Skip to main content
Glama

Bucky

by com.buckybuild
OverviewDiscussionsAdmin

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

TableJSON 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."
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.
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. 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"
+]
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

The description adds meaningful behavioral context beyond the annotations: no sign-in needed, returns no numerical values, the lot outline has no scale, and the result is a coverage indicator rather than actual zoning data. It goes beyond the readOnly/idempotent hints and does not contradict them.

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 front-loaded with the most important facts (free, no sign-in, geographic scope) and then moves to output semantics, use-case, and the alternative tool. Every sentence earns its place; the zoning-facts list is detailed but directly relevant to what the tool returns.

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 absence of an output schema, the description does a good job explaining the output: coverage statuses, no values, and a shape with no scale. It also covers prerequisites (no sign-in) and the alternative for numeric results. Minor ambiguity remains about the exact structure of the per-fact statuses and error behavior for unsupported or invalid addresses.

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 coverage is 100%, so the schema already documents all parameters. The description adds helpful scope constraints for the address (Canada/US, street address) and implies the preview is read-only, but adds no additional meaning for context, llm_model, or conversation_id beyond what the schema provides.

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 names a specific verb, resource, and scope: it previews what Bucky has on file for one US/Canada street address. It clearly defines the output as coverage statuses (found, partly, not) for a concrete list of zoning facts. This distinguishes it from getFeasibilitySnapshot, which returns numeric values.

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?

The description explicitly says to use this tool when the user is not signed in and asks what they can build at an address. It also names the alternative, getFeasibilitySnapshot, and notes that alternative requires sign-in. This gives an agent a clear decision rule for tool selection.

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

All Bucky toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources