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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the description's job is added context, and it delivers: it warns that cogsCoverageAllTime and marginBasisAllTime describe the entire order history rather than the current period, which prevents a real misinterpretation. It stops short of covering data freshness or staleness, hence 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?

It is dense and front-loaded with the core scope statement before drilling into field-level caveats. The heavy parenthetical detail (productFacts enum explanations, the margin caveat) is justified because there is no output schema carrying that meaning, though a single long paragraph is slightly harder to scan than a segmented one.

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 no output schema and no parameters, the description carries full responsibility for conveying what comes back, and it does so thoroughly, including per-field semantics for productFacts and a cross-tool disambiguation for the all-time vs period margin metrics. Nothing an agent needs before calling is missing.

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?

The tool takes zero parameters (empty object, additionalProperties=false), so there is nothing parameter-level to document; the baseline for a no-param tool applies. The description usefully focuses its effort on interpreting the returned fields instead.

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?

It states a specific resource ('Everything Nuira knows about this company') and enumerates the exact content domains returned: economics/targets, decision rules, productFacts, suppliers, channels, locations and product lines. This is far more specific than a sibling like get_data_status or get_summary and lets the agent distinguish it without opening a 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?

It gives an explicit usage rule ('Use for any question about the business itself, what Nuira knows, or where a figure came from') and explicitly names the alternative tools (get_summary, get_product_performance) for the closely related period-coverage question. The when-to-use and when-to-use-something-else conditions are both stated.

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