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by com.buckybuild
OverviewDiscussionsAdmin

See what Bucky has mapped for a city

cityInventory
Read-onlyIdempotent

Public city catalogue inventory. Pass exactly one of: cityName, lat and lng together, or geoDivisionId. A city name with multiple matches returns choices; after the user chooses, call again with that candidate geoDivisionId. Never pass a slug. Shows datasets grouped by topic as on file, not loaded yet, unavailable, or not confirmed. This is city coverage, not lot feasibility or operator health. If Bucky has not mapped the place, the result points to recording demand. It does not record demand by itself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNo
lngNo
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
cityNameNo
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
geoDivisionIdNo
conversation_idNoEcho the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / anyOf
      Removed value: -[
-  {
-    "additionalProperties": false,
-    "properties": {
-      "cityName": {
-        "maxLength": 100,
-        "minLength": 2,
-        "type": "string"
-      }
-    },
-    "required": [
-      "cityName"
-    ],
-    "type": "object"
-  },
-  {
-    "additionalProperties": false,
-    "properties": {
-      "lat": {
-        "maximum": 90,
-        "minimum": -90,
-        "type": "number"
-      },
-      "lng": {
-        "maximum": 180,
-        "minimum": -180,
-        "type": "number"
-      }
-    },
-    "required": [
-      "lat",
-      "lng"
-    ],
-    "type": "object"
-  },
-  {
-    "additionalProperties": false,
-    "properties": {
-      "geoDivisionId": {
-        "format": "uuid",
-        "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
-        "type": "string"
-      }
-    },
-    "required": [
-      "geoDivisionId"
-    ],
-    "type": "object"
-  }
-]
    • addedInput schema / properties
      Added value: +{
+  "cityName": {
+    "maxLength": 100,
+    "minLength": 2,
+    "type": "string"
+  },
+  "context": {
+    "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+    "type": "string"
+  },
+  "conversation_id": {
+    "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+    "type": "string"
+  },
+  "geoDivisionId": {
+    "format": "uuid",
+    "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
+    "type": "string"
+  },
+  "lat": {
+    "maximum": 90,
+    "minimum": -90,
+    "type": "number"
+  },
+  "llm_model": {
+    "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+    "type": "string"
+  },
+  "lng": {
+    "maximum": 180,
+    "minimum": -180,
+    "type": "number"
+  }
+}
    • addedInput schema / required
      Added value: +[
+  "context",
+  "llm_model"
+]
  2. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already carry the safety profile (readOnly, idempotent, non-destructive), so the bar is lower, and the description still adds real behavior: ambiguous city names return a candidate list that must be re-called with geoDivisionId, results classify datasets as on-file/not-loaded/unavailable/unconfirmed, and an unmapped place points to demand recording without performing it. This re-invocation loop and the 'does not record by itself' boundary are non-obvious traits not present in the 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?

The critical constraint (exactly one selector) is front-loaded in the second sentence, followed by the retry rule, output shape, and scope boundaries. Every sentence carries a distinct constraint or boundary; nothing is filler.

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?

For a read-only lookup with no output schema, the description supplies the input contract, the disambiguation loop, the shape and meaning of the result statuses, the scope boundary, and the fallback behavior. An agent could call and correctly handle this tool end-to-end from the description alone.

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?

Schema coverage is only 43% and no mutual-exclusion constraint is encoded in the schema, so the description carries meaningful weight: it states the exactly-one-of rule among cityName/lat+lng/geoDivisionId, that lat and lng must be passed together, and that slugs are invalid. That compensates for the gap on the geo parameters, though the analytics plumbing parameters (context, llm_model, conversation_id) are left entirely to the schema.

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 verb+resource ('Public city catalogue inventory') and immediately scopes what it returns (datasets grouped by topic with coverage statuses). It contrasts itself against adjacent concerns ('not lot feasibility or operator health'), so an agent can separate it from previewSiteCoverage, getFeasibilitySnapshot, and explainFeasibilityStatus without opening a schema.

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 an explicit input-selection rule ('Pass exactly one of: cityName, lat and lng together, or geoDivisionId'), a multi-match retry protocol, and an exclusion ('Never pass a slug'), plus the scope exclusion against feasibility tools. It stops short of naming the specific sibling tool an agent should call when feasibility is the actual need, so routing is implied rather than fully resolved.

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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