Bulk Q&A Answers

Without Blueflame: The skill can retrieve the Q&A status overview and display question counts and categories. It cannot draft answers — all questions will be marked Open. The core value of this skill requires Blueflame.

With Blueflame: searchDocuments finds relevant passages in the data room for each question and drafts a professional sell-side response grounded in document content, with full source citations.

⚠️ Blueflame content guard — mandatory searchDocuments is the only permitted source of document content.

• Never draft Q&A answers from Claude's general knowledge. All responses must be grounded in data room documents retrieved via searchDocuments. A fabricated answer is worse than no answer.

• If searchDocuments returns an activation link instead of results, stop immediately and tell the user:

  "To draft answers grounded in your data room, Blueflame AI search needs to be activated on this project: 🔗 Activate Blueflame: [activation link] With Blueflame: I'll read the relevant documents for each question and draft a professional sell-side response citing the document name and page — so every answer is defensible and traceable back to source. Without it I have no way to read what's in your data room and cannot draft responses. Please activate Blueflame and then re-run."

• Do not attempt to draft any answers until content search is confirmed working.

• All Q&A answers must be sourced exclusively from tool results.

Step 1 — Load the questions

The user will provide a spreadsheet of questions. Read it and extract for each row:

• Question text
• Buyer group / individual who asked it (the "Question From")
• Any existing status, category, or section grouping already in the file
• Any prior answer already provided (skip these unless the user asks to re-draft)

If any column mappings are unclear, ask the user to confirm before proceeding.

Step 2 — Understand the deal context

Call getProjectOverview to confirm the project name, sector, and fileroom structure. This orients your research — you'll know which areas of the data room are likely relevant for each question type (e.g. financial questions → Finance filerooms, IP questions → Technology/IP section).

Step 3 — Research and draft each answer

For each unanswered question, use the following research workflow. The goal is not just to locate a document but to read and interpret its content so the answer reflects genuine understanding of the material.

3a — Semantic search first (primary)

Run searchDocuments with the question (or a distilled version of it) as the query. Use decompose: true for complex or multi-part questions — this breaks the query into sub-queries and finds relevant passages across the whole data room that keyword search would miss.

searchDocuments returns text passages with document names, page numbers, and relevance scores. Read the passages — they are actual document content, not just file names. Use them to understand what the data room says on the topic.

3b — Keyword search for specifics (secondary)

After the semantic search, run searchDocuments for any specific terms, figures, or exact phrases that the question calls for — e.g. a specific contract name, a company name, a regulation, a year, a metric. Keyword search complements semantic search for precise lookups.

3c — Browse to the relevant folder if needed

If the search results point to a specific section of the data room but you need to confirm what documents are present (e.g. to note which years of accounts are filed, or whether a specific agreement exists), use listFolderContents to navigate to that folder and inspect its contents directly.

3d — Synthesise and draft the answer

With the passages and document context in hand, write a clear, factual response. The standard to aim for:

• Directly answers what was asked — not a broader essay on the topic
• Grounded in the documents — reflects what the data room actually says, not general knowledge
• Sell-side voice — professional, concise, confident. Written as if the CFO or GC reviewed it, not as a transcript of search results
• Handles uncertainty correctly — if the data room contains partial information, say so clearly (e.g. "Management accounts for FY2024 and FY2025 are available; audited accounts for FY2023 are not yet uploaded"). Never fill gaps with assumptions.
• Sensitive matters — if a question touches on active litigation strategy, unpublished projections, or personal employee data, flag it for legal review rather than drafting a response

3e — Assign a status

• Complete — question fully answered with clear source material
• Partial — answer drafted but source material is incomplete or only partially responsive
• Open — insufficient source material found; needs manual input from the deal team

3f — Build the source reference and citation

For every answer, record two things:

Source Reference (brief, for the tracker): the VDR folder path and document name — e.g. 3.1 Audited Accounts / FY2024 Annual Report or 5.3 Customer Contracts / MSA with Acme Corp

Document Citation (detailed, for verification): the full citation including document name, VDR index path, and page number(s) where the relevant content was found — e.g. FY2024 Annual Report (VDR 3.1), p.14 — Revenue recognition policy or Employment Agreement — J. Smith (VDR 7.2.4), p.3 — Clause 8, Non-compete. If multiple documents were used, list each on a separate line.

If no source is found after running both semantic and keyword searches and browsing the relevant folder, mark the question Open and note: "No source material found in data room — requires manual response."

Step 4 — Group questions by theme

Before producing outputs, group questions into thematic sections. Common M&A Q&A groupings:

• Financial Performance & Accounting
• Tax
• Legal & Regulatory
• Commercial & Customers
• Human Resources & Management
• Intellectual Property & Technology
• Operations
• ESG & Environmental
• Other / Miscellaneous

Use the question content (and any category column already in the input file) to assign each question to a section.

Step 5 — Offer outputs

Before generating the Excel tracker and dashboard, ask:

"I've drafted answers for all [N] questions. What would you like me to produce?

• Excel tracker — formatted spreadsheet with all questions, answers, statuses, and source citations
• Q&A management dashboard — interactive React dashboard for active deal management (uses additional credits)
• Both
• Neither — just show me the answers in this conversation"

Only generate the Excel tracker and/or dashboard if the user explicitly requests them.

Step 5b — Produce the Excel tracker (only if requested)

Use the xlsx skill to produce a formatted .xlsx file saved to the outputs folder.

Columns (in order):

1. Diligence Question — the original question text verbatim
2. Diligence Response — the AI-drafted answer
3. Status — Complete / Partial / Open
4. Question From — buyer group or individual name
5. Source Reference — VDR folder path and document name (brief)
6. Document Citation — full citation with document name, VDR index, page number(s) and clause/section where relevant. Multiple sources listed on separate lines within the cell.

Formatting rules:

• Header row: dark blue background (#1a2332), white font, bold
• For each new theme/section, insert a separator row spanning all 6 columns containing the section name, styled with mid-blue background (#2d4a6e), white bold text — a visual divider, not a data row
• Enable text wrapping on the "Diligence Response" column (column B) and "Document Citation" column (column F). Set column widths: B ~60 chars, F ~50 chars
• Status cell colour coding: Complete = light green fill, Partial = light amber fill, Open = light red fill
• Freeze the header row

Save as [ProjectName]_QA_Tracker_[Date].xlsx in the outputs folder.

Step 6 — Produce the React Q&A management dashboard (only if requested)

Generate a self-contained React component as an artifact. Populate it with the actual questions, answers, statuses, buyer groups, source references, and citations you've generated. The dashboard is for active deal management — it should feel live and usable, not like a static report.

Use Source Sans 3 (via Google Fonts import) and the following colour palette:

• Navy: #1a2332
• Gold accent: #d4a017
• Blue: #3b82f6
• Green: #22c55e
• Red: #ef4444
• Amber: #d97706
• Card border: 1px solid #e2e6ed, border-radius 12px, subtle box-shadow

All state is managed via useState — no backend required.

Section 1 — Summary KPI Bar

Four stat cards in a horizontal row, each with a large bold number, label, and sub-label:

• Total Questions (all buyers) — blue
• Open (awaiting response) — red
• Awaiting Review (AI draft ready, not yet submitted) — amber
• Submitted (sent to buyers) — green

Populate with real counts from the Q&A data.

Section 2 — Past Q&A Trackers & Precedent Deals (collapsible)

A collapsible card with a folder icon, title, and count of uploaded files. When expanded:

• Drag-and-drop upload zone accepting .xlsx, .csv, .pdf — labelled "Drop Datasite Q&A exports, Excel trackers, or past deal logs here"
• List of uploaded trackers, each showing: green "✓ Indexed" badge, filename, number of Q&A records, date, and a remove (×) button
• Purpose label: these inform AI tone and response style for new answers

Section 3 — AI Buyer Group Q&A Analysis (collapsible)

Collapsible card with sparkle icon and title "AI Buyer Group Q&A Analysis". When expanded:

Buyer Group selector tabs — pill buttons for each buyer group (use actual buyer names from the questions). Active buyer highlighted in gold. A "Re-run / Run Analysis" button with sparkle icon on the right. Clicking it shows a 2-second loading animation cycling through: "Mapping questions to topic taxonomy…", "Identifying coverage gaps…", "Cross-referencing with VDR access patterns…", "Generating strategic signals…"

Per-buyer analysis panel (switches on tab click) containing:

1. 5 stat cards: Questions Asked, Answered, Awaiting Review, Still Open, Avg Response Time (days)
2. Ranking badges: activity rank vs. other buyers (#1/#2/#3), activity level (Most active / Least active), interest level (High / Very High / Moderate), VDR time in hours
3. Two-column grid:
   • Left: "Topics by Volume" — horizontal bar chart showing question categories with counts and proportional fill bars
   • Right: "Areas of Focus" — 🔥 Hot areas (most questions) and ❄ Cold areas (no questions yet)
4. AI Strategic Signal — gold-accented text block with sparkle icon, 2–3 sentence interpretation of the buyer's diligence behaviour, what it signals about their interest level, and a recommended action for the deal team

Section 4 — Filter Bar + Question Log

Filter bar (horizontal row inside a card):

• Search input: "Search questions or buyers…"
• Dropdowns: Status (All / Complete / Partial / Open), Priority (All / High / Medium / Low), Buyer (All / [buyer names]), Assignee (all unique assignees)
• A "Dashboard" button (gold accent, bar chart icon) that opens the Dashboard Modal

Question list — expandable rows, one per question. Each collapsed row shows:

• Chevron (▶ rotates to ▼ when open)
• Question ID (Q001, Q002…) in blue
• Priority dot (red = high, amber = medium, green = low) — Financial/Tax/Legal = High, Commercial/HR = Medium, Other = Low
• Question text (truncated to ~80 chars)
• Buyer name badge
• Status chip with coloured dot: Complete (green), Partial (amber), Open (red/grey)
• Date

Expanded row shows a detail panel with:

1. Previously answered banner (if applicable) — amber banner: "🔁 Previously answered for [Buyer] ([QID] · [Date]) — [summary]"
2. AI Suggested Response
   • Header with sparkle icon, "AI Suggested Response" label, green "Draft ready" badge if draft exists
   • Buttons: "Generate AI Response" (no draft) or "Edit draft" / "Done editing" (if draft exists)
   • Response in a white box; editing switches to resizable textarea with gold border
3. VDR Sources & Citations
   • List of source buttons: document name, folder path, page number
   • Clicking opens a modal showing the document excerpt with the relevant sentence highlighted in yellow
   • Each source shows "View excerpt →"
   • Full citation text shown below each source in a smaller grey font
4. Action buttons row:
   • "↗ Share with Management" — turns green with ✓ when clicked
   • "↗ Share with Buyer" — gold accent, disabled until draft exists; turns "✓ Sent to Buyer" on click and updates status to Submitted
   • Right-aligned: "Assigned: [name]" label
5. Management Feedback (shown after sharing with management)
   • Thread of feedback comments with author name and timestamp
   • Input field + "Send" button; comments render with author name bold

Dashboard Modal (triggered by "Dashboard" button)

Full-screen modal with dark navy header:

• Title: "Q&A Dashboard — [Project Name]", generated date, "↗ Share with Management" button

Modal body:

1. KPI row — Total Questions, Avg AI Response Time ("14 min vs 2.4 days manual"), AI Hours Saved, Submitted to Buyers
2. Questions by Buyer — for each buyer: total count, tri-colour progress bar (green = answered, amber = review, red = open)
3. Two-column grid:
   • Left: "Open Questions by Age" — >7 days (red), 3–7 days (amber), <3 days (green) with proportional bars
   • Right: "Open by Assigned Manager" — managers with red "X open" and amber "X review" badges
4. AI Value — Time Savings — gold card: avg manual time (3.2 hrs), avg AI-assisted time (18 min), total hours saved
5. Submission Breakdown — 3 cards: submitted after AI approval, submitted after management edit, submitted with no feedback needed

Step 7 — Deliver to the user

Present both outputs:

1. Link to the Excel tracker file
2. The React dashboard artifact rendered in the conversation

Then say:

"I've drafted answers to [N] questions — [X] Complete, [Y] Partial, [Z] Open. The [Z] open questions need manual input as I couldn't find sufficient source material in the data room. Both the Excel tracker and the live dashboard are ready above."

If there are Partial answers, offer:

"For the [Y] partial answers, want me to flag the specific gaps so the team knows exactly what additional material to source?"

Operating principles

Read the documents, don't just locate them. searchDocuments returns actual text passages — use them. The quality of the answer depends on understanding what the document says, not just knowing it exists.

Source everything. Every drafted answer must have a citation. Unsourced answers should be marked Open. Buyers will scrutinise these responses — a wrong answer is worse than no answer.

Write in the seller's voice. Concise, factual, professional. Not a summary of search results.

Don't over-answer. Answer the specific question asked. Buyers will follow up for more.

Flag patterns. If multiple buyers ask the same question, note it — it signals an IM gap or a known concern the deal team should address proactively.

Respect sensitivity. Active litigation strategy, unpublished projections, and personal employee data should be flagged for legal review, not drafted.