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

Annotations declare a non-read-only but non-destructive operation, and the description adds real value on top: explicit daily quotas (free 1, PRO 3), the 429 quota_exceeded failure mode, and the return shape {session, usage}. It does not say whether a failed/roasted run consumes quota or what the session object enables, which keeps it below 5.

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 short sentences, front-loaded with the purpose, then limits, then routing cue and return shape. No filler or restatement of the title.

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 responsibly discloses the return envelope and the quota error. The remaining gap is that '{session, usage}' is unexplained — an agent cannot tell from this whether the roast text is in the response or must be fetched separately.

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% and cvId even points to list_my_takemeup_cvs, so the schema carries the full burden. The description mentions neither cvId nor the locale fallback behavior, adding nothing beyond structured fields — baseline 3.

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?

Names a specific verb and resource ('roast of one of the user's CVs') and characterizes the output ('blunt feedback on what a recruiter would laugh at'). This clearly separates it from analytical siblings like analyze_takemeup_cv_ats or detect_takemeup_buzzwords, which read as objective tools rather than entertainment-with-substance.

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 asks for brutally honest feedback or a roast' gives an explicit triggering condition. It does not name a competing alternative tool or an exclusion (e.g., 'for ATS scoring use analyze_takemeup_cv_ats'), so it stops short of full routing guidance.

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