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

Annotations already cover the safety profile (readOnly, idempotent, openWorld=false, non-destructive), so the bar is lower. The description adds substantive scope context — it is an early-warning cross-market scanner over all NZX companies with a defined detection taxonomy — which tells the agent what breadth of results to expect. It stops short of noting result limits or pagination behavior.

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?

Front-loads the core purpose, then the detection list, then triggers, then routing — a sensible order. The 16-item anomaly enumeration and the trigger-phrase list are somewhat verbose, but each block carries distinct information an agent needs for selection.

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-format detail is unnecessary. Combined with the annotations and full schema coverage, the description supplies everything needed to pick this tool over its siblings and call it correctly with zero required parameters.

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 all five filters (days, sector, ticker, category, severity) are already documented in the schema. The description does not mention any parameter or its defaults, so it adds no meaning beyond the schema; the baseline 3 applies. The 7-category taxonomy mentioned loosely relates to the category filter but does not map cleanly onto its five enum values.

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+resource (market anomaly detection results) and concretely enumerates the 16 anomaly types across 7 categories, so the agent knows exactly what signal is returned. It also explicitly distinguishes itself from sibling company-level tools via the ROUTING block.

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?

Gives explicit trigger phrases ('red flags', 'warning signs', 'governance concerns across the market') and a clear when-not rule: use it only to find WHICH companies show patterns, and prefer get_governance_scores, get_agm_resolutions, get_audit_history, get_capital_raises when a company is already named. Alternatives and the selecting condition are both spelled out.

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