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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: it infers the business model from inputs when not supplied, conditionally omits the activation dimension, and quotes and answers customer feedback. It does not state limits on metric parsing beyond the schema's note that unscored figures are listed as such.

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?

Three tight sentences, front-loaded with the core action and followed by the inference and dimension-exclusion rules; little waste. Slightly dense with metric enumeration that largely duplicates the schema, keeping it short of a 5.

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 so reasonably: a scorecard scoring each dimension against benchmark ranges plus quoted-and-answered feedback. With read-only annotations covering safety, the remaining gap is depth of the output shape, which is described only at a high level.

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 schema already documents all seven parameters including enum meanings and optionality. The description restates the metrics input and business-model inference but adds no syntax or format detail beyond the schema, so the 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+resource: it returns a product-market fit scorecard that scores each metric dimension against example benchmark ranges, with model-aware behavior (activation omitted for services/connectivity/investment). This is clearly distinguishable from the surrounding sibling playbooks, though it never names an alternative tool to route against, which is what a 5 would require.

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 rather than stated: an agent can infer it should call this when a PMF assessment is wanted, since the description explains the inputs it consumes. There are no explicit when-to-use/when-not-to-use conditions and no mention of when to prefer a sibling such as retention_playbook or craft_gtm_analyzer.

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