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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered. The description usefully adds the scoring semantics (sector-relative percentile 0-100, A-F grades, six factors), which goes beyond the annotations, but says nothing about data freshness, universe size, or pagination.

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 sentences, front-loaded with what the tool returns before the filters and the use case. No filler, though the factor enumeration in sentence one partly duplicates the schema's factor parameter.

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 an output schema present, the description need not explain return values, and it does supply scope, filter dimensions and a use case. It stops short of clarifying how this differs from sibling factor tools, which is the one gap an agent would still hit.

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%, so the schema already documents all four parameters, and the description's 'Filter by sector, factor, grade' adds nothing beyond it. There is a minor inconsistency worth noting: the description lists 'Quality' as a factor while the schema's factor parameter uses 'profitability'.

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 ('Get NZ Equity Factor Model') and pins down scope precisely: market-wide, all NZX companies, six named factors, sector-relative percentile 0-100 with A-F grades. It does not, however, distinguish itself from near-siblings like get_factor_grades or get_alpha_factors, which an agent could easily confuse it with.

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?

One sentence gives a use case ('factor-based stock selection and quantitative screening'), which implies when to reach for it. There is no when-not guidance and no named alternative among the many factor/alpha siblings, so the agent must infer routing on its own.

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