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Find Property Comparables

find_property_comparables
Read-only

Find comparable properties for valuation - the #1 tool for real estate agents.

REQUIRED parameters:

  • latitude, longitude: Target property coordinates

  • type_local: "Maison" or "Appartement"

  • surface_min, surface_max: Surface range in m² (typically ±20% of target)

Optional:

  • pieces: Number of rooms (±1 tolerance applied)

  • code_postal, commune: Optional administrative fallback when GPS comparables are sparse

  • radius_m: Search radius (default: 500m, max: 2000m)

  • max_age_months: Transaction age limit (default: 18, same as estimate_property_value; max: 36) When fewer than 3 comps match, the search first extends to 36 months at the same radius, then to 2 km.

  • limit: Max comparables (default: 10, max: 20)

Returns:

  • Comparable properties with similarity scores (0-1)

  • Distance from target, age of transaction

  • Adjustment suggestions, to apply to the comparable's €/m² (e.g., "+2% for 10m² larger": smaller units sell dearer per m²)

  • excluded_comparables: sales left out (Carrez/built surface mismatch, €/m² over 2× from the median)

  • Valuation estimate with comparable-agreement confidence, plus a data-calibrated 50% interval (interval.*) and traceable confidence_factors — see estimate_property_value's description for the full field reference

Example: Find comps for a 75m² apartment near Tour Eiffel: {latitude: 48.858, longitude: 2.294, type_local: "Appartement", surface_min: 60, surface_max: 90}

Cost: 10 credits per call

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum comparables to return (default: 10, max: 20)
piecesNoNumber of rooms (optional, ±1 tolerance used)
communeNoCommune fallback when GPS comparables are sparse
latitudeYesLatitude of the target property (required)
radius_mNoSearch radius in meters (default: 500, max: 2000)
longitudeYesLongitude of the target property (required)
type_localYesProperty type (required for matching)
code_postalNoPostal code fallback when GPS comparables are sparse
surface_maxYesMaximum surface in m² (typically target surface + 20%)
surface_minYesMinimum surface in m² (typically target surface - 20%)
max_age_monthsNoMaximum transaction age in months (default: 18, max: 36)
exclude_bulk_salesNoExclude bulk sales (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / max_age_months / default
      Removed value: -12
    • changedInput schema / properties / max_age_months / description
      Previous value: -"Maximum transaction age in months (default: 12, max: 36)"New value: +"Maximum transaction age in months (default: 18, max: 36)"
  2. First observed

TDQS

A4.1/5.0
Behavior5/5

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

With readOnlyHint=true and openWorldHint=false already covering safety, the description adds rich behavioral detail: cost (10 credits per call), fallback search logic (extends to 36 months at same radius, then 2 km when fewer than 3 comps match), and return structure including similarity scores, excluded_comparables, adjustment suggestions, and confidence intervals. This goes well beyond what annotations provide.

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?

The description front-loads purpose and organizes required/optional/returns/example sections clearly. However, it repeats parameter details already present in the schema and includes a marketing phrase ('the #1 tool'), which detracts slightly from conciseness.

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 12-parameter tool with no output schema, the description compensates thoroughly by detailing return fields, cost, fallback logic, defaults, and a concrete example. An agent has enough information to invoke correctly and interpret results without consulting missing output documentation.

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 description coverage is 100%, so the baseline is 3, but the description adds meaningful semantics: surface range should be ±20% of target, pieces carries ±1 tolerance, max_age_months default aligns with estimate_property_value, and fallback behavior when comps are sparse. These interpretive details aid correct invocation beyond raw schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Find') and resource ('comparable properties for valuation'), which is clear and actionable. However, it does not explicitly differentiate itself from sibling tools like estimate_property_value or search_property_transactions; it only references estimate_property_value for field reference, leaving the agent to infer when to choose this over alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

The description implies usage ('for valuation', 'for real estate agents') and details required/optional parameters, but provides no explicit when-to-use versus alternatives or exclusions. The marketing phrase 'the #1 tool for real estate agents' occupies space without offering selection guidance.

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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