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Get feasibility snapshot for an address

getFeasibilitySnapshot
Read-onlyIdempotent

Look up lot, zone, and building envelope for one street address in Canada or the US. Pass address. One address per call; cannot search or compare. Every envelope value carries a status. Never report not_extracted or site_specific_schedule as no limit or as zero — call explainFeasibilityStatus first. Envelope numbers are extracted ceilings. Call getBylawSection with a citation knowledgeSectionId, or with coverage.geoDivisionId, zone.code, and the section number, before treating a number as available on this lot. Do not fetch zone.bylawSourceUrl.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesWhich question the caller is answering. Used for attribution and to pick the link back; the payload is the same either way.full
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",
-  "source",
-  "context"
-]New value: +[
+  "address",
+  "source",
+  "context",
+  "llm_model"
+]
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, open-world), and the description adds substantial behavior beyond them: every envelope value carries a status, envelope numbers are 'extracted ceilings' rather than authoritative limits, and there are required follow-up calls before the data can be relied upon. This is exactly the kind of caveat an agent cannot infer from annotations.

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

Conciseness4/5

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

Front-loaded purpose followed by tightly packed, actionable constraints. Slightly dense and list-like, but every sentence carries a distinct behavioral rule, so little is wasted.

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?

With no output schema, the description does the heavy lifting on return-value semantics (status on every envelope value) and cross-tool workflow. It stops short of describing the full payload shape, but the critical gotchas an agent needs to avoid misreporting numbers are all present.

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 baseline is 3. The description adds a little ('Pass address') but its main value is naming output-side fields (knowledgeSectionId, coverage.geoDivisionId, zone.code, zone.bylawSourceUrl) that drive sibling calls, which gives the agent context beyond the input schema without fully documenting the structured parameters.

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+scope: 'Look up lot, zone, and building envelope for one street address in Canada or the US.' An agent can immediately tell this is a per-address feasibility lookup rather than a batch/search tool, and the scope constraint ('one address, cannot search or compare') further distinguishes it from siblings like runFeasibilityAnalysis or screenLots.

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?

Explicit routing: call explainFeasibilityStatus before treating not_extracted or site_specific_schedule as a limit, and call getBylawSection with specific keys before treating a number as available. Also states a clear exclusion ('Do not fetch zone.bylawSourceUrl') and the one-address-per-call constraint.

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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