suggest_improvements

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

With no annotations provided, the description carries the full burden of disclosing behavior. It accurately states the tool generates recommendations without side effects, but it does not elaborate on the nature of the output, whether it reads or writes data, or any limitations. This is adequate for a simple suggestion tool but lacks depth, missing an opportunity to clarify that it is non-destructive.

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 description is a single, well-structured sentence that front-loads the main action and clearly states the domain. Every word adds value, and it is appropriately sized for the tool's simplicity, achieving maximum conciseness.

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?

Given the tool's low complexity (2 parameters, 1 optional) and the presence of an output schema (which likely documents return values), the description is mostly sufficient but leaves out any mention of the target_job_title parameter. It does not explain when to use this tool, but the core purpose is clear. It barely meets the minimum viable standard for completeness.

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 0%, so the description must compensate. It adds meaningful detail about resume_text (referencing bullet points, action verbs, formatting), but completely ignores the optional target_job_title parameter. This leaves a significant gap in understanding how the second parameter behaves, earning a below-average score.

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 clearly uses a specific verb ('Generates') and resource ('actionable recommendations to optimize bullet points, action verbs, and formatting'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like analyze_resume or calculate_ats_score, though the focus on improvement recommendations is distinct enough to infer a difference.

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 offers no guidance on when to use this tool versus its siblings. There is no mention of alternatives, prerequisites, or typical scenarios. The only hint is the verb 'Generates', which implies a recommendation role, but no explicit usage context is provided.

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