Windsock

Impute missing aircraft specs

impute_aircraft_specs

ML fill-in for missing airframe, engine, and condition fields (SMOH, AFTT, interior/exterior quality, etc.) before a valuation. Identify the aircraft by registration or make_model_id; any fields you supply (including known hours) are preserved and used to estimate the rest. field_sources says which values were provided, taken from the tail's registry/listing data, or imputed. Quality scores use a 1–10 scale on input (a literal 1 reads as like-new, not the worst grade — send 0.1 for the worst) and are RETURNED on the 0–1 scale, where 0.7 means grade 7. Pass the returned values straight to value_aircraft, which accepts either scale.

Input Schema

TableJSON Schema

Name	Required	Description
`aftt`	No	Airframe total time (hours), if known.
`year`	No
`smoh_1`	No	Hours since major overhaul, engine 1, if known.
`smoh_2`	No	Hours since major overhaul, engine 2, if known.
`registration`	No
`make_model_id`	No
`exterior_quality`	No	Exterior condition, 1–10 (10 = like-new). Caution: values <= 1 are read on the legacy 0–1 scale, so a literal 1 means like-new, NOT the worst grade — send 0.1 for the worst.
`interior_quality`	No	Interior condition, 1–10 (10 = like-new). Caution: values <= 1 are read on the legacy 0–1 scale, so a literal 1 means like-new, NOT the worst grade — send 0.1 for the worst.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes
`meta`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 20, 2026

addedInput schema / properties / aftt

Added value: +{
+  "description": "Airframe total time (hours), if known.",
+  "type": "number"
+}

addedInput schema / properties / smoh_1

Added value: +{
+  "description": "Hours since major overhaul, engine 1, if known.",
+  "type": "number"
+}

addedInput schema / properties / smoh_2

Added value: +{
+  "description": "Hours since major overhaul, engine 2, if known.",
+  "type": "number"
+}

addedOutput schema / properties / data / properties / field_sources

Added value: +{
+  "additionalProperties": {
+    "type": [
+      "string",
+      "null"
+    ]
+  },
+  "description": "Per field: provided (you sent it), registry (this tail's registry/listing data), or imputed (the model's estimate).",
+  "type": [
+    "object",
+    "null"
+  ]
+}

First observedSep 11, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations only give the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true), so the description usefully adds that supplied fields are preserved, that field_sources encodes provenance (provided/registry/imputed), and the input vs return quality scales. It stops short of explaining auth needs or persistence/side effects, which matters given readOnlyHint=false.

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-loads the core purpose and then layers provenance and scale warnings in a compact sequence with no obvious filler. It is dense but every sentence carries actionable information.

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 structure is already documented, and the description focuses on the non-obvious semantics (field_sources, scale mismatch, chaining to value_aircraft). The one gap is the unresolved relationship to infer_aircraft_specs, which the description never clarifies.

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?

With schema coverage at 63%, the description compensates by explaining the identity parameters and the tricky 1-10 input vs 0-1 return scale for quality fields, which the schema only partly covers. It does not touch on the year parameter, so it adds solid but not full value over the schema.

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?

States a specific verb (ML fill-in) and resource (missing airframe, engine, and condition fields) with concrete examples (SMOH, AFTT, quality). However, it never differentiates from the near-identically named sibling infer_aircraft_specs, leaving an agent to guess which imputation/inference tool applies.

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?

Gives clear context ('before a valuation') and an explicit downstream route ('Pass the returned values straight to value_aircraft, which accepts either scale'). It also explains how to identify the aircraft (registration or make_model_id), but offers no when-not guidance and does not name a sibling alternative.

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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