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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral detail beyond annotations: thin rounds return low_sample=true instead of fabricated precision, and the consensus price is defined as stake-weighted median. This gives the agent more insight into edge cases and output semantics.

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 dense sentence that front-loads the core purpose and then enumerates metrics efficiently. While it packs in many details, each element earns its place; it borders on run-on but remains scannable and useful.

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?

With no output schema present, the description carries the burden of explaining return values. It enumerates the key metrics (consensus price, dispersion, quartiles, bullish/bearish split, low_sample flag) and clarifies edge-case behavior, giving an agent enough context to interpret results 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?

Schema description coverage is 100%, with each parameter (pool, round, history_window) already documented with defaults and ranges. The description references the historical percentile baseline, which relates to history_window, but does not add param-specific detail beyond what the schema provides, so baseline 3 is appropriate.

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: 'Aggregated crowd analytics for one prediction-pool round', then details the exact metrics returned. This makes the tool's purpose unmistakable and clearly distinguishes it from sibling pool tools like get_btc_pool_state or get_btc_pool_history.

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 clearly scopes usage to a single prediction-pool round and notes it is read-only, which helps an agent choose it for analytics. However, it does not explicitly name alternatives or state when not to use it, leaving some inference to the agent.

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