recAuroraHomeAIParams

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

Beyond the annotations, the description discloses useful behavioral context: results are curated, mixed across bot types, capped at 18 strategies (6 for Copy Trading leaders), and rate-limited to 20 requests per second per UID per path. It also clarifies that the request takes no parameters and gives downstream usage guidance, which goes well beyond what the annotations provide.

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 well-structured and front-loaded: the core purpose comes first, followed by limits, rate limit, and actionable agent hints. Every sentence adds value, and there is no redundant filler or repetition of the tool name or schema.

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 zero-parameter, read-only endpoint with no output schema, the description is complete enough for an agent to select and invoke it correctly. It covers what the result contains, how many items to expect, the rate limit, and how to use `aurora_id` downstream. No critical operational detail appears to be 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 input schema is empty and schema description coverage is 100%, so there are no parameter semantics to document. The description still usefully states 'The request takes no parameters,' reinforcing that the agent should not look for or supply arguments. This aligns with the 0-parameter baseline.

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 opens with a specific verb and resource: 'Returns a curated list of Aurora AI strategy recommendations for the home feed of the trading-bot product.' It clearly states the scope, the mixed bot types, and points to the `biz_type` field, making it easy to distinguish from related recommendations and creation tools.

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 trigger condition: 'Use this when a user opens the trading-bot home page and wants to see what Aurora is currently recommending.' It also explains what to do next with `aurora_id`, but it does not explicitly contrast this tool with siblings like recAuroraCreationAIParams, so the when-not-to-use guidance is implicit rather than explicit.

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