Route & shipment brief (bundle) — One call: driving distance and time between two US points (addresses or lat,lon), an estimated fuel cost, and weather + active alerts at both ends, fused into a go/caution verdict. JSON. Price: $0.05 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| mpg | No | optional vehicle MPG (default 25) | |
| dest | Yes | destination address or 'lat,lon' | |
| origin | Yes | origin address or '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 cover the safety profile (readOnlyHint=true, destructiveHint=false), so the bar for added behavior is lower. The description goes beyond them by disclosing a concrete cost ($0.05 USDC via x402), a geographic constraint (US points only), the output format (JSON), and behavioral scope details — that weather is fetched at both endpoints and results are fused into a go/caution verdict. No contradiction with annotations; the only omissions are peripheral (rate limits, data freshness).
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 sentences with zero filler. The purpose and composite scope are front-loaded in the first clause, the enumerated components follow in a tight list, and practical details (format, price) close it out. Every word earns its place — notably, the title annotation is fully redundant with the description, so there is no duplication to cut.
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 carries the burden of conveying what comes back, and it covers all the essentials: distance, time, fuel cost, weather, active alerts, the fused verdict, and JSON format. Input format and defaults are delegated to the 100%-covered schema. Minor gaps remain — units for distance/time are unstated, and it doesn't clarify whether one route or alternatives are returned — but for a moderately complex bundle tool, the coverage is largely adequate.
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%, setting a baseline of 3, but the description contributes real semantic value beyond the schema: it reveals why mpg matters (it feeds the estimated fuel cost — the schema merely labels it 'optional vehicle MPG'), and it adds the US-only scope that constrains how origin and dest values should be interpreted. This transforms the parameters from syntax into an economic and geographic model.
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 opens with a concrete composite deliverable ('Route & shipment brief (bundle)') and enumerates exactly what one call produces: driving distance and time, estimated fuel cost, weather and active alerts at both ends, fused into a go/caution verdict. The specific enumeration of components ('bundle', 'One call') distinguishes it unmistakably from single-purpose siblings like weather_alerts, geo_geocode, and vehicle_fuel_economy, whose scopes it subsumes.
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 phrase 'One call' and 'bundle' imply this is the consolidated alternative to making several separate single-purpose calls, and the component list communicates its coverage. However, it never explicitly names alternatives such as weather_alerts, weather_current, geo_geocode, or vehicle_fuel_economy, nor states when an agent should prefer those instead (e.g., when only weather or only a geocode is needed). The usage context is implied, not prescribed.
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.