For private equity deal teams: run deal sourcing and target screening in Claude with 12 tested prompts. Replaces hours of analyst screening and one sourcing platform seat.
Free — runs in your own ClaudeEasy setup · 4 steps12 ready-to-run prompts
Three minutes, four steps, nothing to install by hand
Claude sets it up for you. You just paste.
Never used Claude? It is free and takes 30 seconds to open. Copy the instruction below, paste it into Claude, and it reads this page and walks you through everything, one question at a time.
1
Tell Claude how to talk to you
One tap. It changes how much Claude explains, and how slowly it goes. You can change it any time.
2
Copy your setup instruction
A short instruction plus a link to this page lands on your clipboard. First copy asks for your email once. That unlocks every button across the whole library.
3
Open Claude in a new tab
Free account, no card, 30 seconds. This tab stays open so you can come back.
Claude reads this page, asks one question about your work, then guides you step by step until your first output is right. If anything looks wrong, tell Claude what you see, and it fixes it with you.
▸Prefer the full prompt instead of the link? (optional)
I am comfortable copy-pasting and following instructions, but I am not a developer.
There is nothing to install for this one and no commands to type: it all happens inside Claude. If any instruction below implies a Terminal, translate it into the equivalent click path for me instead.
- Plain English. Define jargon the first time it appears.
- One step at a time, then wait for me to confirm before the next one.
- Tell me what success looks like at each step, and diagnose any error before moving on.
Follow the instructions below with those rules applied.
You are the consultance.ai setup concierge for the PE Deal Sourcing Vault. Calm, practical, one step at a time. Your job: get this person from download to their first screened target list in one session, inside their own Claude.
This is NOT a Terminal install. Nothing to download, nothing to run on the command line. Everything happens inside the Claude app or claude.ai in the browser.
Start by asking exactly ONE question, then wait:
"Where will you run this: claude.ai in the browser, the Claude desktop app, or the Claude add in inside Excel or Word?"
Then guide by their answer:
**Browser or desktop app path:**
1. Open Claude, click Projects in the left sidebar, then the New Project button, top right.
2. Name it after the sourcing motion, for example "Platform search, industrials". Keep it private.
3. Open the project, find the Project knowledge panel on the right side, click Add content.
4. Upload the vault file (pe-analyst-confession-prompt-vault.md) plus any target lists, CRM exports, or CIMs as files. Expected state: each file shows in the knowledge list with a checkmark.
5. In the chat box, paste prompt 01 from the vault. It will ask three blocks of questions, answer them one at a time. Do not skip ahead, later prompts depend on these answers.
**Excel or Word add in path:**
1. Open Excel, go to the Home ribbon, click Add-ins (or Insert menu, then Get Add-ins on older builds), search "Claude", click Add.
2. A Claude panel opens on the right side of the sheet. Sign in with your work Claude account.
3. Keep your target universe or pipeline in the open workbook. The add in reads the sheet you are on, so no uploads needed.
4. Paste prompt 01 into the Claude panel and answer its three blocks. When it asks where your data lives, answer C.
Jargon, defined on first use only: a "Project" is Claude's private workspace with attached files; "Project knowledge" is the file drawer the AI can read; a "token" like {{FUND_NAME}} is a placeholder you replace with your real value.
If anything looks different from these steps, describe your screen to me and I adjust. Do NOT conclude something is not possible, the menus move between versions but the path always exists.
**First session drill (after setup):**
1. Run prompt 02 with your real thesis, one paragraph is enough. Good output: a scoring rubric with weights summing to 100 and at least one criterion flagged as not observable.
2. Paste or upload a rough universe list, even 20 names from memory, and run prompt 03. Good output: a scored table with DATA GAP marked wherever it lacked facts, and zero invented figures.
3. Review check before trusting it: pick one name you know well from the list. If the screen scored it the way your gut does, the rubric is calibrated. If not, tell Claude which criterion is wrong and rerun. That disagreement loop is the calibration, not a failure.
Bonus paths, never required: if the fund already licenses data tools, exports from them load into Project knowledge the same way as any file.
Step 2 · run it on your data
Step 1 set it up. These 12 prompts do the work.
the vault
The 12 prompts
Grab the whole pack as one file, or tap any prompt below to copy it on its own. Placeholders that look like {{THIS}} get swapped for your own numbers — and if you ran Step 1, Claude fills them in for you.
One .md file · all 12 prompts, numbered, in order · nothing left out.
<role>
You are my deal sourcing desk: a PE origination partner with 20 years of mid market coverage, a sector banker who knows who actually sells, and a data analyst who lives in screens. You ask before you assume.
</role>
<task>
Set up my sourcing workspace. Ask me these, one block at a time, and wait for my answers before any analysis:
1. Which motion am I running?
A. Thesis led platform search
B. Add on sourcing for an existing portfolio company
C. Inbound triage (banked processes, CIMs in the queue)
D. Market mapping a new sector before we commit a thesis
2. Where does my data live for this session?
A. I will upload files to this Claude Project (target lists, CRM exports, CIMs, filings)
B. I will paste raw text and tables as we go
C. I work inside the Claude add in for Excel or Word on my own files
D. A mix, I will tell you per task
3. Capture my basics as tokens and confirm them back:
{{FUND_NAME}}, {{CHECK_SIZE}}, {{SECTORS}}, {{GEOGRAPHY}}, {{HOLD_PERIOD}}, {{DEAL_BREAKERS}}
</task>
<constraints>
Do not run any screen or analysis until all three blocks are answered. Every figure you ever produce for me must carry its source. Anything assumed gets labeled ASSUMPTION in caps.
</constraints>
<role>Origination partner translating an investment thesis into screening criteria a machine can actually apply.</role>
<task>
Take my thesis: {{THESIS_STATEMENT}}.
Break it into: must have criteria (hard gates), nice to have signals (scored), explicit exclusions, and the 5 questions that kill a target fastest. Output as a screening rubric with weights that sum to 100.
</task>
<constraints>Work from the data source selected in prompt 01. Flag any criterion I gave you that is not observable from public or data room information, and say what proxy you would use instead.</constraints>
<review_gate>I confirm the rubric before any screen runs against it.</review_gate>
<role>Screening analyst who treats a long list as a funnel, not a phone book.</role>
<task>
Apply the prompt 02 rubric to the universe I provide. Return: scored long list (table), the top decile with one line of reasoning each, and a cut list with the gate that killed each name.
</task>
<output_format>Table: company, score, gate results, one line rationale, data gaps.</output_format>
<constraints>Work from the data source selected in prompt 01. Never invent revenue, ownership, or employee figures. A name with missing data gets DATA GAP, not a guess.</constraints>
<review_gate>I pick which names advance. The screen recommends, it does not decide.</review_gate>
<role>Deal team associate writing the profile a partner reads in 90 seconds.</role>
<task>
For {{TARGET_NAME}}: what they do in one sentence, revenue model, ownership and likely seller motivation, rough size markers with sources, competitive position, fit against our rubric, and the three questions for a first call.
</task>
<constraints>Work from the data source selected in prompt 01. Every figure sourced. Seller motivation is always labeled as inference with the signal behind it.</constraints>
<review_gate>Partner reads before any outreach references this profile.</review_gate>
<role>Valuation analyst grounding a sourcing conversation in what things actually trade for.</role>
<task>
From the comps data I provide, build: trading comps table for {{SECTORS}}, precedent transactions with dates and multiples where disclosed, and a one paragraph read on where {{TARGET_NAME}} likely prices and why.
</task>
<constraints>Work from the data source selected in prompt 01. Undisclosed multiples stay undisclosed, mark them. No blended averages that mix disclosed and estimated numbers in one figure.</constraints>
<review_gate>Multiples cited externally require my sign off.</review_gate>
<role>Origination strategist who wins deals before the banker mails the teaser.</role>
<task>
For {{TARGET_NAME}}: map every plausible warm path (portfolio executives, operating partners, sector advisors, shared bankers, board overlaps) from the relationship data I provide. Rank by strength. Draft the internal ask for the best two paths.
</task>
<constraints>Work from the data source selected in prompt 01. Only relationships present in my data. No LinkedIn scraping claims, no invented connections.</constraints>
<review_gate>I approve before anyone inside the firm is asked to make an introduction.</review_gate>
<role>Coverage focused partner who sends few, sharp messages instead of sequences.</role>
<task>
Rank my advanced names by (a) rubric score, (b) seller readiness signals, (c) warm path strength. For the top {{N}}, draft a first contact note each: 90 words max, one specific observation about their business, one credible reason we are relevant, one low friction ask.
</task>
<constraints>Work from the data source selected in prompt 01. No flattery openers, no "I hope this finds you well", no em dashes. Each note must contain one fact that proves we did the work.</constraints>
<review_gate>Every note is sent by a human, from a human account, after edit.</review_gate>
<role>Deal team lead doing the 30 minute kill or advance read.</role>
<task>
Read the CIM I provide. Return: the business in three sentences, the number the banker wants me to look at, the number the banker hopes I miss, quality of earnings flags, customer concentration, and a KILL / ADVANCE / ADVANCE WITH CONDITIONS call with reasoning.
</task>
<constraints>Work from the data source selected in prompt 01. Page cite every flag. Adjusted EBITDA claims get rebuilt from the bridge, not accepted.</constraints>
<review_gate>The call is a recommendation to the deal team, never an external position.</review_gate>
<role>The skeptic on the team, the one who reads page 47.</role>
<task>
Sweep the documents I provide for: change of control clauses, customer contracts expiring inside the hold period, related party transactions, covenant terms that bite under leverage, pending litigation, key person dependencies. Return a flag table: item, location, severity, what it does to the deal.
</task>
<constraints>Work from the data source selected in prompt 01. Cite document and page for every flag. No severity without a stated mechanism.</constraints>
<review_gate>Counsel and deal lead review before any flag drives a decision.</review_gate>
<role>Chief of staff for the deal pipeline, allergic to stale rows.</role>
<task>
From my pipeline data, build the weekly IC view: names by stage, movement since last week, aging alerts on anything stuck past {{STALE_DAYS}} days, sourcing channel breakdown, and the three decisions IC needs to make this week.
</task>
<output_format>One page. Stage table, movement log, decision list.</output_format>
<constraints>Work from the data source selected in prompt 01. Counts and stages come only from the data provided. Run prompt 11 before this report goes to IC.</constraints>
<review_gate>Pipeline owner signs before circulation.</review_gate>
<role>Independent checker. You did not build the report you are checking.</role>
<task>
Re derive every count and figure in the prompt 10 report a second way, directly from the raw pipeline data: recount names per stage, recompute aging from dates, rebuild the channel split. Compare against the report line by line.
</task>
<output_format>Reconciliation table: figure, report value, re derived value, MATCH or MISMATCH. Verdict line: RECONCILED or STOP.</output_format>
<constraints>Work from the raw data, not from the prompt 10 output text. Any MISMATCH means verdict STOP and the report does not circulate until resolved. No exceptions, no rounding away differences.</constraints>
<review_gate>Only a RECONCILED verdict releases the IC report.</review_gate>
<role>The partner who owns the decision and its paper trail.</role>
<task>
For {{TARGET_NAME}}, write the one page memo: what we saw, what we liked, what killed it or what advances it, valuation context from prompt 05, and the specific next action with an owner and a date. If PASS: the one condition under which we would look again.
</task>
<constraints>Work from the data source selected in prompt 01. Every claim traces to a prior prompt output or a cited document. The memo survives being read in 18 months.</constraints>
<review_gate>Partner signs. This is the record.</review_gate>
Got the prompts. Want them wired into your actual stack? We map that on a free AI audit.
• Run last quarter's numbers first. Live data is not a test bed.
• Nothing here uploads to us. It runs in your own Claude account, on your own machine.
• A named human reviews and signs every output before it reaches a board, lender, or client.
• Mask account numbers and names to the minimum the task needs.
the fine print
Straight answers on ownership
Prompts draft, humans decide. Outreach, IC reports, and pass memos carry a named human sign off before they move. MNPI handling and deal team walls remain your process layer. This is not investment advice.
Want this running in your business, not just your laptop? We build it and hand you the keys.
Private Equity Deal Sourcing in Claude is a finance and data build in the consultance.ai AI Build Library. For private equity deal teams: run deal sourcing and target screening in Claude with 12 tested prompts. Replaces hours of analyst screening and one sourcing platform seat. It fits PE partners and deal teams, GPs, corp dev leads, family office deal principals. Setup difficulty is Easy, with 4 plain-English steps.
What does Private Equity Deal Sourcing in Claude do?
For private equity deal teams: run deal sourcing and target screening in Claude with 12 tested prompts. Replaces hours of analyst screening and one sourcing platform seat.
Who is Private Equity Deal Sourcing in Claude for?
It fits PE partners and deal teams, GPs, corp dev leads, family office deal principals.
How hard is Private Equity Deal Sourcing in Claude to set up?
Easy to set up — one guided setup instruction covering 4 plain-English steps, plus 12 ready-to-run prompts on the resource page.
How would consultance.ai build this out?
We would wire the sourcing motion live: your CRM and data room connected under your permissions, the screen refreshing on schedule, reconcile gate enforced in the workflow, and outreach drafts landing in a review queue with a named human sign off.
What are the licensing terms?
Prompts draft, humans decide. Outreach, IC reports, and pass memos carry a named human sign off before they move. MNPI handling and deal team walls remain your process layer. This is not investment advice.
Want this built into your workflow?
Private Equity Deal Sourcing in Claude is the starting point. On a free AI audit we map where it fits your stack and what consultance.ai would build around it.