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

With no annotations, the description carries the full burden and does well: it discloses determinism ('same inputs always give the same weights'), the hard output bounds (23-43% band), the neutral treatment of omitted inputs, and the non-advice disclaimer. It stops short of stating permissions, error behavior, or that the operation is side-effect free beyond the implied 'simulate' framing.

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 tight sentences, front-loaded with purpose before mechanics, and each clause carries information (output shape, bounds, default handling, determinism, disclaimer). Slight overlap between 'always within the 23-43% band' and the determinism sentence keeps it from a perfect score.

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 10-optional-parameter compute tool with no annotations and no output schema, the description usefully compensates by spelling out the returned shape (proportions, convictions, rationale) and the bound/default behavior. It is adequate; only edge cases (invalid ranges, error responses) are unaddressed.

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 per-parameter meanings are already documented and the baseline is 3. The description adds genuinely new semantics: all ten inputs are optional, any subset is accepted, and missing values default to neutral — behavior the schema does not express.

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 precise verb+resource ('Run the vault's allocation model on YOUR market inputs') and names the exact outputs (buy proportions for gold / S&P 500 / treasuries, per-asset convictions, rationale). The word 'simulate' plus 'YOUR market inputs' clearly separates it from siblings like get_todays_allocation (actual allocations) and get_market_signals (current data), so an agent can route 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?

Gives solid invocation guidance ('all inputs are optional numbers; provide any subset and the rest are treated as neutral'), which tells the agent how to call it. However, it never states when to use this simulation versus get_todays_allocation or get_market_signals, nor any exclusions, so the when-to-use decision is left to inference.

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