Microburbs Australian Property Data

Property · All valuation outputs — bundle

properties_valuation_all

Read-onlyIdempotent

Our automated valuation for one property: the point estimate, the 80% range around it, and a 0-100 confidence score derived from how wide that range is.

Today this bundles the single /valuation/avm call, so it costs the same; it exists so an agent can ask for "everything valuation" without tracking which valuation endpoints exist. Agent quoting behaviour, land values, negative gearing and the value series are separate calls.

Price: 10¢ per call.

Input Schema

Name	Required	Description	Default
`gnaf_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 15, 2026

changedOutput schema / (root)

Previous value: -{
-  "properties": {
-    "available": {
-      "anyOf": [
-        {
-          "type": "boolean"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "description": "`false` on no-data responses. Omitted on success — branch on `data !== null` if you want a single discriminator.",
-      "title": "Available"
-    },
-    "data": {
-      "anyOf": [
-        {
-          "description": "All valuation outputs in one call. Today: just the AVM (which\nnow includes confidence_score inline). Kept as a bundle so future\nvaluation outputs — rental AVM, off-market signals — slot in\nwithout a new endpoint.",
-          "properties": {
-            "avm": {
-              "anyOf": [
-                {
-                  "description": "Automated valuation: point estimate + 80% prediction interval +\nconfidence score derived from the interval width.",
-                  "example": {
-                    "predicted_price": 876651,
-                    "predicted_price_high": 1183479,
-                    "predicted_price_low": 569823,
-                    "prediction_date": "2026-04-20"
-                  },
-                  "properties": {
-                    "confidence_score": {
-                      "anyOf": [
-                        {
-                          "type": "integer"
-                        },
-                        {
-                          "type": "null"
-                        }
-                      ],
-                      "description": "0–100. The valuation model's own calibrated confidence in this estimate — higher means the model is more certain. Read alongside `predicted_price_low` / `predicted_price_high` for the range.",
-                      "title": "Confidence Score"
-                    },
-                    "predicted_price": {
-                      "description": "Point estimate, AUD.",
-                      "title": "Predicted Price",
-                      "type": "number"
-                    },
-                    "predicted_price_high": {
-                      "description": "Upper bound of the 80% prediction interval, AUD.",
-                      "title": "Predicted Price High",
-                      "type": "number"
-                    },
-                    "predicted_price_low": {
-                      "description": "Lower bound of the 80% prediction interval, AUD.",
-                      "title": "Predicted Price Low",
-                      "type": "number"
-                    },
-                    "prediction_date": {
-                      "description": "Date the model produced this estimate. AVMs are refreshed in batches; not on demand.",
-                      "title": "Prediction Date",
-                      "type": "string"
-                    }
-                  },
-                  "required": [
-                    "predicted_price",
-                    "predicted_price_low",
-                    "predicted_price_high",
-                    "prediction_date"
-                  ],
-                  "title": "AvmEstimate",
-                  "type": "object"
-                },
-                {
-                  "type": "null"
-                }
-              ]
-            }
-          },
-          "title": "ValuationAll",
-          "type": "object"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "description": "The endpoint's payload, or `null` when Microburbs has no value."
-    },
-    "message": {
-      "anyOf": [
-        {
-          "type": "string"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "description": "Human-readable explanation. Omitted on success.",
-      "title": "Message"
-    },
-    "reason": {
-      "anyOf": [
-        {
-          "type": "string"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "description": "Machine-readable slug naming the no-data condition (e.g. `no_avm_for_GANSW704074813`). Stable per endpoint. Omitted on success.",
-      "title": "Reason"
-    }
-  },
-  "title": "ApiResponse[ValuationAll]",
-  "type": "object",
-  "x-fastmcp-top-level-schema": "ApiResponse_ValuationAll_"
-}New value: +null

First observedSep 14, 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, and non-open-world behavior. The description adds output content (point estimate, range, confidence score) and a clear cost (10¢ per call), which is useful behavioral context. It does not cover auth or rate limits beyond price, so it stops short of 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?

Outputs are front-loaded, followed by rationale and then a bold price line. The middle sentence about bundling is slightly wordy but earns its place by explaining the tool's convenience role. Overall efficient and well-structured.

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

Completeness3/5

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

It compensates for the missing output schema by describing return values, and annotations cover the safety profile. However, the only input parameter remains undocumented despite 0% schema coverage, leaving a notable gap for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0% and the sole parameter `gnaf_id` is never defined. The description says 'for one property', implying a property identifier, but gives no format, source, or example. With low coverage, the description must compensate, and it does not.

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 output for one property: point estimate, 80% range, and 0-100 confidence score. It also distinguishes itself from siblings by naming agent quoting, land values, negative gearing, and value series as separate calls, so an agent can tell it apart without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use it (to ask for 'everything valuation' without tracking endpoints) and names the four alternative valuation calls. It also notes it costs the same as the single `/valuation/avm` call, clarifying equivalence. Nothing is left to inference.

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

All Microburbs Australian Property Data tools Inspect

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