Property underwriting (bundle) — One call: STANDARD/SURCHARGE/REFER hazard-underwriting posture for a US address, fusing FEMA flood zone, USGS seismic history, and active NWS weather alerts. Price: $0.40 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | latitude | |
| lon | Yes | longitude | |
| address | Yes | US property address (or use lat+lon) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, non-destructive, open-world behavior, so the description does not need to restate that. It adds valuable behavioral context: the output posture values, the specific fused data sources, geographic scope, and a $0.40 USDC price. No contradiction with readOnlyHint or openWorldHint.
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 tight sentences deliver the purpose, output, data sources, geography, and pricing with no filler. The key outcome is front-loaded before the supporting detail.
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 no output schema, the description still explains what the agent will get back (STANDARD/SURCHARGE/REFER), what data is combined, and what geographic scope applies. Combined with read-only annotations and full schema parameter documentation, the agent has enough to select and invoke the tool correctly.
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 coverage is 100%, so the baseline is 3. The description does not add per-parameter detail beyond reinforcing the US-address input; address, lat, and lon are already documented in the schema. It does not clarify the slight tension between the required-address schema and the address's '(or use lat+lon)' note, but that is a schema-level issue.
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 a specific verb-resource pair: it returns a STANDARD/SURCHARGE/REFER hazard-underwriting posture for a US property address. The 'bundle' framing and the fused data sources distinguish it from similar siblings like realestate_property_report and realestate_site_risk.
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 makes the use case clear: call this when you need a consolidated hazard-underwriting posture across flood, seismic, and weather data. It does not explicitly name alternatives or say when not to use it, but 'One call' and 'bundle' imply it should be preferred over separately querying geo/weather tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.