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kanari wildfires

by io.github.vria-consulting

Active wildfires right now

active_fires
Read-only

Fire clusters detected by satellite over the last N hours (default 24), worldwide or filtered by ISO-2 country, bounding box, or a point with a radius. Returns up to limit clusters ranked by relevance (corroborated and recent first). Use for 'is there a fire near X right now' or 'wildfires in today'. Each cluster: position, first/last satellite pass (UTC), detections per sensor, peak fire radiative power (MW), confidence (possible | probable | corrobore = cross-checked with witnesses).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxNo[minLon, minLat, maxLon, maxLat]
nearNoOnly clusters within radiusKm of this point
hoursNoTime window in hours: 6, 12, 24, 48 or 72
limitNo
countryNoISO-2 country code, e.g. FR, US, BR

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

The readOnlyHint and openWorldHint annotations are reinforced and extended by the description. It discloses ranking behavior, time-window defaults, filter semantics, and the meaning of confidence values such as 'corrobore = cross-checked with witnesses', adding real behavioral detail beyond 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.

Conciseness5/5

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

The description is front-loaded with the core behavior, then filters, then usage examples, then result fields. Every sentence carries useful information without repetition or filler.

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?

The tool has five parameters and no output schema, but the description covers the main calling decisions: time window, spatial filters, result count, ordering, and returned cluster fields. Minor ambiguities like whether filters can be combined and the exact shape of 'position' remain, but these are mostly covered by the input schema.

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

Parameters4/5

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

Schema coverage is high at 80%, so the schema already documents most parameters. The description adds value by explaining the ranking relevance for `limit`, clarifying the spatial filter options as a group, and stating the default hours window, which helps the agent choose parameters more confidently.

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 names a specific resource and action: satellite-detected fire clusters over a time window, with explicit filters and a ranked list of results. It also clarifies the scope ('active... right now') and the returned cluster attributes, distinguishing it from archive or stats siblings.

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 explicit use-case templates: 'is there a fire near X right now' and 'wildfires in <country> today'. It does not explicitly name alternatives or say when not to use this tool, but the active-vs-archive framing makes the intended context clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All kanari wildfires toolsInspect
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TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct aspect: current fire clusters, media-lead case studies, archive search, fire details, aircraft positions, and aggregate statistics. No two tools appear to serve the same purpose, so an agent can reliably select the right one.

Naming Consistency4/5

All tool names use lowercase snake_case and follow a consistent pattern of descriptive nouns plus an action or modifier (e.g., active_fires, fire_archive_search, wildfire_stats). Minor deviation like 'earliness_cases' uses an adjective, but the style is uniform and predictable.

Tool Count5/5

With 6 tools, the surface is well-scoped for a wildfire data provider. Each tool covers a discrete capability without redundancy, and the count is comfortably within the ideal 3-15 range.

Completeness5/5

The tool set covers current detection, historical search, detailed per-fire records, media lead evidence, active aircraft, and summary statistics. For a read-only wildfire information service, this is a complete lifecycle surface with no obvious dead ends.

Resources