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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses the scoring weights (0.5/0.3/0.2), the cap for missing hard requirements or impossible claims, the 30,000-character limit, and that job_fit plus a keyword match summary are returned. It even pins the rules version (2026-10-19), which pins down reproducibility.

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 primary verb and output are front-loaded, and the two long sentences avoid filler. The second sentence is dense with parenthetical detail on scoring weights, which costs some scannability but each clause carries substantive information.

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 carries the return-shape burden and does so: issue codes, parsed structure, word counts, and the conditional job_fit/keyword summary. An agent has everything needed to call it and interpret the response.

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%, so the baseline is 3, but the description adds real semantics: job_description does not merely filter, it redefines the score as job fit and adds job_fit/keyword outputs, and target_role unlocks role-specific advice. That is meaning beyond the schema's terse parameter blurbs.

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 gives a specific verb and resource: score a resume 0-100 with fixed rules and list each issue with a stable code. It also enumerates the parsed-text output, making the tool's scope distinct from narrower siblings like check_bullets. It never names a sibling to route against, so it stops short of full differentiation.

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 states the conditions that change behavior: role-specific advice only appears when the resume names a target title or target_role/job_description is passed, and passing job_description switches scoring to job fit. That is clear conditional guidance, but there is no explicit when-not or comparison to alternatives such as match_job or keyword_scan.

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