Skip to main content
Glama

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 400 h/year, acquisition curve, with costModelVersion. Same numbers as the Jet Tracker model page and as jt_compute_tco assumptions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesSlug do catálogo (ex: embraer-phenom-300, cessna-citation-cj3).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoMachine-readable error code (INTERNAL, TIMEOUT, INVALID_ARGUMENT, NOT_FOUND, TOOL_FAILED, ACCOUNT_KEY_REQUIRED).
_metaNo
errorNo
foundNo
gatedNo
requestIdNo
retryableNo
quota_exceededNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed8 schema fields changed
    • 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"
      +}
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint, lowering the bar. The description adds useful behavioral context beyond those hints: how the model is resolved (slug, family slug, prefix variations, name) via model.matchedBy, and that the returned numbers are canonical and consistent with another tool. No contradictions 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 a single dense sentence but every clause adds relevant detail: resolution options, cost components, costModelVersion, and consistency with other sources. It is front-loaded with the core resource and slightly run-on, but not bloated.

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?

Given the output schema exists and annotations cover safety and idempotence, the description is largely complete: it explains the input flexibility, the resolution mechanism, and the cost model outputs. It could have been slightly more explicit about the relationship to jt_model_search, but nothing essential to calling the tool is missing.

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

Parameters5/5

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

The schema covers the single slug parameter, and the description adds substantial meaning beyond it: the slug may be a catalog slug, family slug, slug with or without manufacturer prefix, or a name, and model.matchedBy indicates resolution. This directly helps an agent construct the parameter correctly.

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 clearly defines the resource as model technical specs plus a canonical operating cost engine, enumerating the exact cost outputs (variable cost per hour, fixed cost per year, total per hour at 400 h/year, acquisition curve, costModelVersion). It also differentiates from the sibling jt_compute_tco by explicitly stating these are the same numbers and that this is the canonical engine.

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 gives clear context: this is the canonical source for model specs and operating cost, and its numbers match the Jet Tracker model page and jt_compute_tco assumptions. It does not explicitly say when not to use it or name alternatives like jt_model_search, so it lacks explicit exclusions.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources