pulse_cohort_summary

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

No annotations provided, so description carries full burden. It describes output structure but does not mention behavioral traits like rate limits, side effects (none), or authentication needs. It is a read operation but not explicitly stated.

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 concise with two main sentences and a list of tiers. It is front-loaded with the purpose. The tier list is informative but could be slightly trimmed; still efficient overall.

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 summary tool with one parameter and no output schema, the description covers what each tier returns (wallet count, avg PnL, avg win rate, total volume). It is complete enough for an agent to understand the output. Missing details on return format beyond toon/JSON are minor.

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 coverage is 100% (one boolean parameter). Description adds no extra meaning beyond the schema; it only mentions 'compact toon format' which is already in the parameter description. Baseline score applies.

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 'Get behavioral cohort analysis across every tracked wallet on Hyperliquid' and lists specific PnL and size tiers with what each shows. This is specific and distinguishes it from sibling tools like pulse_cohort_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 provides context: it is 'unique intelligence' and suggests calling pulse_global_stats first for the total wallet count. It lacks explicit when-not or alternatives but gives actionable prerequisite guidance.

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