stripe_forecast_snapshot

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 forecast is server-computed without a Stripe round-trip, and lists the output fields. This provides good behavioral insight beyond what annotations would convey, but could mention auth requirements or data freshness.

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?

Two sentences, no fluff. Front-loaded with the core purpose, followed by specific outputs and a note on computation. Every sentence earns its place.

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 tool with no inputs and an output schema present, the description is complete. It identifies key outputs and the nature of the computation. No gaps remain for an AI agent to understand what this tool does and what it returns.

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?

The input schema has zero parameters, so description does not need to explain parameter meaning. It compensates by describing the output fields clearly, which adds value given the baseline for zero parameters is 4.

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 it provides a 'predictive forecast for the merchant' and lists specific outputs (MRR, failed-payment rate, dispute risk band, payout cashflow band). This distinguishes it from sibling tools like stripe_list_invoices or stripe_create_refund, which are CRUD operations.

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 implies usage for obtaining a forecast but does not explicitly state when to use this tool versus alternatives. It mentions 'server-computed; no Stripe RTT' which hints at speed but lacks explicit exclusions or when-not-to-use guidance.

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