predict_demand

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

No annotations provided, so description carries full burden. It discloses data caching (~5 min) and mentions the key output field. However, it does not state whether the tool is read-only, permissions needed, or potential side effects. It provides moderate transparency.

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?

Two sentences with precise language. No redundant words. Purpose is stated upfront, followed by key output explanation and caching note.

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?

The description adequately explains what the tool does and the main output for a 3-parameter tool with no output schema. It could benefit from a brief note on return structure or error conditions, but overall it's sufficient for agent understanding.

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 description coverage is 67% (limit and refresh have descriptions, sortBy lacks description but enum values are self-explanatory). The description adds minimal extra parameter meaning beyond schema, mostly contextualizing the output rather than parameters.

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 action ('Forecast... and compare') and resource ('top Aerodrome pools'). It distinguishes from siblings (pool_history, recommend_allocation, etc.) by specifying it's about next-epoch demand vs current allocation.

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 explains the key output (predictiveEdgePct) and its interpretation (positive edge = under-incentivized), giving context for when to use. It implicitly suggests this tool for identifying under-incentivized pools, but lacks explicit when-not-to-use or alternative comparisons.

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