generate_tailored_resume

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

Without annotations, the description explains the process: parsing, selecting/ranking experiences, generating, optionally compiling to PDF. It mentions return types but does not cover side effects, permissions, or saving behavior. Still, it provides good transparency.

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 well-structured with a summary, process paragraph, and Args list. It is front-loaded but the Args section is lengthy due to the number of parameters; however, it remains clear and efficient.

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?

The description covers the core function and parameters but lacks prerequisites (e.g., need existing resume data from 'get_resume_data' or 'import_resume') and does not explain interactions between parameters like target_tags and include/exclude. Edge cases and errors are omitted.

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 0%, but the description provides thorough explanations for all 12 parameters in an Args section, offering context beyond names (e.g., 'Raw job description text', 'Force include these experience indices').

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 states the tool's purpose: parsing a job description, selecting relevant experiences/projects, and generating a tailored resume. It distinguishes from siblings like 'generate_resume' (generic) and 'score_resume_quality' (scoring).

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 implies use when tailoring a resume to a job description but does not explicitly state when to use this tool over alternatives like 'generate_resume'. No exclusions or when-not-to-use guidance.

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