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ddq-respond

Generate first-draft AI-section DDQ responses from structured JSON artifacts with consistency scoring.

Updated Apr 25, 2026
Search Tags:#ddq#response generation#private equity#consistency scoring#ai-section
One-click install
npx skills add https://github.com/bolnet/private-equity --skill ddq-respond
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ddq-respond
Source: https://github.com/bolnet/private-equity/tree/main/finance-mcp-plugin/skills/private-equity/ddq-respond
Command: npx skills add https://github.com/bolnet/private-equity --skill ddq-respond

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a deterministic first-draft response to an LP's AI-section DDQ, with cross-answer consistency scoring to flag contradictions before the LP reviews.

Core Features & Use Cases

  • DDQ Response Drafting: Build first-draft responses to AI-section DDQs from existing AI-evidence artifacts.
  • Cross-Answer Consistency: Score for consistency across answers, flagging contradictions for review.
  • Use Case: Utilize this Skill to create a response packet for an LP's AI-section DDQ, ensuring consistency and accuracy of information.

Quick Start

Generate a DDQ response packet for Bolnet Capital Partners I using the AI-evidence in the finance_output/ directory.

Frequently Asked Questions about ddq-respond

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate AI-section DDQ responses for private equity workflows?▼

Generate AI-section DDQ responses by feeding existing AI-evidence artifacts into a deterministic workflow that builds first-draft answers for private equity AI governance, data lineage, and risk management sections.

What is cross-answer consistency scoring in a DDQ response packet?▼

Cross-answer consistency scoring evaluates drafted DDQ responses to detect and flag contradictions across answers, ensuring LP reviewers see a coherent AI governance packet without conflicting statements.

Can I use this Skill without structured JSON artifacts from related tools?▼

No, you cannot use this Skill without structured JSON artifacts. It requires pre-existing AI-evidence artifacts from related tools to assemble the first-draft DDQ response and perform consistency scoring.

How do I flag contradictions in an LP's AI-section DDQ before review?▼

Flag contradictions in an LP's AI-section DDQ by applying cross-answer consistency scoring to the generated draft, which identifies conflicting information across AI governance and risk management responses.

What's the best way to draft LP AI governance DDQ answers from existing evidence?▼

The best way to draft LP AI governance DDQ answers is to consolidate structured JSON artifacts from prior AI-evidence tools into a deterministic response packet, then score for cross-answer consistency.

Are there limitations when generating private equity DDQ responses with consistency scoring?▼

A limitation is that the consistency scoring relies entirely on the quality of structured JSON artifacts provided; it cannot generate accurate private equity DDQ responses from unstructured evidence or missing data lineage inputs.

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