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

Annotations cover the safety profile (readOnly, non-destructive, closed world), so the bar is lower, and the description adds real context beyond them: it discloses the returned artifacts, how sector and business model are inferred from other inputs, and how goals map to metrics. It does not mention any rate limits or failure modes, but for a read-only generator this is solid disclosure.

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 sentences, front-loaded with the outcome, then input-format guidance, then the sector/business-model nuance. Every sentence carries information, though the middle sentence is slightly circuitous and the goal-filing clause is a little dense.

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 11 parameters, no output schema, and six enums, the description compensates by naming the returned artifacts and explaining the inference fallbacks for optional inputs. An agent has enough to call it correctly, though the relationship between goals and the metrics table could be spelled out a bit more.

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 100%, so the baseline is 3, but the description goes further by explaining inference behavior for optional fields (sector and business model are read from other inputs and reported back) and the accepted launch_date formats with their planning implications. That meaning is not fully captured by the schema alone.

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 action (takes launch inputs) and a concrete deliverable set: a phased launch plan with tasks, a messaging table and success metrics. That output signature clearly separates it from siblings like pmf_scorecard or craft_gtm_analyzer, so an agent can route without reading the schema.

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?

The description gives useful input-handling guidance (give a date for a dated timeline, use 'TBD' or 'Q2 2027' for a flexible plan) and explains that optional fields are auto-inferred. However, it never says when to choose this tool over the sibling planning tools, nor any prerequisites or exclusions, so usage is only implied.

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