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

Beyond the readOnly/idempotent/destructive annotations, it discloses that nothing is stored, that scoring is deterministic ('the same way every time'), and that the score is a fixed formula rather than AI judgement. These are real behavioral traits not present in the structured fields, though it omits latency or failure behavior.

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 core purpose and scoring breakdown are front-loaded and information-dense. It is slightly long, repeating the title in the first sentence and packing several marketing-style query examples, but every clause still carries usable signal.

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?

For a ten-parameter, all-optional tool with no output schema, it describes the return contents (matched/missing skills, strengths, gaps, keywords) and the scoring model well. It does not state which parameter combinations are valid (e.g. cv vs titles+skills), which is the main remaining gap.

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 all ten parameters are already documented in the schema. The description adds only indirect hints ('job from a search (or pasted advert)') and does not clarify the minimum viable input set, so 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?

The description states a specific verb and resource ('Scores a CV or profile against a job') and explains the exact output — a 0-100 score with weighted components. It is clearly distinguishable from siblings like compare_jobs or get_job.

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 enumerates the user intents that map to it ('how well do I match this job?', 'should I apply?', 'what's missing from my CV?') and notes the job can come from a search result or a pasted advert. It does not name an explicit alternative tool or a when-not-to-use case, so it stops short of a 5.

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