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by com.buckybuild
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Preview what Bucky has on file for an address

previewSiteCoverage
Read-onlyIdempotent

Free preview, no sign-in needed. For one street address in Canada or the US, it says whether Bucky covers the place and which zoning facts it holds for the lot (lot boundary, zone, height, density, setbacks, permitted uses, overlays, parking): found, partly on file, or not on file. It returns no values: no zone code, heights, setbacks or areas. The lot outline is a shape with no scale. Use it when the user is not signed in and asks what they can build at an address. For the numbers, call getFeasibilitySnapshot. That call asks the user to sign in.

Input Schema

NameRequiredDescriptionDefault
addressYesStreet address to analyse, e.g. "4170 Sophia St, Vancouver BC".
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."

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / llm_model
      Removed value: -{
-  "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"
-}
    • changedInput schema / required
      Previous value: -[
-  "address",
-  "context",
-  "llm_model"
-]New value: +[
+  "address",
+  "context"
+]
  2. Changed1 schema field changed
    • removedInput schema / properties / conversation_id
      Removed value: -{
-  "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"
-}
  3. Changed4 schema fields changed
    • changedInput schema / properties / context / description
      Previous value: -"Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\""New value: +"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.\""
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "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"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "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"
+}
    • changedInput schema / required
      Previous value: -[
-  "address",
-  "context"
-]New value: +[
+  "address",
+  "context",
+  "llm_model"
+]
  4. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld), yet the description still adds non-obvious behavior: the call is free and requires no sign-in, it returns presence status (found / partly on file / not on file) rather than values, and the lot outline is an unscaled shape. This prevents an agent from misreading the result as real dimensional data.

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?

Front-loaded with the two facts an agent needs most (free, no sign-in), then scope, then the negative space (no values returned), then routing to the sibling. Every sentence carries distinct information; nothing is repeated from the schema.

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?

There is no output schema, so the description must carry the return semantics — and it does, spelling out the three coverage statuses and explicitly warning that no zone codes, heights, setbacks or areas come back. Combined with the geographic scoping and the sign-in routing, an agent has everything needed to call it and interpret the result.

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 100% so the address format and the analytics-only 'context' parameter are already documented. The description still adds a real constraint the schema lacks: exactly one address, restricted to Canada or the US. It adds nothing about the 'context' parameter, but the schema handles that thoroughly.

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: a free, no-sign-in preview of what coverage/zoning facts exist for one street address. It enumerates the facts checked (lot boundary, zone, height, density, setbacks, permitted uses, overlays, parking) and explicitly contrasts itself with getFeasibilitySnapshot, so an agent can separate it from siblings 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 Guidelines5/5

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

Gives an explicit use condition — 'when the user is not signed in and asks what they can build at an address' — plus the alternative and its consequence: 'For the numbers, call getFeasibilitySnapshot. That call asks the user to sign in.' Both the when and the when-not are stated.

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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