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Glama

DataQuoll

Find incidents near a location

nearby_incidents
Read-only

Returns incidents within a radius (km) of a given lat/lng coordinate, sorted by distance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude
lngYesLongitude
limitNo
stateNo
agencyNo
radiusYesRadius in kilometres (max 500)
statusNoComma-separated incident statuses (active, contained, controlled, safe, completed). Defaults to all.
urgencyNo
severityNo
certaintyNo
eventTypeNo
warningLevelNo
eventCategoryNo
include_retractedNoSet true to include retracted incidents. Default false; retracted incidents are hidden, matching /incidents.

Schema Changelog

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

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

The readOnlyHint annotation already establishes that this is a safe read operation, and the description adds the radius-filter and distance-sort behavior. However, it does not disclose edge-case behavior such as result limits, default filtering, or how ties in distance are handled, though nothing it states contradicts the annotations.

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?

A single front-loaded sentence with zero filler, putting the spatial scope first and the sort detail second. It is efficiently written, but it is lean to the point of under-specification given the tool's 14-parameter surface, so it does not earn a 5.

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

Completeness2/5

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

With 14 parameters, no output schema, and no enums, the one-sentence description is insufficient. It never mentions the extensive filter capabilities, the default behaviors (e.g., status defaults to all, include_retracted defaults to false), or what the response structure looks like, leaving the agent to discover these from the sparse schema.

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

Parameters2/5

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

Schema description coverage is only 36%, so the description carries a heavy burden that it does not meet. It only clarifies lat/lng/radius (and even repeats the 'km' detail that the radius schema already provides), while the 11 remaining parameters — state, status, urgency, severity, certainty, eventType, warningLevel, eventCategory, limit, and include_retracted — go unexplained in both the schema and the description.

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 names a specific verb ('Returns'), a resource (incidents), a unique spatial scope (within a radius of a lat/lng coordinate), and the sort order (by distance). This clearly identifies the tool's function, but it does not explicitly differentiate it from overlapping siblings such as list_incidents or the point-based declaration tools.

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?

The title 'Find incidents near a location' and the description's spatial framing imply when to use this tool, but there is no explicit guidance on when to choose it over list_incidents, nor any exclusions or alternative tool names. The agent must infer that this is the location-scoped variant.

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

A3.9/5.0
Disambiguation4/5

Most tools target a distinct resource and action, and the descriptions are detailed enough to separate declaration lookups, hazard history, incidents, events, and gauges. A couple of pairs could still be confused at first glance, such as declarations_by_point vs hazard_history_by_point or list_events vs list_incidents, but the descriptions resolve the boundaries.

Naming Consistency4/5

The naming largely follows a clear get_/list_ convention for single resources versus collections, with lookup-style names like declarations_by_point and declarations_by_postcode. Minor deviations such as incident_snapshot, nearby_incidents, and the singular declaration_by_agrn prevent a perfect score.

Tool Count4/5

19 tools is on the heavier side, but the count is justified by the broad domain covering current incidents, historical incidents, clustered events, declarations, river gauges, hazard history, schema discovery, attribution, and feed health. Each tool appears to earn its place, though the set is larger than the ideal 3-15 range for a tightly scoped server.

Completeness5/5

The surface is remarkably complete for a read-only emergency/disaster data API: current and historical incidents, event clustering, incident snapshots, nearby queries, declaration lookups by multiple keys, gauge readings and summaries, hazard history, schema enums, attribution, and source feed status are all covered. There are no obvious dead ends or missing core operations for the stated domain.

Resources