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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed world, so the safety profile is covered. The description adds real context beyond that: the output is a bounded set of 5-10 workflows drawn from a fixed built-in library rather than generated arbitrarily, which is meaningful with no output schema present.

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?

Two sentences with zero filler: the first front-loads the transformation and its output, the second enumerates the inputs. Nothing is repeated or padded.

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-value burden and does state the count and provenance of results. Inputs are fully enumerated in the schema, and the read-only, idempotent nature is covered by annotations; the only gap is the absence of sibling routing.

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 the baseline is 3. The description restates five of the six inputs in prose (line of business, team size, AI usage, data rules, bottleneck) but omits health_information and adds no format or value guidance beyond what the schema already states.

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+resource ('Take short answers ... and return 5 to 10 starting workflows') and names the source library ('built-in benefits and P&C library'), so the agent knows exactly what it produces. It does not, however, distinguish itself from the sibling find_workflows, which plausibly overlaps in function.

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 input list ('asks for line of business, team size, how AI is used today...'), which tells the agent the preconditions for a useful call. There is no explicit when-to-use vs. find_workflows or build_governance_policy guidance, and no exclusions, so it stays at implied rather than stated.

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