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DFX Real Estate Intelligence

by io.github.Capital-W-Holdings
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Private equity transactions

search_pe_transactions
Read-onlyIdempotent

Acquisitions, add-ons, recapitalisations, carve-outs, secondary sales and exits on the private equity graph: type, status, announced and closed dates, target with industry and state, platform for an add-on (with the basis for calling it one), control, every party with role, side and attribution, and money (enterprise value, purchase price, equity value, target revenue and EBITDA) ONLY where disclosed, each beside its basis. An undisclosed amount is absent, never estimated. Filter by firm (any party), target, platform, type, target state, since-date, add-ons only, control or target name. 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
limitNo
queryNoNAME FILTER ONLY: the target's or any party's name contains. Never a sector or place; use sector and state.
sinceNoISO date; transactions announced on or after.
stateNoTwo-letter US state code of the target.
sectorNoThe target's industry as the graph classified it (technology, industrials, healthcare, consumer, construction_engineering, business_services, energy, environmental, financial_services, education, transportation_logistics, home_services, aerospace_defense, automotive). Plain words are mapped (software to technology). About half of transactions carry an industry; one without is not returned by this filter.
add_on_onlyNo
firm_dfx_idNoA dfx:pe: firm or person id; returns transactions where it is any party (sponsor, buyer, seller, co-investor, lender, adviser, deal partner).
target_dfx_idNoA private equity graph id of the form dfx:pe:<uuid>, as returned by search_pe_firms, search_pe_funds, search_pe_platforms or search_entities.
control_statusNo
platform_dfx_idNoA private equity graph id of the form dfx:pe:<uuid>, as returned by search_pe_firms, search_pe_funds, search_pe_platforms or search_entities.
transaction_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / query / description
      Previous value: -"Target company name contains."New value: +"NAME FILTER ONLY: the target's or any party's name contains. Never a sector or place; use sector and state."
    • addedInput schema / properties / sector
      Added value: +{
+  "description": "The target's industry as the graph classified it (technology, industrials, healthcare, consumer, construction_engineering, business_services, energy, environmental, financial_services, education, transportation_logistics, home_services, aerospace_defense, automotive). Plain words are mapped (software to technology). About half of transactions carry an industry; one without is not returned by this filter.",
+  "type": "string"
+}
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the safety annotations by disclosing the entitlement model: unpaid access returns only the first 5 rows plus locked.count and locked.by_type, records name their subject and first 3 related names per section, and contact values and decision-maker names are withheld. It also promises every answer reports what it withheld in entitlement and locked, which is exactly the behavioral context an agent needs before calling.

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

Conciseness3/5

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

Front-loads the resource and returned fields well, but the middle sentence is a long comma-spliced run-on that lists fields in prose form and is harder to scan than it needs to be. The ACCESS block is dense but earns its place; the marketing URL and free-trial pitch at the end is less clearly functional.

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?

Given 11 parameters, no required params, no output schema, and partial schema coverage, the description covers what is returned, the entitlement ceiling, and the money-disclosure rule, which is most of what an agent needs. It could be more explicit about pagination, the limit cap of 25, and how locked results should be presented, but the core is complete.

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 64%, so some parameters rely on the description. The description adds real meaning: query is a name filter only (never sector/place), money fields are disclosed-only and never estimated, and platform includes the basis for the add-on call. It does not explain the since-date ISO format or the firm_dfx_id any-party semantics beyond the schema, so it is not a 5.

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?

Opens with a concrete verb and resource ('Acquisitions, add-ons, recapitalisations, carve-outs, secondary sales and exits on the private equity graph') and then enumerates the fields returned, including money only where disclosed. An agent can distinguish this from siblings like search_sponsor_deals or search_vc_exits by the PE-graph transaction scope and the disclosed-only money rule.

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

Usage Guidelines4/5

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

Explicitly lists the filter facets (firm, target, platform, type, state, since, add-ons only, control, name), which tells an agent when this tool is the right one. It does not name an alternative sibling or state exclusions (e.g., when to use search_sponsor_deals instead), so it stops short of a 5.

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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