Skip to main content
Glama

DFX Real Estate Intelligence

by io.github.Capital-W-Holdings

Find parcels by place, use, tenure, vintage and assessed value

search_parcels
Read-onlyIdempotent

Search the assessor parcel layer with filters instead of one exact address. Filter by state, municipality, assessor land use code, owner-occupancy, tax-exempt status, year built and assessed value range; results carry assessed value, gross building area, assessed value per square foot, the annual tax and the year built. This is the only way to ask a QUESTION of the parcel layer: resolve_address needs an address you already have. Every answer states the true match count alongside the sample, and a search that matches nothing names the filter that emptied it rather than returning a bare empty list. At least one filter is required. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
stateNoTwo letter state code
land_useNoAssessor land use code, for example 'R3' for a three family dwelling
tax_exemptNotrue for the institutional universe (churches, universities, authorities), false for the taxable one
built_afterNoExclusive lower bound on year built
built_beforeNoExclusive upper bound on year built
max_assessedNoMaximum assessed total, in dollars
min_assessedNoMinimum assessed total, in dollars
municipalityNoCity or town, for example 'Boston'
owner_occupiedNotrue for owner-occupied, false for investor or institutionally held. Parcels whose roll does not state it are excluded either way.

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses meaningful response behavior: 'Every answer states the true match count alongside the sample,' and a no-match search 'names the filter that emptied it rather than returning a bare empty list.' It also describes the fields carried in results, adding context that annotations do not provide.

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 core action and resource, then enumerates filters and result fields, and finishes with edge-case behavior and the filter requirement. Every sentence contributes distinct information with no redundant filler.

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?

Given the rich input schema, the sibling context, and the absence of an output schema, the description adequately covers what the agent needs: filterable fields, returned fields, match-count behavior, no-match naming, required filter rule, and cost. No significant operational gap remains.

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 high at 90%, so most parameter meanings already live in the schema. The description adds the crucial constraint 'At least one filter is required,' which is not evident from the schema's zero required parameters, and it lists the filterable dimensions, reinforcing the parameter semantics.

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 opens with a specific verb and resource: 'Search the assessor parcel layer with filters instead of one exact address.' It distinguishes itself from resolve_address and clarifies the unique question-answering role of the tool, so an agent can clearly identify its purpose among siblings.

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 states when to use this tool: 'This is the only way to ask a QUESTION of the parcel layer: resolve_address needs an address you already have.' It also gives a concrete usage rule, 'At least one filter is required,' and notes the tool is 'Free,' disambiguating the choice context clearly.

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

All DFX Real Estate Intelligence toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a clearly distinct task: exact address resolution versus filter-based parcel search, subscription delta versus event search, coverage status versus natural-language routing, and the account lifecycle is split into open/fund/status. Even the closest pairs, changes_since and search_property_events, are explicitly disambiguated in their descriptions.

Naming Consistency3/5

The dominant pattern is verb_noun, e.g. resolve_address, search_parcels, get_property_record, but several tools break it: dfx_coverage, dfx_payment_status, debt_maturity_schedule, changes_since, and what_can_dfx_answer. These names are still readable and semantically clear, so the naming is mixed rather than chaotic.

Tool Count5/5

Twelve tools is well within the ideal range and each tool earns its place: discovery, coverage, resolution, search, records, event subscription, paid maturity schedules, and the account/payment lifecycle all have a distinct role. No tool feels redundant or ornamental.

Completeness4/5

The read-only real estate intelligence surface is well covered: coverage checks, address and organization resolution, property records, parcel search, event search, delta subscription, paid loan schedules, and account funding. The main gap is that resolve_organization returns entity IDs without an obvious downstream tool for organization detail, and there is no separate event detail endpoint, but agents can work around these.

Resources