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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the bar is lower. The description adds genuine behavior: the output shape (tiers, commission rows, KPIs), that deal size scales example amounts while rates stay fixed, that a range is refused, and that omitted optional fields are inferred and the inference is reported back – a useful transparency trait. It does not describe output size, format or failure modes beyond the range refusal.

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 dense sentences, front-loaded with purpose then output shape, with no filler. It is information-rich rather than padded, though the second sentence packs several conditional facts together and would read better as short clauses.

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 10-parameter, 5-required analytical tool with no output schema, the description covers purpose, required inputs, return contents and optional-field fallback behavior. The remaining gap is the `industry`/`your_sector` overlap and what happens with partial or contradictory inputs.

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% with per-field descriptions and enums, so the baseline is 3. The description adds marginal meaning by saying program structure varies by partner model and that sector drives the named partner types, but it does not clarify the near-duplicate `industry` vs `your_sector` parameters, which is the one ambiguity an agent would actually need resolved.

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 ('decide what partner program to run and how to start it') and then enumerates the concrete deliverables: tiers, example commission amounts and KPIs. It is also clearly distinct from every sibling tool (pmf_scorecard, launch_commander, retention_playbook), so an agent can route without opening 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 use case is explicit ('decide what partner program to run and how to start it') and it notes that existing partners are used 'when given', which tells the agent when to populate an optional field. It stops short of stating when NOT to use it or naming an alternative sibling for adjacent partner questions.

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