pulse_cohort_history

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns historical data aggregated by day, covering PnL, trade count, and activity. However, it does not mention the compact toon format default (useToonFormat), potential pagination, or any constraints like rate limits or authentication. The core behavior is transparent but lacks depth on response format and edge cases.

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 two sentences: the first states the core purpose, the second gives a concrete example of use. Every word is meaningful; there is no redundancy or filler. The structure is front-loaded with the most important information, making it easy for an agent to quickly grasp the tool's function.

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 tool has four parameters and no output schema, yet the description does not explain the return format (e.g., time series structure, fields included, how compact toon format differs from standard JSON). While the example provides a trend context, important details like the role of the 'days' parameter or the default true for 'useToonFormat' are omitted. The description is incomplete for an agent to fully understand the tool's behavior without inspecting the schema.

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%, so the schema already documents all four parameters in detail. The description adds no further parameter guidance beyond the example referencing 'sharps' tier. It does not explain the meaning of 'days', 'tierType', or 'useToonFormat', or how they affect the output. Given the high schema coverage, a baseline of 3 is appropriate, but the description could have added context on parameter interplay.

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 uses a specific verb ('Get') and resource ('historical performance data for a specific trader cohort'), clearly stating the tool returns day-by-day aggregate PnL, trade count, and activity. It distinguishes from sibling cohort tools like pulse_cohort_summary or pulse_cohort_positions by focusing on historical trends over time, and provides an example usage that grounds the purpose.

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 gives a concrete use case ('spot trends like the sharps tier being increasingly bearish over the last month'), which implies when to use this tool. However, it does not explicitly contrast with alternatives (e.g., pulse_cohort_bias_history for bias direction, pulse_cohort_performance_daily for daily metrics) or state when not to use it. The guidance is clear but could be more explicit about exclusions.

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