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

Adds substantial behavioral context beyond the annotations: 7 credits per call with only successful calls charged, a free sandbox key returning a fixed sample, expected latency of tens of seconds up to 90 seconds because an LLM voices the result. Annotations cover the read-only/idempotency profile, so this cost-and-latency disclosure is the real added value.

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?

Three short blocks front-load the purpose, then cost/latency, then an example. Every sentence carries information, though the opening 'Like forecast' is slightly redundant with the sibling comparison already implied by the name.

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 an output schema present, the description needn't explain return values, and annotations plus full schema coverage handle the rest. Cost, latency, and a worked example make it callable without further digging, though it never states prerequisites (e.g., whether birth data accuracy affects results) beyond what the schema notes on omitted time.

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 every parameter and the enum domain. The full example arguments object illustrates how birthData, domain, question, and targetDate combine, which is mildly useful, but no syntax or domain meaning is added beyond structured fields. Baseline 3 applies.

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?

States a specific function (decision timing for a decision question) and explicitly relates it to the sibling get_forecast while distinguishing the use case. The resource is identifiable, though the phrasing 'Decision timing' as a lead is terse and partly restates the title.

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?

It implies usage via 'for a decision question' and notes optional anchoring to targetDate or dateRange, but never states when to pick this over get_forecast, find_muhurta, or get_guidance. The guidance is implied rather than explicit.

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