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Ddq Response Drafter

Community
latour-ai
ddq-response-drafter

Draft responses to an incoming LP due diligence questionnaire or consultant RFP by matching each question to the firm's approved answer library, adapting approved language to the asker's wording and format without changing any facts, carrying the source and approval date beside every answer, and flagging questions with no acceptable match as NEEDS DRAFTING rather than improvising. Separately routes every performance, regulatory, and policy answer for compliance review. For IR, fundraising, COO, and compliance teams at private equity, private credit, hedge fund, real assets, and venture managers. Trigger on phrases like "draft the DDQ," "answer this questionnaire," "RFP from [consultant]," "fill out this DDQ," "we got an ILPA DDQ," "respond to these LP questions," "match this to our answer library," or when a user uploads a due diligence questionnaire, RFP, or investor question list. Do NOT use for scanning someone else's completed DDQ for red flags — use the ddq-red-flag-scanner skill. Do NOT use for drafting a fund one-pager — use the fund-marketing-one-pager skill. Never invents facts; drafted answers require human and compliance review.

Overview

Publisherlatour-ai
Repositoryskills
Skill nameddq-response-drafter
Stars
69
Forks
4
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by latour-ai on GitHub. Read the source before you install it.

Installation

Install the Ddq Response Drafter AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/latour-ai/skills/tree/main/ddq-response-drafter
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/latour-ai/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/ddq-response-drafter .claude/skills/ddq-response-drafter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ddq Response Drafter in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ddq Response Drafter on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ddq Response Drafter is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

DDQ Response Drafter

Get a DDQ from blank to substantially drafted in an hour, with every answer traceable to an approved source and every genuinely new question clearly flagged for a human. The goal is not to answer faster than you can think — it is to stop your best IR people from spending three weeks retyping answers they have already written, so their judgment goes to the twenty percent that actually needs it.

Why this skill exists

A fund in market handles a lot of DDQs, and they ask the same things in different words. The work is overwhelmingly matching and adaptation, not thinking: the LP wants your valuation policy described in their template's section 4.2 rather than yours, with their terminology and their character limit. That work is real, it takes forty to sixty hours per questionnaire, and it is done by the people you least want doing data entry.

It is also where the mistakes happen. The failure mode is not a wrong answer thought up from scratch — it is a right answer that went stale: an AUM figure from two quarters ago, a headcount that changed, a policy description that no longer matches the manual, a performance figure carried forward without its as-of date. Fatigue at week three is exactly when those slip through, and an LP who catches an inconsistency between your DDQ and your ADV will ask about it in the ODD call.

So the discipline this skill enforces is narrow and strict: adapt approved language, never generate facts, always carry the source and the as-of date, and be loud about what has no approved answer.

Inputs

Required:

  • The incoming DDQ, RFP, or investor question list (uploaded or pasted)
  • The firm's approved answer library — ideally an export with, per entry: the question or topic, the approved answer, the source document, and the approval or as-of date. A prior completed DDQ works as a substitute library, with the caveats noted below.

Optional but high-value:

  • The most recent Form ADV, PPM, LPA, and compliance manual, for cross-checking that library answers still match the governing documents
  • Current firm facts with as-of dates: AUM, fund sizes, headcount by function, portfolio company count, office locations
  • The most recent performance figures, with the required net/gross labeling and as-of date
  • Who the asker is — an ILPA-standard DDQ, a consultant's proprietary RFP, and a sovereign wealth fund's bespoke list get different treatment
  • Character or word limits per question, and the required output format
  • Prior DDQs completed for this same LP or consultant, so answers stay consistent with what they were told before
  • The firm's tone conventions and any language compliance has previously rejected

Missing-input behavior: Without an answer library there is nothing to draft from, and generating answers about a firm's policies would be fabrication of exactly the kind this skill exists to prevent. Say that plainly and ask once. If the user offers a prior completed DDQ instead of a formal library, use it — but flag that its answers carry no approval dates, so every extracted fact needs re-verification before use, and mark them accordingly throughout. If firm facts with as-of dates are not provided, never carry a figure forward from the library without marking it [VERIFY AS-OF DATE].

How it works

  1. Parse the questionnaire into discrete questions, preserving the asker's numbering and section structure — the response has to go back in their format. Split multi-part questions into their parts; a partially answered compound question reads as evasion.
  2. Classify each question by type: firm and organization, strategy and process, track record and performance, team, operations and service providers, valuation, risk, compliance and regulatory, ESG, terms, references. The classification drives routing in step 6.
  3. Match each question to the library by meaning rather than wording. Record the match confidence honestly — a close match, a partial match that covers some of what was asked, or no match.
  4. Adapt the approved language to the asker's terminology, format, and length limit. Adapting means rephrasing and reordering; it does not mean adding a fact, sharpening a claim, or filling a gap in the approved answer with something reasonable-sounding.
  5. Flag every no-match and partial-match as NEEDS DRAFTING with a note on what specifically is being asked that the library does not cover. Never improvise the answer. A blank flagged for a human takes five minutes to fill; an invented answer that reaches an LP is a different category of problem.
  6. Route for review. Every answer containing a performance figure, a regulatory statement, a policy description, an AUM or headcount figure, or a forward-looking statement goes to compliance review — see the routing list below.
  7. Run the consistency checks: answers against each other within this DDQ, against the Form ADV and governing documents where provided, and against any prior DDQ for the same asker.
  8. Flag every stale-dated fact — anything where the library's as-of date is old enough that the figure has probably moved.
  9. Assemble the deliverable in the asker's structure, with the internal tracking table alongside it.

Output format

Length follows the substance: cover what the task needs and leave out filler sections, restated summaries, and boilerplate.

# DDQ Response Draft — [asker] [questionnaire name/version]
Received: [date] | Due: [date] | Questions: [N]
Library: [source, export date] | Format required: [ ]

## Status summary
Ready for review: [N] | Needs drafting: [N] | Needs compliance review: [N]
Stale-dated facts flagged: [N] | Consistency issues: [N]

## Response tracker
| Q# | Question (short) | Drafted response | Library source | Approved | Match | Status |
|---|---|---|---|---|---|---|
[Status: READY / NEEDS DRAFTING / NEEDS COMPLIANCE / VERIFY AS-OF DATE]

## Needs drafting — no acceptable library match
### Q[#]: [full question]
**What's being asked that the library doesn't cover:** [specific]
**Closest library entry:** [entry, and why it falls short]
**Who should draft this:** [IR / compliance / CFO / CIO]

## Needs compliance review
| Q# | Response excerpt | Why routed |
|---|---|---|

## Stale-dated facts
| Q# | Fact | Value in library | As of | Needs refresh? |
|---|---|---|---|---|

## Consistency check
| Fact | This DDQ (Q#) | Other source (doc, §) | Consistent? |
|---|---|---|---|
[Internal, vs. Form ADV / PPM / LPA, and vs. prior DDQ for this asker.]

## Assembled response document
[The full draft in the asker's structure and numbering, ready for review.
Every NEEDS DRAFTING item appears in place as a clearly marked placeholder —
never silently omitted, never filled with plausible text.]

Always route to compliance

These answer types go to compliance review without exception, regardless of how well the library matches:

  • Any performance figure — returns, IRR, MOIC, DPI, TVPI, benchmark comparisons, attribution — including whether gross and net are labeled as required
  • Track record presentation: which funds and deals are included, how realized and unrealized are treated, and whether the selection could read as cherry-picking
  • AUM, fund sizes, and dry powder
  • Regulatory history: examinations, deficiency letters, enforcement, litigation, and any "has the firm ever…" question
  • Valuation policy and process, especially for hard-to-value assets
  • Conflicts of interest, related-party transactions, and allocation policy
  • Side letters, MFN, and preferential terms
  • Key person, succession, and team departures
  • Fees and expenses charged to the fund
  • Cybersecurity, BCP, and insurance coverage claims
  • ESG claims and any policy the firm states it follows
  • Anything forward-looking: target returns, pipeline, fundraising plans, capacity

Guardrails

  • Never invent a fact about the firm. Not an AUM figure, not a headcount, not a policy, not a date, not a service provider, not a process description. If the library does not contain it, the answer is NEEDS DRAFTING. This is the single rule the skill exists to enforce, and it holds even when the answer seems obvious from context or appears in an adjacent library entry.
  • Adapt language; do not upgrade claims. Rephrasing an approved answer to fit an LP's wording is the job. Making it sound more impressive, more definitive, or more complete is not — even removing an approved hedge changes the claim.
  • Every drafted answer carries its library source and approval date. An answer without provenance cannot be reviewed efficiently, which defeats the point.
  • Stale facts are flagged, never refreshed by inference. If AUM was $2.1B as of two quarters ago, the draft says so and flags it. It does not estimate the current figure.
  • Performance answers are the highest-risk output in the document. Marketing Rule requirements around net presentation, time periods, hypothetical and extracted performance, and substantiation apply to DDQ responses that will be used in an investment decision. Route them all, and never generate a performance figure that was not supplied.
  • Do not answer questions about individuals' backgrounds, regulatory history, or personal circumstances from anything other than approved firm records.
  • Never omit a question. An unanswered question left out of the response document is worse than one flagged as needing drafting.
  • This is a draft, not a submission. Every response requires human review by someone accountable for its accuracy, and compliance review for the routed items, before it goes to the LP.
  • Confidentiality: DDQs, answer libraries, and fund documents are confidential. Assume a firm-approved AI environment.

Example prompts

"ILPA DDQ from [consultant] attached, due in ten days. Our approved answer library export is the second file — it has question, answer, source doc, and approval date. Draft what you can, flag what needs real drafting, and route anything compliance has to see. AUM as of quarter end was $3.4B, headcount 41."

"This LP sent a bespoke 90-question list, no standard format. We don't have a formal library but here's our last completed DDQ from March. Draft from it, but flag everything that needs re-verification since we don't have approval dates."

"Short-form DDQ, 200-character limit per answer. Library attached. Adapt our standard answers to fit the limit without dropping anything compliance requires."

Works well with

Run ddq-red-flag-scanner over the finished response before it goes out — reading your own DDQ the way a skeptical ODD analyst would is the cheapest quality check available. Route performance sections through marketing-compliance-prescreen, and use fund-marketing-one-pager for the materials that accompany the response.

Frequently asked questions

What does the Ddq Response Drafter AI skill do?

Draft responses to an incoming LP due diligence questionnaire or consultant RFP by matching each question to the firm's approved answer library, adapting approved language to the asker's wording and format without changing any facts, carrying the source and approval date beside every answer, and flagging questions with no acceptable match as NEEDS DRAFTING rather than improvising. Separately routes every performance, regulatory, and policy answer for compliance review. For IR, fundraising, COO, and compliance teams at private equity, private credit, hedge fund, real assets, and venture mana...

Why use Ddq Response Drafter on TypingMind?

Because you install it once and use it with any model. Ddq Response Drafter is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ddq Response Drafter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/latour-ai/skills/tree/main/ddq-response-drafter. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ddq Response Drafter?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ddq Response Drafter?

As many as you like. As long as a model supports skills, you can use Ddq Response Drafter with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ddq Response Drafter AI skill free?

Yes. It is published on GitHub by latour-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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