Builder Cohorts

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

Annotations already declare readOnly/openWorld/idempotent, and the description adds substantial behavioral context: tiers are lifetime labels emitted as legacy slugs, missing wallets roll into 'untracked' so counts always sum to totalUsers, attribution undercounts relative to ledger revenue due to trigger-order fills, results are ordered largest cohort first, and Pro tier is required. No contradictions with annotations.

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 dense but every sentence earns its place: core resource and metrics, tier semantics and untracked bucket, attribution caveat, concrete use cases, and access requirement. It is front-loaded with the most important compositional detail before caveats and use cases.

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, the description carries the burden of explaining the return contents, and it does: fields returned, cohort ordering, tier semantics, untracked behavior, dataNotes caveat, and access restrictions. For a moderately complex 3-parameter tool, nothing critical is missing.

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 builder, period, and useToonFormat. The description echoes the period concept and notes the day/week/month window, but adds no new parameter-level meaning beyond the schema. This matches the baseline for fully covered schemas.

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 identifies the resource — a builder's attributed users — and specifies the exact segmentation (all-time profitability and size tiers) plus the metrics returned, so an agent can tell it apart from pulse cohort tools. It distinguishes from siblings by explicitly noting these are lifetime tiers, not the 30d-rolling tiers used by pulse cohort tools. However, it opens with a noun phrase ('Cohort composition of...') rather than an explicit verb like 'Returns' or 'Lists'.

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 explicit use cases: 'is builder X's user base smart money or exit liquidity?' and 'do whales or shrimp pay most of its fees?'. It also gives a when-not signal by contrasting the lifetime tiers with the 30d-rolling tiers used by pulse cohort tools, steering agents toward the correct tool family.

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