THE DEAL ROOM · THE ORIGINATION · Nº 1296 · EDITION 1 ·Liquid error (snippets/rm-comps-scraper-card line 27): comparison of String with 0 failed
LUND CARDS · THE DEAL ROOMNº 1296
THE CARD AS TEXT · FOR EYES AND FOR MACHINES
THE COMPS SCRAPER CARD · the comp-set seat — normalizes a messy set of comparables into one clean table
WAKES WHEN a valuation needs a clean, normalized set of comparable companies or deals · a person asks 'clean up these comps', 'normalize the comp set', 'build the comp table' · a messy list of comparables needs standardizing
THE LOOP
intake · the raw comps the person gathered, however messy
normalize · to one currency, one period, one set of metrics; outliers flagged
multiple · each comp's multiples computed consistently
table · the clean comp table with the median, quartiles, and the outliers marked
NEVER
Drops an outlier silently — it flags it and shows the table with and without, for a person to judge
Gives investment advice or tells anyone to buy, sell, invest in, or price a deal
Promises, guarantees, or projects a certain return — outputs are assumptions, not outcomes
Presents an invented number as real — unknown inputs are marked [FILL] for the person's own data
IT MAKES run — normalizes a raw comps CSV, computes multiples consistently, flags outliers; selftest — 10 checks that prove the machine.
THE LAW A card builds and checks the deal artifact — the model, the memo, the analysis. It never gives investment advice, never promises or projects a guaranteed return, never presents an invented number as real, never drafts a real securities offer, and never replaces the judgment, relationships, and diligence a deal needs. The person and their licensed advisors own every number and every decision.
PROOF SELFTEST 10/10 · witnessed in Claude 2026-10-20 on the studio’s own example inputs · the dated run in the box (RUN.md) · Edition 1.
THE SEAL 98 of 100 · LEGENDARY · WITNESSED · Trigger 5 · Machinery 5 · Law 5 · Portability 5 · Proof 5
IT CAN BE WRONG an AI reading a text file: it can be wrong and can invent a number, a rule, a name or a date; check what matters against your own records and the source; the risk is yours. LICENSE-NOTE.md rides in the packet and is the licence.
THE PUNCH · SHA-256 OF SKILL.MD · 1CDC6B8F761F6E271CD9090A
CITE THIS CARDTHE COMPS SCRAPER CARD, Edition 1. Lund Studio LLC, Westminster, Colorado. https://lundr.tech/?view=comps-scraper-card. Punch 1CDC6B8F761F6E271CD9090A. Retrieved 2026-10-20.
What it is.
Normalizes a messy set of comparables into one clean table. Use when a valuation needs a clean, normalized set of comparable companies or deals. Not for deal advice or promised returns. For applying the comp set → THE COMPS CARD.
It carries a machine that shows its working: run — normalizes a raw comps CSV, computes multiples consistently, flags outliers; selftest — 10 checks that prove the machine — 10 checks in its selftest, run in the open below. It never drops an outlier silently — it flags it and shows the table with and without, for a person to judge; never gives investment advice or tells anyone to buy, sell, invest in, or price a deal; never promises, guarantees, or projects a certain return — outputs are assumptions, not outcomes; never presents an invented number as real — unknown inputs are marked [FILL] for the person's own data.
The house law, written into the card.
It is in the card itself, so the AI follows it.
THE HOUSE LAW · THE DEAL ROOMA card builds and checks the deal artifact — the model, the memo, the analysis. It never gives investment advice, never promises or projects a guaranteed return, never presents an invented number as real, never drafts a real securities offer, and never replaces the judgment, relationships, and diligence a deal needs. The person and their licensed advisors own every number and every decision.
THE LIMIT, ON THE TINIt cleans and normalizes the comps you supply; it does not fetch them or judge which are truly comparable — that judgment is yours and sets the whole valuation.
The method.
Intake. The raw comps the person gathered, however messy.
Normalize. To one currency, one period, one set of metrics; outliers flagged.
Multiple. Each comp's multiples computed consistently.
Table. The clean comp table with the median, quartiles, and the outliers marked.
What it does once your AI has it.
run Normalizes a raw comps CSV, computes multiples consistently, flags outliers
selftest 10 checks on the studio’s own example inputs; it must print selftest 10/10
What it will never do.
It never drops an outlier silently — it flags it and shows the table with and without, for a person to judge; never gives investment advice or tells anyone to buy, sell, invest in, or price a deal; never promises, guarantees, or projects a certain return — outputs are assumptions, not outcomes; never presents an invented number as real — unknown inputs are marked [FILL] for the person's own data.
Where it hands off: Applying the comp set → THE COMPS CARD (THE EXCHANGE). The valuation it feeds → THE VALUATION CARD.
It is an AI reading a text file: it can be wrong, so check what matters against your own records and the source. The holder brings their own AI; no endorsement by Anthropic or any other AI company is claimed. Names of other companies and standards are used only to say what the card works with.
What’s in the buy.
SKILL.md — the door your AI reads first: when it wakes, when it does not, the loop, the never-lines, the house law
CARD.md — the whole card in ten sections, §0 to §9 · TIN.md — what is on the tin, in nine lines
scripts/compscraper.py — the machine, Python standard library only, offline; selftest 10/10
RUN.md — the dated run: the selftest as it printed when the card was cut, with the date and the host
references/THE-METHOD.md — the method in plain words, in the card’s own voice
START-HERE.md and system/short-prompt.md — the doors, for any AI with or without skills
MY-LEDGER.md — the card’s memory, on your own machine · LICENSE-NOTE.md — the licence
PROOF · SELFTEST 10/10 · AUDIT 12/12 · WITNESSED IN CLAUDE 2026-10-20 ON THE STUDIO’S OWN EXAMPLE INPUTS · THE TEST PROMPTS IN FRESH CHATS OWED · EDITION 1 · PUNCH 1CDC6B8F761F6E271CD9090A
ON EVERY DOOR · A CARD FOR YOUR AI, A FILE FOR YOUR COMPUTER
In Claude: turn on code execution under Settings › Capabilities, then Customize › Skills › + › Create skill, and upload the zip as it is — START-HERE.md in the box walks you through it, and tells you how to keep the ledger. In ChatGPT, Gemini and the rest: a Project, a GPT or a Gem with the card’s files attached and the short door in the box pasted as its instructions. The words run anywhere an AI reads Markdown; the machines run wherever the host runs Python. Witnessed in Claude only. The host marks →
Take it.
Nº 1296 —Liquid error (snippets/rm-comps-scraper-card line 116): comparison of String with 0 failed
Sold as is under the term printed. A card instructs an AI you operate; results depend on your model, your files and your judgement. Not medical, legal, tax or financial advice, never the person’s boss, and not a licence to practise. Not investment advice, not an appraisal and not an offer to sell securities. The terms →
One payment. The file is yours to keep and keeps working at its edition; new editions issued in the year after you buy reach you by email as replacement files. Tax is added at checkout where it applies. Nothing auto-renews.
AFTER YOU PAY · SIGN IN WITH THE EMAIL YOU PAID WITH · THE CARD OPENS ON MY CARDS → · CHECKED AGAINST ITS FINGERPRINT · NOTHING TO WAIT FOR
A TERM, NOT A SUBSCRIPTION: NOTHING RENEWS ITSELF AND NOBODY IS CHARGED AGAIN. WHEN A TERM ENDS THE FILES STAY ON YOUR COMPUTER AND STAY READABLE — FREEZE, NOT LOSS.
THE MACHINE · IN THE OPEN · FROM THE STUDIO’S RUN OF 2026-10-20
compscraper.py, showing its working.
A small Python program, standard library only. Your AI runs it; you can too. The block below is the machine’s selftest as it printed when the studio ran it from inside the packet, in Claude, on 2026-10-20.
run
normalizes a raw comps CSV, computes multiples consistently, flags outliers · run COMPS.csv [RATES.txt]
selftest
10 checks that prove the machine; it must print selftest 10/10
selftest · AS PRINTED
$ python3 scripts/compscraper.py selftest
wrote COMPS.md — median 10.0x, 1 outlier(s) flagged
wrote COMPS.md — median 5.0x, 0 outlier(s) flagged
REFUSED: comp 'Z' has zero/negative revenue — a multiple would divide by zero; fix the input
REFUSED: no comps — expected company,value,revenue,currency
wrote COMPS.md — median 10.0x, 1 outlier(s) flagged
wrote COMPS.md — median 10.0x, 1 outlier(s) flagged
selftest 10/10
THE SELFTEST RUNS ON THE STUDIO’S OWN EXAMPLE INPUTS, INVENTED FOR THE TEST; NO REAL COMPANY, PERSON OR ACCOUNT IS NAMED.
QUESTIONS AT THE TABLE
Asked before the wire.
What does it need from me?
Your own files and figures, on your own disk. It starts by asking for them: the raw comps the person gathered, however messy. If something it needs is missing, it marks it and says so — it never fills a gap with a guess.
Does it send anything anywhere?
No. The machine is a standard-library Python program that runs on your own computer and sends nothing anywhere; the words run wherever an AI reads Markdown. No server, no account, no key.
What is on the record?
The machine's selftest (10/10), run from inside the packet in Claude on 2026-10-20 on the studio's own example inputs and printed below as it ran; the twelve-check audit (AUDIT.md, 12/12); MANIFEST.md with every file hashed. RUN.md in the box is that run, dated. Still to come, as the next receipt: the card's test prompts asked in fresh chats with the card installed. The punch on the face is the SHA-256 of SKILL.md, so a downloaded copy can be checked against this room.
Can it be wrong?
Yes — it is an AI reading a text file: it can be wrong and can invent a number, a rule, a name or a date; check what matters against your own records and the source; the risk is yours. It cleans and normalizes the comps you supply; it does not fetch them or judge which are truly comparable — that judgment is yours and sets the whole valuation.
What will it never do?
It never drops an outlier silently — it flags it and shows the table with and without, for a person to judge; never gives investment advice or tells anyone to buy, sell, invest in, or price a deal; never promises, guarantees, or projects a certain return — outputs are assumptions, not outcomes; never presents an invented number as real — unknown inputs are marked [FILL] for the person's own data.
