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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds contextual behavior beyond these: the narrative=true option incurs a paid model call and is limited to 60 per hour, plus it clarifies the output contents. This cost/rate-limit information is valuable for an agent to know before invoking the tool.

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 description is three sentences, each earning its place: the first states the use cases, the second describes the core output, and the third explains the optional narrative with its cost and limit. It is front-loaded with the most important information and contains no filler.

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?

Given the simple two-parameter tool, no output schema, and strong annotations, the description covers the essential return values (match percentage, covered/missing requirements, optional narrative assessment) and the cost implication of narrative. It could be more explicit about whether the output is structured or free-text for the narrative, but the tool is simple enough that this is a minor 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 coverage is 50%: job_id is well documented (source from list_matching_jobs or list_my_applications), while narrative is only typed as a boolean with default false. The description compensates for narrative by explaining that true adds a short written assessment with strengths and gaps and that it is a paid, rate-limited call. This adds meaning beyond the schema, though job_id needs no further explanation.

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 ('explain'), the resource ('job match' for one vacancy), and the exact outputs (match percentage, covered and missing requirements). It also lists three natural-language triggers ('is this job a good fit', 'why this match', 'what am I missing for this role') that help an agent recognize when this tool is relevant, distinguishing it from sibling tools like get_match_status or list_matching_jobs.

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?

Explicitly begins with 'Use for ...' and gives three user-intent phrases, which is strong when-to-use guidance. It also scopes to 'one vacancy' and notes the paid, rate-limited nature of narrative=true. It lacks an explicit when-not-to-use or alternative tool mention, but the use-case phrasing is clear enough for proper routing.

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