linkedin_generate_cover_letter

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

Beyond the annotations, the description discloses important behavioral traits: it draws evidence from real experience rather than inventing achievements, reports gaps for improvement, and warns that the output needs rewriting for voice. These are valuable insights that the annotations alone do not provide, making this a standout description.

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 three sentences, each earning its place: the first states the core function, the second explains the evidence-based approach and gap reporting, and the third provides an actionable next step. No filler or repetition.

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 complexity (7 params, no output schema), the description covers the key behavioral aspects (grounded in profile, gaps, rewrite) but does not mention that the tool can save output to disk (save=true default) or return format. Since the schema covers save, this is a minor miss, but the description is still quite complete for a drafting tool.

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 86%, so the schema already documents most parameters. The description adds no direct parameter-level details, but it does reinforce the purpose of the job and profile inputs by mentioning 'user's real profile' and 'specific job posting.' This meets the baseline of 3 for high schema coverage.

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 function with a specific verb ('Draft') and resource ('cover letter'), and distinguishes it from sibling tools like linkedin_generate_resume by grounding it in the user's profile and a specific job posting. This is exactly the kind of specific verb+resource+scope that the rubric rewards.

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 when to use this tool—when a cover letter is needed based on a job posting and profile—and adds practical guidance by telling the agent to rewrite for voice before sending. It does not explicitly name alternatives or exclusions, but the context is clear enough for a 4.

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