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

Annotations already declare readOnlyHint, idempotentHint and non-destructive behavior, so the safety profile is covered. The description adds genuinely new context that goes beyond the annotations: the credit economics of downstream tools. It doesn't say whether the call itself consumes credits or whether the balance resets, which are minor gaps.

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 short sentences. The return content is front-loaded, and the second sentence about costs is not padding: it tells the agent how to use the number.

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?

No output schema is declared, so the description has to explain the return, and it does: credit count plus Litjob Pro status. The credit pricing for sibling tools rounds it out. It only omits edge cases such as what happens when credits hit zero or whether Pro implies unlimited usage.

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 tool takes zero parameters and the description has no parameter semantics to explain, which is the baseline for a no-argument tool. Nothing is misdescribed.

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 states a specific resource and the two values returned: the AI credit count and whether the user is on Litjob Pro. It is clearly distinguishable from siblings such as tailor_application or draft_application_answers, though it doesn't explicitly name those alternatives.

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?

Usage is only implied: the credit costs listed (2 for tailoring a CV and cover letter, 1 for drafting answers) suggest checking the balance before invoking those paid siblings, but the description never says 'call this before X' or states any when-not condition.

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