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

Beyond the annotations it discloses three things an agent cannot infer: a connected GetMattered account is required, the call consumes the user's AI credits, and the job gets saved to the account if not already saved. The remaining gap is retry behavior—with idempotentHint=false and credit consumption, it doesn't say whether re-calling after a failure duplicates work or burns credits again.

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 output list is front-loaded in the first sentence and the selection rule and exclusion follow in order of decision importance. It is a single dense paragraph that runs long, but nearly every clause carries actionable information rather than 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?

With annotations, full schema coverage and an output schema covering returns, the description carries everything needed to select and invoke the tool: prerequisites, cost, side effects, input modes. Only the failure/retry and credit-cost-magnitude behavior is unaddressed.

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%, so baseline is 3; the description earns a bump by explaining the consequence of choosing application_id (it preps an existing application and creates no new saved job) rather than merely echoing the schema's 'Replaces job_title and company_name'. It leaves job_description's effect unsurveyed, but the schema already covers it as optional/recommended.

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 ('Produce interview preparation') plus an enumerated deliverable list (company insights, role questions, STAR scenarios, talking points, interviewer questions, salary prep) and names the exact inputs. It is clearly distinguished from getmattered_generate_cover_letter by an explicit exclusion.

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?

It states both invocation paths with their tradeoffs: application_id for jobs already applied to ('no new saved job') versus job_title + company_name 'for any other job'. It also names the sibling tool to use instead for cover letters, so the agent has a when-not rule.

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