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Glama

Weatherapi

by io.github.pipeworx-io

Astronomy

astronomy
Read-onlyIdempotent

Get astronomy data for a location and date: sunrise, sunset, moonrise, moonset, moon phase, and moon illumination. Example: astronomy({ q: "Reykjavik", dt: "2026-06-21" }).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesLocation — city name (e.g. "London"), "lat,lon" (e.g. "48.8567,2.3508"), US/UK/Canada zip/postcode, IATA airport code (e.g. "DXB"), or "auto:ip". NOTE on IATA codes: WeatherAPI resolves them to that airport's CITY, not the airport's own weather station — for the actual airport-station reading (can differ by several degrees) use the aviation-weather pack's metar tool with the airport's ICAO code instead.
dtNoDate in YYYY-MM-DD format (optional; defaults to today).
_apiKeyNoOptional — your own WeatherAPI.com API key for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / q / description
      Previous value: -"Location — city name (e.g. \"London\"), \"lat,lon\" (e.g. \"48.8567,2.3508\"), US/UK/Canada zip/postcode, IATA airport code (e.g. \"DXB\"), or \"auto:ip\"."New value: +"Location — city name (e.g. \"London\"), \"lat,lon\" (e.g. \"48.8567,2.3508\"), US/UK/Canada zip/postcode, IATA airport code (e.g. \"DXB\"), or \"auto:ip\". NOTE on IATA codes: WeatherAPI resolves them to that airport's CITY, not the airport's own weather station — for the actual airport-station reading (can differ by several degrees) use the aviation-weather pack's metar tool with the airport's ICAO code instead."
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "dt": "2026-06-21",
+    "q": "Reykjavik"
+  }
+]
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context by enumerating the specific data fields returned and including an example invocation. This goes beyond what annotations alone convey, though it does not address rate limits or error behavior.

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

Conciseness5/5

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

The description is two sentences: one functional summary and one example. It is front-loaded with the key purpose and wastes no words. Every sentence earns its place.

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

Completeness4/5

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

For a simple lookup tool with three parameters, good annotations, and no output schema, the description is complete enough. It tells the user exactly what data will be returned and gives a usable example. Minor gaps like default date behavior are already covered by the schema, not the description.

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

Parameters3/5

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 includes a usage example showing q and dt, which reinforces the schema. However, the schema already thoroughly explains all three parameters, including the nuanced IATA code note for q. The description does not add meaning beyond the schema.

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

Purpose5/5

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

The description uses a specific verb ('Get') and clearly identifies the resource ('astronomy data') along with the key output fields (sunrise, sunset, moonrise, moonset, moon phase, moon illumination). This distinguishes it from sibling tools like current, forecast, and marine, which cover other weather domains.

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

Usage Guidelines4/5

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

The description states exactly when to use the tool: to retrieve astronomy data for a given location and date. It provides a concrete example with parameters, making the context clear. It does not explicitly mention when not to use it or name alternative tools, but the purpose is distinct enough that no exclusions are needed.

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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TDQS

A3.8/5.0
Disambiguation2/5

Several tools have near-identical purposes: ask_pipeworx and ask_pipeworx_beta are explicitly described as functionally identical, and six Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread, polymarket_edge_tracker) overlap heavily in discovery, edge, and arbitrage roles. Company-research tools (entity_profile, compare_entities, recent_changes) also blur boundaries, making misselection likely.

Naming Consistency3/5

All names use lowercase snake_case with underscores, which is a consistent base convention. However, the lexical pattern varies: bare single words (current, forecast, remember, forget) coexist with verb_noun compounds (resolve_entity, validate_claim) and noun compounds (entity_profile, polymarket_edges). The lack of a uniform verb_noun structure makes the set less predictable, though still readable.

Tool Count1/5

35 tools is well into the 'too many' range, and the server's name promises weather while only 4 of 35 tools (current, forecast, astronomy, marine) are weather-related — an extreme mismatch between the declared purpose and the actual surface. The remaining 31 tools form a general data/prediction-market platform that would be better served under a different server name.

Completeness4/5

Judged by its actual (non-weather) domain, the set is quite complete: generic routed lookup, grounded answer mode, deep research, entity resolution/profile/comparison, claim validation, subscriptions, memory, discovery, and feedback are all present. The weather subset covers current conditions, forecasts, marine, and astronomy, though it lacks historical weather and alert endpoints — a minor gap.

Resources