Jet Tracker

Model specs and operating cost

jt_model_specs

Read-onlyIdempotent

Technical specs of a catalog model (slug, family slug, slug with or without manufacturer prefix, or name; model.matchedBy says how it was resolved) plus the canonical operating cost engine: variable cost per hour, fixed cost per year, total per hour at standard_hours_per_year (200 h/year), acquisition curve, with costModelVersion. Same numbers as the Jet Tracker model page and as jt_compute_tco assumptions.

Input Schema

Name	Required	Description	Default
`slug`	Yes	Slug do catálogo (ex: embraer-phenom-300, cessna-citation-cj3).

Output 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

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/non-open-world, so the bar is lower. The description adds genuinely new behavioral context: fuzzy slug resolution via model.matchedBy, the costModelVersion stamp, and the standard_hours_per_year=200 default that drives the total-per-hour figure. It does not mention rate limits or caching, hence not a 5.

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?

Two front-loaded sentences with no filler; the payload is described first, the resolution semantics second. The parenthetical lists are dense but each item carries information. Slightly over-packed for a one-parameter tool.

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 values need not be enumerated, yet the description names the key fields (variable cost/hour, fixed cost/year, total/hour, acquisition curve, costModelVersion) and flags that the numbers match the model page and jt_compute_tco — enough for an agent to trust and reuse the output. Nothing critical is missing for a single-param read tool.

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% for the single slug parameter, so baseline is 3, but the description goes beyond the schema by enumerating accepted forms (bare slug, family slug, slug with or without manufacturer prefix, or model name) and by naming the resolution-echo field. That is real added meaning the schema alone does not convey.

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?

States a specific resource (catalog model technical specs) plus a second, clearly bounded payload (the canonical operating cost engine), so an agent knows exactly what comes back. The phrase 'canonical operating cost engine' and the explicit reference to jt_compute_tco assumptions distinguish it from the cost-computation sibling.

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 implied: this is the per-model lookup that yields specs and standard cost figures, and the mention of jt_compute_tco signals a relationship. But there is no explicit when-to-use/when-not statement and no routing versus jt_model_search (discovery) or jt_compute_tco (custom TCO runs).

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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