getAuroraStrategy

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

With no annotations, the description carries full burden. It discloses the read nature ('Returns'), rate limit (20 req/s per UID per path), and implies safety. It does not mention authentication or caching, but the provided details are sufficient for a get tool. No contradictions.

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 tightly written: one sentence for purpose, one for rate limit, one agent hint with usage instruction and alternatives. No redundancy, easy to scan.

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's simplicity (one parameter, no output schema), the description covers all needed context: what it returns, prerequisite (aurora_id), suggested workflow, and rate limits. Complete for agent decision-making.

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 only parameter, aurora_id, is described as 'encoded ... previously returned by one of the recommendation endpoints', adding crucial context beyond the schema's bare type definition. This clarifies source and format, fully compensating for 0% schema description coverage.

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 it 'Returns the full Aurora AI strategy (params + backtest metrics)' identified by an aurora_id. It distinguishes from siblings by explicitly directing users without an aurora_id to recommendation endpoints, making its purpose specific and non-overlapping.

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 provides explicit guidance: use when you have an aurora_id to refetch/refresh; do not use if you lack an aurora_id, in which case call one of four named recommendation endpoints first. This fully covers when-to-use, when-not-to-use, and alternatives.

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