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by io.github.pipeworx-io
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Altos Inventory Trend

altos_inventory_trend
Read-onlyIdempotent

Track weekly inventory changes for a region (e.g., "Austin, TX"). Returns trends in inventory, new listings, days on market, median price, and price reductions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
weeksNoNumber of weeks to look back (default 12, max 52)
regionYesRegion code (e.g., "us_national", "ca_los-angeles")
_altosKeyYesAltos Research API key

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
trendYesWeekly inventory trend snapshots
regionYesRegion code queried
weeks_requestedYesNumber of weeks requested
snapshots_fetchedYesNumber of weekly snapshots retrieved

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "region": {
+      "description": "Region code queried",
+      "type": "string"
+    },
+    "snapshots_fetched": {
+      "description": "Number of weekly snapshots retrieved",
+      "type": "number"
+    },
+    "trend": {
+      "description": "Weekly inventory trend snapshots",
+      "items": {
+        "properties": {
+          "date": {
+            "description": "Friday snapshot date",
+            "type": "string"
+          },
+          "days_on_market": {
+            "description": "Median days on market",
+            "type": "string"
+          },
+          "inventory": {
+            "description": "Total inventory count",
+            "type": "string"
+          },
+          "new_listings": {
+            "description": "New listings count",
+            "type": "string"
+          },
+          "pct_price_decreased": {
+            "description": "Percent listings with price decrease",
+            "type": "string"
+          },
+          "price_median": {
+            "description": "Median listing price",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "weeks_requested": {
+      "description": "Number of weeks requested",
+      "type": "number"
+    }
+  },
+  "required": [
+    "region",
+    "weeks_requested",
+    "snapshots_fetched",
+    "trend"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_altosKey": "your-altos-api-key",
+    "region": "us_national"
+  },
+  {
+    "_altosKey": "your-altos-api-key",
+    "region": "ca_94105",
+    "weeks": 24
+  }
+]
  3. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already indicate the tool is read-only, open-world, idempotent, and non-destructive (readOnlyHint, openWorldHint, idempotentHint, destructiveHint). The description adds value by confirming the tool returns trends over time and listing specific metrics. However, it does not disclose additional behavioral details like pagination, rate limits, or data staleness. The annotations carry the main burden, so a score of 3 is appropriate.

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?

The description is a single, well-structured sentence that front-loads the verb and key action ('Track weekly inventory changes'), then lists the returned metrics. No extraneous information is present. This is optimal for an AI agent scanning many tool definitions.

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 tool has 3 parameters with 100% schema coverage, comprehensive annotations, and an output schema (mentioned but not shown), the description is largely adequate. It explains the core functionality and return values. A slight improvement would be to explicitly state that the data is historical and weekly, but the existing 'weekly inventory changes' implies this.

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 description coverage is 100% (every parameter has a description). The tool's description only provides an example region ('Austin, TX') and mentions the trends returned, but adds no new semantic information beyond what the schema already provides. Thus, a baseline score of 3 applies.

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?

The description clearly states the tool's purpose: tracking weekly inventory changes for a region, and lists specific metrics returned (inventory, new listings, days on market, median price, price reductions). This is a specific verb+resource combination. However, it does not explicitly differentiate from sibling tools like 'altos_market_stats' or 'altos_active_listings', which could cause confusion for an agent.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. For instance, it doesn't mention that for a current snapshot of listings, the agent should use 'altos_active_listings' instead. This omission forces the agent to rely on trial and error or external knowledge.

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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