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DFX Intelligence

by io.github.Capital-W-Holdings
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A name to DFX ids, fast, across every private capital graph

resolve_name
Read-onlyIdempotent

Resolve a firm, fund, person or company name to canonical dfx ids from the Data Factory's index of every published name and alias (former names, dbas, legal names) on the family office, sponsor, venture, private equity, RIA, allocator, private credit and real estate fund graphs as each graph is indexed. Each row carries the ROLES the institution holds across graphs where the identity layer publishes them, so one institution that is a private equity manager, a registered adviser, a private credit manager, a real estate fund manager and a manager holding allocator capital comes back as one identity with the id on each graph, never as five unrelated firms. Ranked exact, prefix, then word match; one row per entity; typically under 200 ms. The first call before get_entity. Real estate organisations are resolved by resolve_organization instead. 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

NameRequiredDescriptionDefault
nameYesThe name, or a word of it (Blackstone, Horowitz, Thoma).
limitNo
domainNoComma-separated: family_office, independent_sponsor, venture_capital, private_equity, ria, allocators, private_credit, real_estate_funds. Default: all.
entity_typeNoComma-separated graph types: organization, office, sponsor, capital_provider, fund, person, company.
prefer_domainNoThe domain the question is about (same keys as domain, plus real_estate). Reorders, never filters: a row holding every asked word stays first, then rows in the preferred domain, then a real estate brand's primary adviser, then score. 'Blackstone' with real_estate_funds is Blackstone Real Estate Advisors with the brand's other advisers under `family`; 'Blackstone Management Partners' is still BMP.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / prefer_domain
      Added value: +{
+  "description": "The domain the question is about (same keys as domain, plus real_estate). Reorders, never filters: a row holding every asked word stays first, then rows in the preferred domain, then a real estate brand's primary adviser, then score. 'Blackstone' with real_estate_funds is Blackstone Real Estate Advisors with the brand's other advisers under `family`; 'Blackstone Management Partners' is still BMP.",
+  "type": "string"
+}
  2. Changed1 schema field changed
    • changedInput schema / properties / domain / description
      Previous value: -"Comma-separated: family_office, independent_sponsor, venture_capital, private_equity. Default: all four."New value: +"Comma-separated: family_office, independent_sponsor, venture_capital, private_equity, ria, allocators, private_credit, real_estate_funds. Default: all."
  3. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds substantial context beyond them: ranking order, sub-200ms latency, one-row-per-entity identity merging, and detailed entitlement/withholding behavior (first 5 rows, locked.count, contact values never returned, entitlement/locked fields). This is exactly the surplus detail this dimension rewards.

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?

The purpose and first-call guidance are front-loaded, which is good, but the body is a dense run-on of access rules and a promotional line ('7 days free at https://dfxintel.com/...'). The plan advertisement and some repeated entitlement framing do not earn their place, hurting signal-to-noise.

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 carries the burden of explaining returns and does so well: one row per entity, ROLES per row, locked/entitlement reporting, and what is withheld. It is close to complete for a resolution tool; only minor gaps around exact response shape remain.

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 80%, so the schema already documents name, domain, entity_type and prefer_domain in detail, including prefer_domain's reorder-not-filter semantics. The description adds only tangential query behavior (exact/prefix/word ranking) and does not meaningfully expand on the parameters beyond what the schema provides.

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 precise verb (Resolve) and resource (firm, fund, person or company name to canonical dfx ids), plus the scope of the underlying index. It explicitly distinguishes itself from resolve_organization (for real estate orgs) and get_entity (the follow-up call), so an agent can route without opening another schema.

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?

Gives explicit sequencing ('The first call before get_entity') and a clear exclusion with the alternative named ('Real estate organisations are resolved by resolve_organization instead'). When-to-use and when-not-to-use are both stated.

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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