pulse_cohort_recent_positions

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 explains that the tool returns 'live positions' and 'currently-printing wallets,' which implies a read-only, real-time query. However, it does not disclose details such as rate limits, data freshness, or error handling. The description adds value by explaining the cohort definition (last-30-day tier) but could be more explicit about behavioral traits like caching or update frequency.

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 long, front-loading the core purpose in the first sentence and adding a critical differentiator in the second. Every word earns its place; there is no redundancy or fluff. It is concise and well-structured for an AI 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?

Given the tool has 4 well-documented parameters and no output schema, the description sufficiently explains what the tool does and its key differentiator from the all-time sibling. It is complete enough for a user to decide when to use it. However, it could be slightly improved by explicitly naming the sibling `pulse_cohort_positions` and mentioning that the output is a list of positions (though that is implied by 'positions held').

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 baseline is 3. The description does not add any parameter-level information beyond what the schema already provides. The schema's parameter descriptions are detailed (e.g., enum values, defaults, meaning), so no additional context is needed from the description. The tool's description focuses on the overall purpose, not individual 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 tool retrieves live positions for a cohort defined by its last-30-day tier, not lifetime tier. It explicitly distinguishes from the sibling `pulse_cohort_positions` (all-time) by noting it catches regime changes the all-time version misses. The verb 'surfaces' paired with 'positions' and 'wallets' makes the resource unambiguous.

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 clear context for when to use this tool: when the user wants positions based on recent 30-day behavior rather than lifetime tier. It contrasts with the all-time version by mentioning regime changes. However, it does not explicitly list alternatives or state when not to use this tool, leaving some room for ambiguity.

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