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

With no annotations, the description carries the full burden and does substantial work: it discloses the fact-preserving rule/automated-check behavior, warns 'AI can make mistakes', lists the full return payload, and states that the cover letter can be null. It does not cover latency, data retention, or failure modes beyond the null cover letter.

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?

A single front-loaded sentence that opens with purpose before trailing qualifications (fact-safety disclaimer, rate limit, upsell). Every clause carries information, though the nested parentheses make it denser than it needs to be.

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?

There is no output schema, so enumerating the returned artifacts (tailored CV, match score, role-fit notes, interview prep, nullable cover letter) is the right compensation, and rate limits are disclosed. Remaining gaps are modest: no input size limits or handling of unparseable job postings.

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% with only two required string parameters, so the schema already documents both inputs fully. The description adds only the framing that the CV is tailored against a 'specific job posting', which maps trivially onto jobDescription; baseline 3 applies.

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?

Uses a specific verb ('tailor/rewrites') plus resource ('CV/resume') and scope ('to a specific job posting'), and enumerates what comes back. It does not explicitly name or contrast with the sibling score_cv, so the distinction (rewrite vs. score-only) is left to inference from the verb.

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?

Gives a clear triggering context (tailoring a CV to a specific posting) and routes heavy usage elsewhere by noting the trial is rate-limited per network and the MaxCV web app is needed for more tailorings and PDF export. It never explicitly says when to prefer score_cv instead, so the alternative-selection guidance is incomplete.

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