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AstroNest

Forward-looking reading for a question

get_forecast
Read-only

Forward-looking reading for a question. The interpret verdict for domain, voiced as a narrative answer to question by a language model grounded in the classical statements for the domain. Expect tens of seconds; set a client timeout of at least 90 s. Cost: 8 credits per call (only successful calls are charged; a sandbox key is free and returns a fixed sample). Voiced by a language model: allow up to 90 seconds. Example arguments: {"birthData":{"date":"1990-05-12","time":"14:35","timezone":"Asia/Kolkata","latitude":28.6139,"longitude":77.209},"domain":"career","question":"How will the next year unfold for my work?"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesLife area the question is about, e.g. career, marriage, finance or health.
questionYesThe question in plain language, e.g. "What does the next year hold for my career?"
birthDataYesThe person's birth data: date, local time (omit if unknown), IANA timezone, latitude and longitude.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, non-destructive, not idempotent, closed-world), and the description adds substantial context on top: it warns of tens-of-seconds latency and a 90 s minimum client timeout, states the 8-credit cost with the rule that only successful calls are charged, and explains that a sandbox key is free and returns a fixed sample. That billing and latency disclosure is exactly the kind of behavior the annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first sentence, followed by cost/latency notes and a concrete example. It is a bit dense with repeated latency warnings ('tens of seconds' then 'allow up to 90 seconds'), but every block is actionable and there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-parameter, nested-object tool with an output schema, the description covers what is needed to invoke it correctly: cost, latency expectation, sandbox behavior, and a complete example. Return-value detail is legitimately omitted because an output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already carries the parameter meaning and the baseline is 3. The description goes slightly beyond by supplying a full worked example of the three arguments, showing how domain, question, and nested birthData (with timezone and coordinates) are populated together.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it produces an interpretive verdict for a domain, voiced as a narrative answer to the user's question by a language model grounded in classical statements. This distinguishes it conceptually from a raw verdict tool, but it never names a sibling (e.g. interpret_domain or get_guidance), so the agent must infer which of the forward-looking tools to pick.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by 'forward-looking reading for a question' rather than stated as a rule, and there is no explicit when-to-use/when-not guidance against siblings like interpret_domain, get_guidance, or resolve_timing. Cost and timing notes hint at when it is worth calling, but routing guidance is absent.

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

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