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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds genuinely new context beyond them: it discloses the data basis ('actual company financial data and NZX historical precedents') and the cost profile ('Pure computation, $0 cost'). It stops short of stating limitations or accuracy caveats, so not a 5.

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 front-loaded sentences with the core purpose first, then event types, then data/cost notes. Efficient overall, though the event-type list duplicates the schema's enum text and slightly inflates the middle sentence.

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?

An output schema exists, so return values need no explanation, and annotations cover the safety profile. The description supplies what remains: scope, supported event types, data source, and cost, leaving no critical gap for correct invocation.

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 ticker, event_type, ocr_change, and customer_name. The description restates the event-type list but adds no syntax or format detail (e.g., bp convention) beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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?

Specific verb (simulate) plus resource (hypothetical event on an NZX company) and a concrete list of outputs (share price, revenue, governance, stakeholders). The enumerated event types and the sibling simulate_investor_qa make the boundary clear, so an agent can distinguish it 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 event-type list implies the kinds of scenarios it covers, but the description never states when to pick this over related siblings like get_dividend_cut_probability, get_takeover_probability, or get_dividend_stress_test, nor any prerequisites. Usage is inferable but not guided.

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