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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds real behavioral context beyond that: business_model is inferred from other inputs when omitted, and sector notes are conditionally appended only when the inputs name a supported sector.

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?

One dense, front-loaded sentence that leads with the gap-analysis scope before listing outputs and the conditional sector-note behavior. No filler, though the trailing clause about sector notes slightly crowds the core statement.

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 by naming the analysis components (ideal-vs-current deltas, metric gaps, causes, actions, sector notes). Combined with annotations covering the safety profile, an agent has enough to call it correctly, though required-input expectations are left to the schema.

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, and the description genuinely adds semantics on top by disclosing fallback behavior (business_model 'read from your other inputs when left out') and the conditional sector-notes behavior tied to product_category/inputs.

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: 'Analyze gaps between your current customer base and your ideal ICP', and enumerates what the analysis covers (profile deltas, metric gaps, causes, actions). It is clear, though it does not explicitly distinguish itself from near-neighbors such as icp_deep_dive or icp_scoring_model.

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?

There is no statement of when to use this tool versus the eight sibling ICP tools, and no prerequisites or exclusions. Usage is only inferable from the phrase 'gaps between your current customer base and your ideal ICP', which is descriptive rather than directive.

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