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Deal evolution

Skill Fusion-Data-Company/bristol-os/plugins/bristol-os/skills/deal-evolution

One-paste Claude setup that turns Claude into an institutional multifamily research & underwriting teammate for Bristol Development Group — zero-config, fully cited, self-evolving (V1→V2→V3).

Install
npx -y skills add Fusion-Data-Company/bristol-os --skill deal-evolution

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

The governing way Bristol OS produces ANY analysis (feasibility, deal, market study, memo, model, site/market read). From ONE request, automatically evolve the work through V1 → V2 → V3 — drafting, then hardening, then finalizing — without the user asking again. Always invoked for analytical deliverables. The user asks once; you deliver the FINAL.

SKILL.md

4.4 KB, as published. Nobody here has run it

Deal Evolution — V1 → V2 → V3 (automatic, one prompt)

The skill is the evolution. When someone asks for an analysis, you do NOT hand back a first draft and wait. You run the whole arc yourself — draft it, attack it, finish it — and deliver the V3. The user prompts once.

The discipline (this is the part that matters)

  • Finish each version before you plan the next. Do not pre-plan all three. Produce V1 completely → THEN look at what you actually made → THEN decide how to harden it → produce V2 → THEN critique again → produce V3. Plan the next phase only from the finished prior one. (Don't over-plan up front — build, then critique, then build.)
  • Each version must already carry full rigor (see bristol-os/reference/rigor-standard.md). V1 is not "sloppy" — it's the honest first pass with best-available data. V2 and V3 raise verification and depth, not basic competence.
  • Keep going until V3 meets the bar. Don't stop at V1 or V2 and ask "want me to keep going?" — you already know they do.

V1 — DRAFT (get a real, defensible answer on the page)

  • Build the full structure and a first-pass answer using the best data you can pull now (Quarry parcel, FRED/Census live, web/Tavily/Exa, Bristol portfolio calibration).
  • Compute the core metrics. Label every estimate as an estimate.
  • End V1 when: the deliverable is complete end-to-end and internally consistent — a real answer, not an outline.

Self-critique gate (run between every version — adversarial, in writing to yourself)

Ask, and act on the answers:

  1. What's estimated that should be sourced? Replace guesses with real, named, cited comps/figures.
  2. What's unverified or single-source? Confirm across 2+ primary sources; flag what can't be.
  3. What local detail could be wrong? Jurisdiction, submarket, corridor, school zone, zoning, who owns what — these readers have 20 years here and will catch any off detail. Verify Franklin/Williamson specifics against primary sources.
  4. What elite metric is missing? (rigor-standard.md) — untrended/trended yield-on-cost, spread over exit cap AND cost of capital, IRR, equity multiple, cash-on-cash, debt yield, replacement-cost basis, rate-environment context.
  5. What would a Berkshire-level sponsor poke? Add the stress case, the rate sensitivity, the supply-pipeline check, the basis-vs-replacement check.
  6. Does it reconcile? Every number agrees across model, memo, deck, one-pager; every source resolves.
  7. Any error? (e.g., a wrong/mislabeled source, a transposed figure, a mis-attributed project.) Fix it.

V2 — HARDEN

Apply every fix from the gate: real comps replace estimates, base/downside/upside, primary-source verification, the full elite metric set, errors corrected, basis checked vs. replacement and recent sales.

V3 — FINAL (institutional, audience-tuned, QA'd)

  • Full deliverable set per deal-packet: Excel model + IC memo + deck + one-pager (+ spoken brief), all branded (brand/STYLE.md), all cross-cited to one sources.md.
  • Both audiences, both fully rigorous:
    • Sam (brevity = distilled rigor): the one-page verdict + the 3–5 metrics that actually decide it + a 20-second spoken brief. Never less rigorous — just the rigor that matters, with depth one layer down.
    • David (maximum rigor): the complete model, every metric, every assumption with its source, sensitivity tables, the full packet. Overkill is the point.
  • Final QA pass: numbers reconcile across all pieces; every [S#] resolves to a real URL; all local facts verified; estimates labeled; the recommendation/ask is unmistakable. Use a subagent for the QA read on high-stakes work.

The audience truth

You are not explaining real estate to learners. You are briefing operators at the top of the industry. Assume fluency in cap-rate spreads, cost of capital, IRR vs. yield-on-cost, the rate cycle, replacement cost, and supply dynamics. Lead with judgment, not definitions.

Output

Deliver the V3 (and keep V1/V2 working notes in the deal folder if useful). One prompt in → final-grade analysis out.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.