propose_allocation

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds value by explaining that every weight comes from a deterministic core, that it never trades or gives return forecasts, and that the verdict may be null if reference tickers are not cached, with a warm note. This enriches the behavioral understanding beyond annotations.

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?

The description is a single paragraph but conveys all necessary information efficiently without redundancy. It could be broken into shorter sentences for easier scanning, but it is not overly long and every sentence contributes value.

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?

Given the tool has only two parameters with enums, an output schema (not shown but exists), and annotations, the description covers the tool's core function, input options, edge cases (cache miss), and boundaries (no trading, no recommendations). It is complete for an agent to decide when and how to invoke it correctly.

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 input schema has two parameters with enums but no descriptions (0% schema description coverage). The description compensates fully by naming the preset options (conservative/moderate/aggressive), the benchmark options (60-40/all-weather/permanent), the special value 'none' to skip validation, and the default values. This adds significant meaning beyond the schema.

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?

The description clearly states the tool's purpose: proposing a strategic target allocation for a given risk posture and validating it against a canonical benchmark. It specifies the verb 'propose', the resource 'allocation', and the scope 'over user's book + curated universe', distinguishing it from sibling tools like 'rebalance_check' or 'risk_report'.

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?

The description explicitly says when to use the tool: to answer 'what should a moderate portfolio look like for me, and is it sound'. It also clarifies what the tool does not do (never trades, never a recommendation), providing implicit when-not-to-use guidance. While it does not name alternative tools directly, the context and sibling list help differentiate.

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