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

Annotations already declare readOnly/non-destructive/closed-world, so the safety bar is low. The description adds real behavior beyond that: it discloses that ICP match rate and Year 1 share have example defaults applied when omitted, and that sector notes are conditionally appended based on inputs. It does not explain the response format, but no output schema exists to lean on.

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, front-loaded with the core action and method, followed by the one behavioral caveat that matters (sector notes). No padding or repetition of fields.

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 stateless calculation tool with full schema coverage and no output schema, the description covers what it computes, what it is not, and the two conditional behaviors. Only the shape of the returned result is left unspecified, which is a minor gap.

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 eight parameters including the 30% and 3% defaults. The description restates the four driving inputs 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?

States a specific verb (calculate) and resource (TAM/SAM/SOM) with the method (bottom-up) and names the exact inputs used in the arithmetic. The parenthetical 'calculation framework, not a data source' cleanly distinguishes it from data-oriented siblings like lookalike_signal_generator and icp_deep_dive.

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 implies usage ('calculation framework, not a data source' and the sector-notes condition) but never states when to reach for this versus sibling ICP tools such as icp_scoring_model or account_prioritization. Guidance is inferable but not explicit.

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