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Private Borrower Profile

ol_borrower_profile
Read-only

Profile + verified M&A/ownership history for one private-credit borrower. Pass borrower_norm (a key from ol_bdc_top_borrowers, or a name). Returns {summary, borrower_norm, borrower, profile, acquisitions, count, public_footprint}: the profile (description, industry, known_lenders, lien_position, estimated_size, notes, source), VERIFIED-only acquisitions (unaudited or refuted events never surface), and public_footprint (patents, federal contracts, corporate events) matched by exact normalized name, with matched_entities provenance -- a same-name match is never a guaranteed identity, and an empty footprint is normal for a private borrower. Honest-empty when the key is unknown. Source: SEC EDGAR BDC Schedule-of-Investments + attributed public M&A events (Oxford Ledge proprietary parse); FREE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax M&A/ownership events to return (default 20, hard cap 100).
borrower_normYesBorrower key (from ol_bdc_top_borrowers) or a borrower name such as 'Coupa Holdings, LLC'; resolved to the stored key (see match_type).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / borrower_norm / description
      Previous value: -"Canonical normalized borrower key (from ol_bdc_top_borrowers)."New value: +"Borrower key (from ol_bdc_top_borrowers) or a borrower name such as 'Coupa Holdings, LLC'; resolved to the stored key (see match_type)."
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare readOnlyHint, so the description carries the rest and does so richly: acquisitions are VERIFIED-only (unaudited/refuted never surface), same-name footprint matches are 'never a guaranteed identity', empty footprint is normal, honest-empty on unknown key, and the data source is attributed. This is meaningful behavior beyond the structured fields.

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?

Purpose is front-loaded, followed by input then return shape, and every clause carries information (caveats, provenance, source). It is dense and the inline return-field enumeration runs long, which slightly hurts scanability but not substance.

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?

There is no output schema, and the description compensates by enumerating the return keys (summary, profile, acquisitions, count, public_footprint, matched_entities provenance) and their semantics. An agent has everything needed to call it and interpret the result.

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 100%, so baseline is 3, but the description adds value by explaining that borrower_norm may be a stored key or a name and is 'resolved to the stored key (see match_type)', plus that limit caps M&A/ownership events. This exceeds what the schema alone conveys.

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+resource ('Profile + verified M&A/ownership history') and scopes it to 'one private-credit borrower', which separates it from the BDC-borrower list/aggregate siblings. It also names ol_bdc_top_borrowers as the upstream key source, so the agent can place it in the tool chain.

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?

It explains the input path (a key from ol_bdc_top_borrowers, or a name) and the honest-empty behavior, which is useful context. But it never says when to prefer this over alternatives such as search_bdc_borrower or ol_bdc_borrower_news_today; the usage guidance is implied rather than 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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