apply_cover_letter

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

Discloses key behaviors: no network calls, deterministic output, and honesty rules (why_me from CV only, why_them as placeholder). With no annotations, this adds significant context beyond the schema, though side effects are not mentioned.

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 concise paragraphs: purpose, honesty details, and network call behavior. Front-loads the main action, though the honesty explanation could be more integrated.

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?

Covers the tool's core behavior and honesty constraints, which is adequate given the presence of an output schema. However, it does not describe the output structure, assuming the schema handles that.

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 3 applies. Description does not add new parameter meaning beyond the schema; it reiterates that cv_path and job_json are used but without extra semantic context.

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?

Description clearly states 'Build an honest cover-letter scaffold from a CV file and a job posting,' specifying verb, resource, and source. It distinguishes from sibling tools like apply_prefill and apply_act by focusing on scaffold creation with honesty constraints.

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?

Implies use for initial draft generation but does not explicitly state when to use vs alternatives like apply_prefill or apply_followup. No exclusions or when-not scenarios are provided.

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