pulse_cohort_recent_lifecycle_stats

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It is a query tool, but the description does not mention that it is read-only, how data freshness is handled, or define key terms like 'lifecycles' or 'wins/losses.' The lack of behavioral detail beyond the purpose leaves the agent guessing about side effects, caching, or definitions.

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, front-loaded with the core purpose and a usage hint. No wasted words; every sentence adds value. It is appropriately sized for the tool's complexity.

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 5 parameters, no output schema, and medium complexity, the description lists the returned metrics (lifecycles, wins, losses, etc.) and the cohort definition, which is helpful. However, it lacks details on the output structure, ordering, pagination behavior, and definitions of lifecycles/wins. It is mostly complete but has minor gaps.

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 adds context about the cohort being defined by the last 30 days and the 'per-wallet' nature, but the schema already provides detailed descriptions for all parameters (tier, tierType, limit, offset, useToonFormat). Thus the description adds marginal value beyond the schema.

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 returns per-wallet lifecycle stats for a cohort defined by a LAST-30-DAY tier, listing specific metrics (lifecycles, wins, losses, etc.). This verb+resource combination is specific and distinguishes it from sibling tools like pulse_cohort_summary (aggregate) or pulse_cohort_positions (positions).

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 advises using the tool for 'position-level analysis of who is currently printing,' which gives clear context. However, it does not explicitly contrast with alternatives (e.g., when to use pulse_cohort_summary instead) or state when not to use it, so some implicit guidance is present but not fully explicit.

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