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

With no annotations, the description carries the full burden and does meaningful work: it discloses the mandatory async pattern (ALWAYS returns an analysis_id immediately, poll get_analysis_result until succeeded/failed), the 30-position inline cap, and the point-in-time semantics of as_of_date (current composition × historical data). It omits auth requirements, rate limits, and the failure/error surface, so it is strong but not complete.

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?

Dense but front-loaded, with the action and portfolio-sourcing constraint stated first and operational details following. The long parenthetical engine list and the packed final clause cost some readability, though every sentence carries load-bearing information.

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 complex, nested-schema tool with no output schema and no annotations, the description covers the async lifecycle, the return contract (analysis_id), config dependency, and portfolio alternatives. It would be complete at 5 with a note on permissions/limits or what a failed status implies.

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 0%, yet the description supplies semantics for all five parameters beyond the raw schema: portfolio_ref as a stored portfolio id, inline_positions as ad-hoc with max 30 of {symbol, amount-as-decimal-string}, config as engine-specific JSON Schema validated via list_risk_engines, and as_of_date with format plus the asOfDateSupported restriction. This compensates fully for the coverage gap.

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?

Opens with a specific verb+resource ('Submit a risk analysis') and enumerates the eight supported engines, immediately separating it from siblings like get_analysis_result and list_risk_engines. An agent knows exactly what this tool does and what domain it covers 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?

Explicitly states the one-of portfolio sourcing rule (portfolio_ref OR inline_positions, not both) and routes config validation to list_risk_engines and result retrieval to get_analysis_result. It lacks explicit when-not-to-use guidance (e.g. when to prefer list_risk_engines or how to distinguish stored vs ad-hoc portfolios), so it stops just short of the top.

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