Jet Tracker

Where an aircraft actually sleeps

jt_aircraft_base

Read-onlyIdempotent

Overnight ranking of one registration over N days (default 365): aerodromes where the aircraft slept: nights = midnights elapsed between each arrival and the next departure from the same aerodrome (an ongoing stay counts up to now, ongoing=true), overnightEvents = stays that crossed at least one midnight, plus share and last arrival, side by side with the inferred hub (hubIcao) and the owner city at the Receita. inferredBase is the top of the ranking and confidence (high/medium/low/none) depends on how many nights were tracked. Answers "where is this aircraft based" honestly: the three facts can disagree.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No	Window in days. Default 365.
`registration`	Yes	Brazilian registration (PP-LMH).

Output Schema

TableJSON Schema

Name	Required	Description
`code`	No	Machine-readable error code (INTERNAL, TIMEOUT, INVALID_ARGUMENT, NOT_FOUND, TOOL_FAILED, ACCOUNT_KEY_REQUIRED).
`_meta`	No
`error`	No
`found`	No
`gated`	No
`requestId`	No
`retryable`	No
`quota_exceeded`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed8 schema fields changedSep 16, 2026

addedOutput schema / properties / _meta / properties / asOf / description
```
Added value: +"Alias of sourceUpdatedAt (kept for compatibility)."
```

addedOutput schema / properties / _meta / properties / generatedAt

Added value: +{
+  "description": "When this response was produced (ISO 8601).",
+  "type": "string"
+}

addedOutput schema / properties / _meta / properties / observedAt

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "description": "Last event actually observed in the data returned (last flight, last arrival, last listing sighting)."
+}

addedOutput schema / properties / _meta / properties / sourceUpdatedAt

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "description": "Last sync of the underlying source (RAB snapshot, registry import, listing scan). Never in the future."
+}

addedOutput schema / properties / _meta / properties / validUntil

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "description": "Expiry of the fact returned, when it has one (CVA validity, period end)."
+}

addedOutput schema / properties / code

Added value: +{
+  "description": "Machine-readable error code (INTERNAL, TIMEOUT, INVALID_ARGUMENT, NOT_FOUND, TOOL_FAILED, ACCOUNT_KEY_REQUIRED).",
+  "type": "string"
+}

addedOutput schema / properties / requestId
```
Added value: +{
+  "type": "string"
+}
```
addedOutput schema / properties / retryable
```
Added value: +{
+  "type": "boolean"
+}
```

First observedSep 11, 2026

TDQS

A4.2/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the description adds genuine algorithmic context: the midnight-counting definition, the ongoing-stay edge case (ongoing=true, counts up to now), the overnightEvents threshold, and the confidence heuristic scaled by nights tracked. The 'three facts can disagree' disclosure is distinctive and prevents an agent from over-trusting inferredBase.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

Every named term earns its place — each is an output field the agent will encounter — and the purpose is front-loaded. However, it is one dense run-on paragraph with multiple nested parentheticals, which hurts readability; splitting the field definitions into separate sentences or lines would make it substantially clearer.

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?

An output schema exists, so return-value format is already documented elsewhere. The description fills in what the schema cannot: the counting algorithm, the ongoing-stay edge case, confidence semantics, and the honesty caveat about disagreeing facts. Minor terms like 'share' are mentioned without elaboration, relying on the output schema, which is acceptable.

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

Parameters3/5

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

Schema description coverage is 100%: registration already has format and length bounds, days already has range and default. The description echoes 'default 365' and 'one registration' but contributes no new meaning beyond the schema, so the baseline of 3 applies.

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 states a specific deliverable — 'Overnight ranking of one registration over N days' — and enumerates the output facts (nights, overnightEvents, hubIcao, owner city, inferredBase, confidence). The 'where is this aircraft based' framing clearly separates it from movement-focused siblings like jt_aircraft_flights and jt_aircraft_history.

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 explicitly declares the question it answers ('Answers "where is this aircraft based"') and even warns that the three facts can disagree, giving an agent clear context for when to invoke it. However, no sibling alternative is named and no when-not-to-use exclusion is stated, so it falls short of a 5.

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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