Jet Tracker

Brazilian fleet stats for a model

jt_fleet_stats

Read-onlyIdempotent

Brazilian fleet of a catalog model (slug or alias, whole family; model.matchedBy says how it resolved) from the RAB. Two separate rulers: registryTotal (= total) counts REGISTRATIONS in every status, cancelled included (history); alive counts the LIVE fleet (operational + mark reservation + suspended) and is the headline. airframes and aliveAirframes deduplicate by serial (physical aircraft). byRbac is the split over the REGISTRY universe and byRbacAlive over the LIVE universe. Also as_of (RAB snapshot date), source.url (page where a human checks the records) and scope (the exact cut). Live count, not a survey.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes	Slug do modelo.

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

A4.6/5.0

Behavior5/5

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

The description goes far beyond the annotations (read-only, idempotent) by explaining the semantics of the two rulers (registryTotal vs alive), deduplication by serial, and the meaning of byRbac splits and as_of/source/scope. It also clarifies 'Live count, not a survey,' adding behavioral nuance. No contradiction with 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?

The description is dense but well-structured, starting with the purpose, then explaining the key metrics and fields. It is informative without redundancy, though slightly lengthy; given the complexity of the output, it's appropriate.

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

Completeness5/5

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

With an output schema present, the description focuses on semantics. It covers all major aspects: the two counts, deduplication, splits, and metadata fields. It doesn't mention error conditions, but for a read-only stats tool with one parameter, this is sufficient. Very complete.

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?

The schema only says 'Slug do modelo.' The description adds that the slug can be an alias, refers to the whole family, and that model.matchedBy indicates resolution. This adds meaning beyond the schema, exceeding the baseline of 3.

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 resource: Brazilian fleet stats for a catalog model, with the verb implied (fetches/stats). It distinguishes itself from the global sibling by 'Brazilian' and clarifies the resolution mechanism (model.matchedBy) and output fields, making the purpose unmistakable.

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?

Usage context is clear—this is for Brazilian fleet stats—and the presence of jt_global_fleet_stats implies a distinction. However, it doesn't explicitly state when to use this vs alternatives or provide exclusions, relying on the 'Brazilian' qualifier and sibling naming.

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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