Altos

Altos Market Stats

altos_market_stats

Read-onlyIdempotent

Get current market snapshot for a region (e.g., "San Francisco, CA"). Returns inventory count, new listings, median price, days on market, and market action index.

Input Schema

TableJSON Schema

Name	Required	Description
`date`	No	Date (must be a Friday, YYYY-MM-DD). Defaults to most recent Friday.
`region`	Yes	Region code (e.g., "us_national", "ca_los-angeles", "ca_94105")
`quartile`	No	Price quartile: "ALL", "FIRST", "SECOND", "THIRD", "FOURTH". Default: ALL.
`res_type`	No	Residential type filter: "single_family" or "multi_family". Default: single_family.
`_altosKey`	Yes	Altos Research API key

Output Schema

TableJSON Schema

Name	Required	Description
`date`	Yes	Friday date (YYYY-MM-DD) for snapshot
`stats`	Yes	Market statistics rows
`region`	Yes	Region code queried
`quartile`	Yes	Price quartile filter applied
`res_type`	Yes	Residential type filter applied

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedMay 8, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "date": {
+      "description": "Friday date (YYYY-MM-DD) for snapshot",
+      "type": "string"
+    },
+    "quartile": {
+      "description": "Price quartile filter applied",
+      "type": "string"
+    },
+    "region": {
+      "description": "Region code queried",
+      "type": "string"
+    },
+    "res_type": {
+      "description": "Residential type filter applied",
+      "type": "string"
+    },
+    "stats": {
+      "description": "Market statistics rows",
+      "items": {
+        "properties": {
+          "date": {
+            "description": "Snapshot date",
+            "type": "string"
+          },
+          "days_on_market_median": {
+            "description": "Median days on market",
+            "type": "string"
+          },
+          "estimated_sales_total": {
+            "description": "Estimated sales count",
+            "type": "string"
+          },
+          "inventory_total": {
+            "description": "Total inventory count",
+            "type": "string"
+          },
+          "listings_absorbed_total": {
+            "description": "Listings absorbed",
+            "type": "string"
+          },
+          "market_action_median": {
+            "description": "Market action index",
+            "type": "string"
+          },
+          "months_of_inventory_median": {
+            "description": "Months of inventory supply",
+            "type": "string"
+          },
+          "new_listings_total": {
+            "description": "New listings added",
+            "type": "string"
+          },
+          "percent_price_decreased_median": {
+            "description": "Median percent price decrease",
+            "type": "string"
+          },
+          "price_median": {
+            "description": "Median listing price",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "region",
+    "date",
+    "res_type",
+    "quartile",
+    "stats"
+  ],
+  "type": "object"
+}

Changed1 schema field changedMay 6, 2026

addedInput schema / examples

Added value: +[
+  {
+    "_altosKey": "your-altos-api-key",
+    "region": "us_national"
+  },
+  {
+    "_altosKey": "your-altos-api-key",
+    "date": "2024-01-12",
+    "quartile": "FIRST",
+    "region": "ca_los-angeles",
+    "res_type": "single_family"
+  }
+]

First observedApr 22, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds value by specifying the exact data fields returned (inventory count, new listings, etc.), giving the agent a clear behavioral expectation beyond the semantic annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, clear sentence that front-loads the purpose and output. No wasted words; every element earns its place.

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

Completeness5/5

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

With 100% schema coverage, annotations covering safety, and an output schema present, the description is sufficient. It explains the tool's function and key outputs, leaving no gaps for effective use.

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

Parameters3/5

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

Schema covers all 5 parameters with descriptions and examples. The description restates the region example but does not add new meaning beyond the schema. Baseline of 3 is appropriate given 100% schema coverage.

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 states the tool retrieves a 'current market snapshot for a region' and explicitly lists the metrics returned (inventory, new listings, median price, days on market, market action index), distinguishing it from specific sibling tools like altos_active_listings or altos_new_listings.

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?

The description implies usage when an overview of current market conditions is needed, but does not explicitly state when to use this tool versus specific sibling tools or provide when-not scenarios. Guidance is implicit through the composite nature of the output.

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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