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

Annotations already declare readOnlyHint=true, so safety is covered. The description goes further by disclosing the return payload, the no-match behavior ('returns no books'), and a scope exclusion ('therapy is excluded') — useful edge-case context beyond the annotations.

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 packs purpose, return fields and edge behavior without filler. It is slightly run-on but each clause carries distinct 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?

For a one-parameter read-only lookup with no output schema, the description supplies the essentials: what it matches, what it returns, and the empty-result and exclusion rules. Only the exact match semantics (fuzzy vs keyword) remain underspecified.

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?

Only one parameter exists and schema description coverage is 0%, so the description must carry the burden. 'A leader's stated problem' hints that the input is free-form natural language text, but no length or format guidance is given beyond the schema's 3–500 char bounds.

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?

States a specific verb and resource (match a problem to active workbook descriptions) and enumerates the returned fields (terms, audience, intended benefit, Stan link). It implicitly distinguishes itself from list_workbooks by matching on a stated problem rather than enumerating all workbooks, but it never names a sibling explicitly.

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?

Usage is implied by the required 'problem' input — call it when a leader has voiced a problem — but the description gives no explicit when-to-use/when-not-to guidance and does not name alternative tools such as list_workbooks or check_fit.

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