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DFX Real Estate Intelligence

by io.github.Capital-W-Holdings
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Which lenders have funded deals like this one

find_lenders_for_financing
Read-onlyIdempotent

Lenders ranked on the comparable facilities they CURRENTLY HOLD on BDC schedules: same lien, a borrower industry containing the term (as the filer wrote it: health, software, industrial, business services), a facility size lower bound inside the band, entered since the window. Score = comparables 35%, recency 20%, size fit 15%, mark on the comparable book 15%, sponsors named 15%. Refuses one stale comparable, a book marked under 0.85 and passive holds under $2M. Sizes are lower bounds (BDC pieces), never the commitment. states filters on borrower headquarters where DFX holds one (GLEIF, about one comparable in six today); the answer reports geo_coverage, so say how many comparables carried a state. This is the answer to 'find lenders for a $60M unitranche for a sponsor-backed healthcare services business': use it before search_private_credit, whose industry filter lists borrowers. ACCESS: without a paid DFX plan on the vertical, a list returns its first 5 rows in full and a count of the rest by type (locked.count, locked.by_type), never the rows; a record names its subject and the first 3 related names per section; contact values (email, phone, profile URLs) and decision-maker names are never returned, only their types and counts. Every answer says what it withheld in entitlement and locked. Full access: DFX Intelligence, 7 days free at https://dfxintel.com/data-factory/plans.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lienNoA unitranche is filed as first lien.first_lien
limitNo
sinceNoISO date; comparables entered on or after it. Default 24 months ago.
statesNoTwo-letter borrower headquarters states, e.g. ["TX","FL"]. Thins the universe to borrowers with a known state.
industryYesA word from the filer-written industry: health, software, industrial, business services, consumer, education.
band_max_usdNo
band_min_usdNoThe financing's own size band, for the size-fit factor; defaults to size_min_usd.
size_max_usdNo
size_min_usdNoSmallest comparable facility (lower bound) to count.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / states
      Added value: +{
+  "description": "Two-letter borrower headquarters states, e.g. [\"TX\",\"FL\"]. Thins the universe to borrowers with a known state.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only declare it a safe read; the description adds the scoring weights, refusal conditions (stale comparables, under-0.85 marks, passive holds under $2M), the lower-bound caveat on sizes, and a detailed access/entitlement model describing exactly what is withheld and what geo_coverage means. This is far beyond the annotation surface.

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 with the core ranking behavior and criteria, then the refusal rules and access model. Dense but almost every clause carries information; the only drag is the promotional plan URL, though the entitlement explanation around it is genuinely useful.

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 9-parameter ranking tool with no output schema, the description explains what an answer contains, what it withholds, how coverage is reported (geo_coverage, entitlement, locked), and the ranking logic. An agent has everything needed to call and interpret it.

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 67%; the description adds real meaning beyond the schema by clarifying that sizes are BDC lower bounds never the commitment, that `states` only matches where DFX holds a headquarters, and how `industry` terms are matched against filer-written values.

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 (rank lenders) on a specific resource (comparable facilities currently held on BDC schedules) and enumerates the exact matching criteria. It is unmistakably distinct from siblings like search_private_credit or find_real_estate_lenders.

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?

Explicitly routes the agent: gives a concrete example query ('$60M unitranche for a sponsor-backed healthcare services business') and says to use it before search_private_credit, explaining why the sibling differs. When-to-use and when-to-prefer-alternative are both covered.

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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