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.

Changed1 schema field changedSep 28, 2026

changedOutput schema / properties / _meta / required

Previous value: -[
-  "tool",
-  "tier",
-  "source",
-  "asOf",
-  "gated",
-  "via"
-]New value: +[
+  "tool",
+  "source",
+  "asOf",
+  "gated",
+  "via"
+]

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

A4/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial context beyond that: the two counting universes (registry vs live), what each includes and excludes (cancelled registrations; operational + mark reservation + suspended), serial-level dedup, the as_of snapshot date, and the source URL for verification.

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?

Front-loaded with the headline metric and efficient, but the long parenthetical run-ons and stacked clauses take effort to parse; a small amount of restructuring would improve it without losing content.

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?

With an output schema present, return fields need not be explained, yet the description still labels the key metrics, which makes the response interpretable. The remaining gap is the absent routing guidance against the sibling stats/search tools.

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 100% (the slug description is minimal), and the description adds real meaning: the slug may be an alias, resolves to a whole family, and model.matchedBy reports how resolution happened. That goes beyond the schema's bare 'Slug do modelo.'

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?

It states a specific verb+resource: Brazilian fleet counts for a catalog model drawn from the RAB, with named metrics (registryTotal, alive, airframes). The 'Brazilian' qualifier implicitly separates it from jt_global_fleet_stats, but the sibling is never named, so differentiation requires inference.

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?

Usage is only implied: it returns a count for a model, so an agent can guess it is the aggregate-stat call versus jt_fleet_search or jt_aircraft_lookup. It never states when to prefer this over jt_global_fleet_stats, nor any prerequisite about resolving a slug first.

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

All Jet Tracker tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?