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

The description discloses the two-step stateful behavior, that STEP 2 renders a PDF and saves to the dashboard, requires sign-in, and that the model must write the letter (never fabricate). Annotations already indicate destructiveHint=true, and the description adds context about what gets saved and the sign-in requirement. It doesn't fully detail failure modes or what happens without sign-in, but it adds substantial behavioral context beyond annotations.

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 dense and front-loaded with the two-step process, but it is somewhat long and includes some redundancy with the schema (e.g., repeating parameter details). It earns its place by explaining the workflow, but could be tightened by trimming repeated parameter semantics.

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?

For a complex two-step tool with 14 parameters and no output schema, the description covers the workflow, required inputs per step, job_id resolution rules, and the save destination. It doesn't describe the return value of STEP 1 in detail (beyond 'returns the job's JD and the candidate's background, plus writing instructions'), but that is adequately implied. The sign-in requirement and write-back behavior are disclosed.

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 79%, so the schema already documents most parameters. The description adds meaning by explaining the relationship between job_id and job_description (alternatives), the precedence of json_resume over resume_text, and the role of user_email in writing back to profile.applications[jobId].coverLetter. It also clarifies that cover_letter_text is STEP 2 only. This goes beyond the schema's individual descriptions.

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 writes a cover letter for a specific job and explicitly breaks down the two-step process (prepare then save). It distinguishes itself from siblings by naming tailor_resume_tool and job_detail_tool for job_id resolution rules, and the verb 'write' plus resource 'cover letter' is specific.

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 explicitly says 'Use whenever the user asks for a cover letter for a specific job' and provides detailed when-to-use guidance for STEP 1 vs STEP 2, including when to pass job_id vs job_description. It also references sibling tools for job_id resolution, giving clear alternatives.

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