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weather_current

Read-only

US current conditions (NWS) — Latest observed conditions near a US coordinate: temperature, wind, humidity, visibility, pressure from the nearest weather station. Source: National Weather Service. JSON. Price: $0.003 USDC (Base, via x402).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYeslatitude
lonYeslongitude

Schema Changelog

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

  1. 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=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: data comes from the National Weather Service, returns JSON, uses the nearest weather station, is limited to US coordinates, and has a stated price. This goes beyond the annotations and helps the agent understand what to expect.

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 compact and front-loaded: it opens with the tool's purpose, then lists the specific data fields, source, format, and cost. Every sentence adds information without fluff. The one-sentence structure is dense but easily parseable.

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?

With only two simple string parameters and no output schema, the description is largely complete: it states the location scope, the data fields returned, the source, and the output format (JSON). It does not specify units (e.g., Fahrenheit vs Celsius) or exact JSON structure, but these are not critical for invoking the tool. Overall, it gives an agent enough to call it correctly and interpret the result.

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%: both lat and lon are described as 'latitude' and 'longitude', so the schema carries the basic meaning. The description adds a small but meaningful constraint that the coordinates must be in the US ('near a US coordinate'), but it does not provide format details such as decimal degrees or range validation. This is a marginal improvement over the schema, so a baseline score of 3 is appropriate.

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 clearly identifies what the tool does: 'Latest observed conditions near a US coordinate' with explicit fields (temperature, wind, humidity, visibility, pressure). This distinguishes it from sibling weather tools like weather_forecast and weather_hourly by focusing on current observed conditions. The verb 'current' and resource 'US current conditions' are specific and unambiguous.

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 gives clear context: it is for current, observed conditions rather than forecasts or alerts, which is reinforced by the title. It does not explicitly name alternatives or state exclusions, but the 'current conditions' phrasing makes the appropriate usage obvious among the weather sibling tools. It could be improved by explicitly saying 'for forecasts use weather_forecast,' but that is not necessary given the clarity.

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

A3.6/5.0
Disambiguation2/5

Many tools are clearly separated by prefix and data source, but several bundled products overlap heavily: vehicle_deal_check vs vehicle_report, realestate_property_report vs realestate_site_risk, finance_company_360 vs finance_health_scan, and domain_due_diligence vs email_domain_check/business_vet. An agent would frequently struggle to pick the correct premium bundle.

Naming Consistency4/5

Tool names overwhelmingly follow a consistent snake_case category-prefix pattern like weather_, crypto_, vehicle_, finance_, and geo_. Minor deviations such as bare names (domain, ip) and noun-verb forms (dns_lookup, url_check) are easy to learn and don't create real confusion.

Tool Count2/5

50 tools is far beyond the typical well-scoped 3–15 range and will require heavy filtering to navigate. The broad multi-domain data marketplace partially justifies the size, but it would be more coherent split into per-domain servers or consolidated further.

Completeness4/5

For a read-only data/diligence marketplace, the surface is quite comprehensive: weather, vehicle, crypto, SEC/finance, domain/email, sanctions, and geo workflows all have core operations plus fused verdict bundles. Minor gaps exist—such as a simple crypto price lookup or vehicle market value—but agents can usually work around them.

Resources