguishing output trait ('must-haves marked'), which separates it from siblings like score_resume or optimize_resume. It stops short of naming any alternative, so it lands just below the top band.

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?

'Uses AI credits' and 'Changes nothing' hint at the cost/read-only tradeoff, implying you should call it only when extraction is actually needed, but there is no explicit when-to-use statement or comparison to related tools such as score_resume or generate_cover_letter. Usage is implied rather than stated.

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