kanari wildfires

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.

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.

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.

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.

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.

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.

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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral context: automatic geographic matching, a 72-hour window, inclusion of positive and negative gaps, median aggregation, and source article links. This meaningfully clarifies what the tool does beyond the annotation and does not contradict it.

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?

The description is compact, front-loaded, and every sentence earns its place. It states the core computation, the aggregation method, important exclusions, and output availability in a few lines without repetition.

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?

For a simple read-only tool with one optional parameter and no output schema, the description covers the key semantics: time window, positive/negative gaps, median aggregation, caveats, and source links. It does not describe exact return formatting, but that is a minor gap for this tool.

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 description coverage is 0%, so the description should compensate for parameter meaning, but it never mentions the 'limit' parameter or how it affects results. The schema does define min, max, and default, which gives some baseline understanding, but the description adds no value for the parameter.

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 title 'Measured lead over press coverage' plus the description makes the tool's purpose clear: it computes median time gaps between satellite and press timestamps over 72 hours. It does not explicitly name sibling tools, but the caveat 'Not kanari alert publication time, not proof of distinct fires or a lead over emergency services' helps an agent understand the intended scope.

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 provides no explicit guidance on when to choose this tool over alternatives like fire_archive_search or wildfire_stats. It explains what the computation is and what it is not, but does not state selection conditions or exclusions relative to siblings.

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

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

Annotations already signal read-only and open-world behavior, and the description adds useful context beyond those hints: the archive starts on 2026-08-03, only significant wildfires are included, and results link to a permanent page URL. It does not discuss pagination or result ordering details, but the annotation coverage lowers the burden on the description.

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?

The description is compact and front-loaded: it opens with the core search capability, then lists filter dimensions, then gives concrete query examples. Every sentence adds value and nothing is redundant with the schema.

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?

For a search tool with nine parameters, no output schema, and read-only/open-world annotations, the description gives enough orientation: filter types, output URL behavior, and example queries. Minor gaps remain around the return payload shape and the exact role of limit/order, but the overall definition is functional and not missing critical information.

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 description coverage is only 33%, but the description helps compensate by mapping user intent to parameters: 'ISO-2 country' clarifies country, 'date range or month' covers from/to and month, 'minimum detections or power' maps to min_detections and min_frp_mw, and 'status' covers the status enum. It does not explain limit or order, but those have adequate schema-level defaults and enums.

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 states a specific verb ('Search'), a clear resource ('kanari's archive of significant wildfires'), and the key filter dimensions. It distinguishes itself from a live-fire tool by emphasizing 'archive' and the explicit start date, and the example queries make the tool's role immediately identifiable.

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 gives concrete example queries for when to use this tool: historical fire lookups by country/month, biggest fires, and checking whether a fire is still active. It does not explicitly contrast it with sibling tools like active_fires or fire_details, but the use cases make the intended context reasonably clear.

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

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

The readOnly annotation covers the safety profile, so the description only needs to add contextual depth. It lists the record components (timeline, detections per sensor, peak power, aircraft observed, etc.), which goes beyond annotation and tells the agent 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.

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

A single dense sentence that front-loads the core purpose, then provides source context and a colon-separated list of contents. Every clause earns its place; no wasted words.

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?

No output schema exists, so the description compensates by enumerating the expected record components. It is sufficiently complete for a one-parameter read-only fetch, though it does not address potential 'not found' cases or output structure details.

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 description coverage is 0%, so the description must carry the load for the sole parameter. It explains what a slug is and where to obtain it (fire_archive_search or kanari.io URL), though it does not mention the min/max length constraints or error behavior for invalid slugs.

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?

Clearly describes a full record retrieval for archived fires, identified by slug, and lists exact contents. The 'archived' qualifier distinguishes it from active_fires, and the reference to fire_archive_search distinguishes it from the search tool.

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?

States that the slug comes from fire_archive_search or a kanari.io URL, strongly implying when to use this tool: after a slug is obtained. The archived-fire framing gives context, though it does not explicitly exclude active_fires or say when not to use it.

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

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

Annotations provide readOnlyHint=true and openWorldHint=true, and the description goes beyond these with useful caveats: data is near real-time, coverage and identification are incomplete, and some helicopters operate at night. These are behavioral limitations an agent must calibrate around, adding value beyond the annotations. It stops short of fully detailing update cadence or rate limits, but for an open-data, read-only service this is reasonable.

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?

The description is compact and front-loaded: the main capability begins the first sentence, the aircraft examples are disambiguating, and the caveats are appended in a short final clause. There is no filler or nesting; every sentence earns its place.

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?

For a two-optional-parameter read-only data stream, this is largely complete: the data domain, the geographic extent, the filter, and data-quality caveats are all present. The absence of an output schema is partly covered by the phrase 'ADS-B positions', which implies lat/lon and call sign/ID fields, but the behavior of `limit` in determining returned records is left unstated.

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?

The schema has 0% description coverage, so the description is responsible for parameter semantics. It does document `country` as an optional ISO-2 filter on the country of registration, which is meaningful. However, it never explains what `limit` controls or why it caps at 300, so an agent still cannot fully predict how paging or result trimming works.

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: returns near real-time ADS-B positions of firefighting aircraft worldwide, with explicit examples of aircraft types. It differentiates itself from the fire-oriented siblings (active_fires, fire_archive_search, etc.) by focusing on aircraft tracking instead of scene or event data.

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?

No explicit when-to-use or when-not-to-use information exists. The description only mentions the optional ISO-2 country filter, which is a parameter instruction, not tool-selection guidance. It does not name alternative tools or conditions that would make a sibling more appropriate.

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

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

Annotations already establish readOnlyHint=true and openWorldHint=true. The description adds useful context beyond those annotations: the archive source, supported time windows, the 'all since 2026-08-03' bound, and the ready-to-cite sentence with source attribution. It discloses the main behavioral characteristics without contradicting 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.

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

The description is a single dense sentence that front-loads the core purpose and packs the behavior into a compact list. It has no filler, though the long comma-separated enumeration could be slightly harder to parse quickly.

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 present, the description appropriately enumerates the returned items: counts, peak power, daily series, affected regions, and biggest fires with URLs, plus the citation sentence. It omits the default period of 7d and the precise month-parameter condition, but those are available in the schema.

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 description coverage is only 33%, so the description compensates by spelling out period values, the ISO-2 country form, and the worldwide-or-single-country scope. It only indirectly conveys the month parameter's required-when-month relationship and format, which are left to the schema.

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 the tool returns aggregated wildfire statistics from kanari's archive, with explicit period and geography options, and enumerates the metrics included. This distinguishes it from sibling tools like active_fires or fire_details by emphasizing aggregate, citable figures.

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 implies use when aggregated statistics or citable figures are needed, and it lists valid period and country inputs. However, it does not explicitly contrast with sibling tools or state when not to use this tool, leaving the decision rule to inference.

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