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

Annotations only declare the safe-mutation profile (readOnly=false, destructive=false, idempotent=false); the description adds the plan/PRO gate and the AI-consent requirement, which are the real blockers an agent will hit. It also discloses the return shape ({result, cacheKey} or a plan gate), which the missing output schema would otherwise leave unknown. It does not say whether the letter is persisted or how long generation takes.

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?

Four short sentences, with purpose, inputs, and usage condition front-loaded before the gating and return details. Minor redundancy between the parenthetical "(motivation letter)" and the rest, but nothing wasted.

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?

With no output schema, the description compensates by naming the return shape and the plan-gate failure mode, and it covers both prerequisites for a PRO generation tool. Missing only secondary details such as length/format of the produced letter or whether it is saved anywhere.

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 100%, so cvId, locale, and jobDescription are already fully documented, and the description only echoes their existence ("from one of the user's CVs and a job description"). The one thing it could clarify, that "conventions of the CV's country" is not the same as the locale parameter, is left ambiguous. Baseline 3 is appropriate.

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?

States a specific verb and resource ("Write a cover letter (motivation letter)") plus the inputs that produce it (a CV and a job description) and the country-convention constraint. That combination is distinguishable from siblings like generate_takemeup_cv_summary or generate_takemeup_linkedin without opening any schema.

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?

"Use when the user needs a cover letter for a specific job" gives a clear triggering condition, and "PRO and AI consent" flags the prerequisites an agent must check before calling. It stops short of naming alternatives or stating when not to use it (e.g. no CV on file, no consent yet), so it is clear but not exhaustive.

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