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Get feasibility snapshot for an address

getFeasibilitySnapshot

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. A live answer uses one site lookup from the monthly plan allowance; usage says if it was charged and how many are left. getBuckyMcpGuide reports the allowance for free. CMHC rental survey figures describe purpose-built rentals; the new-build proxy is the 2000 or later band. Missing facts are not surveyed or unavailable, never zero. Cite RMS figures as Source: CMHC, Rental Market Survey, October YYYY using referencePeriod. Cite starts and completions with their own source and period. 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. lot.minLotFrontageM is the zone minimum. lot.lotConformity compares lot width, lot area, and floor area per unit to those minima. A missing input is unknown, never a pass. State every fail before quoting a unit count.

Input Schema

NameRequiredDescriptionDefault
sourceNoWhich 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."

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / required
      Previous value: -[
      -  "address",
      -  "source",
      -  "context"
      -]New value: +[
      +  "address",
      +  "context"
      +]
  2. 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",
      -  "source",
      -  "context",
      -  "llm_model"
      -]New value: +[
      +  "address",
      +  "source",
      +  "context"
      +]
  3. Changed1 schema field changed
    • changedInput schema / properties / source / enum
      Previous value: -[
      -  "zoning_lookup",
      -  "lot_dimensions",
      -  "setback_lookup",
      -  "height_limit_lookup",
      -  "full"
      -]New value: +[
      +  "zoning_lookup",
      +  "lot_dimensions",
      +  "setback_lookup",
      +  "height_limit_lookup",
      +  "lot_split_lookup",
      +  "full"
      +]
  4. 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"
      -}
  5. 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"
      +]
  6. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Explains why the tool is not read-only/idempotent: 'A live answer uses one site lookup from the monthly plan allowance; `usage` says if it was charged and how many are left' — a cost/rate-limit disclosure the annotations cannot express. It also discloses interpretation hazards ('Missing facts are not surveyed or unavailable, never zero'; 'Envelope numbers are extracted ceilings') that materially affect how results are reported.

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?

Purpose and the single-address constraint are front-loaded, and most sentences carry actionable content (status handling, citation formats, conformance semantics). It is dense and long, with citation-format rules and envelope caveats packed into one undifferentiated block, which slightly hurts scanability.

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 takes on responsibility for return-value interpretation and does so thoroughly (status values, missing-vs-zero, citation requirements, lot conformity logic). The `source` parameter's role in attribution is left to the schema, a minor gap for a high-complexity tool.

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% and the schema already documents all three parameters well, including examples and the `context` privacy constraint. The description only reinforces the `address` constraint (one per call, no search) and never mentions `source` or `context`, so it adds little beyond 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 and resource with scope: 'Look up lot, zone, and building envelope for one street address in Canada or the US.' The 'One address per call; cannot search or compare' clause immediately separates it from batch siblings like screenLots and runFeasibilityAnalysis.

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 rules: call `explainFeasibilityStatus` before interpreting `not_extracted`/`site_specific_schedule`, call `getBylawSection` before treating an envelope figure as available on the lot, and use `getBuckyMcpGuide` for the free allowance check. It also names an explicit don't ('Do not fetch `zone.bylawSourceUrl`').

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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