deal-analyzer

deal-analyzer is a skill for Claude Code from DataSift-Ty-Personal/SiftStack. It costs 137 tokens per session (6,688 once invoked), scanned A, original, MIT.

A step-by-step tool for evaluating an investment property, from its address and condition through its likely sale value, repair costs, deal numbers, and offer options. ARV means the estimated value after renovation.

In plain words
What is it for?
It is for analyzing property photos or descriptions, finding comparable sales, estimating renovations, comparing exit plans such as flipping or renting, and deciding what to offer.
Why use it?
It brings valuation, repair estimates, profit calculations, and offer planning into one analysis so investors do not have to connect separate estimates themselves.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the deal-analyzer plugin — 3 skills, 1 command shipped together

Good fit It is for analyzing property photos or descriptions, finding comparable sales, estimating renovations, comparing exit plans such as flipping or renting, and deciding what to offer.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/datasift-ty-personal/siftstack/deal-analyzer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add DataSift-Ty-Personal/SiftStack --skill deal-analyzer
Clone the repo
git clone --depth 1 https://github.com/DataSift-Ty-Personal/SiftStack

Made for: Claude Code.

Or install deal-analyzer, the plugin that ships this one along with the rest of its 3 skills, 1 command.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for deal-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/deal-analyzer/github.svg)](https://agentmods.dev/skills/datasift-ty-personal/siftstack/deal-analyzer)
Your own site
<a href="https://agentmods.dev/skills/datasift-ty-personal/siftstack/deal-analyzer"><img src="https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/deal-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for deal-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/datasift-ty-personal/siftstack/deal-analyzer"><img src="https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/deal-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 137 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,688 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00137 $0.06688
Opus 5.5 $0.00055 $0.02675
Sonnet 5.5 $0.00027 $0.01338
Haiku 4.5 $0.00014 $0.00669

Measured 2mo ago against content hash 9426e15fc2d1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

deal-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/deal-analyzer/skills/deal-analyzer/SKILL.md · 512 lines

How it starts

The opening of the file, as written. The whole thing — 512 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deal Analyzer — Full Property Analysis Pipeline

Orchestrate a complete investment property analysis from raw photos and an address through to ARV, rehab cost, deal math, and offer strategy. This skill ties together the real-estate-comping skill (for valuation) and the rehab-estimator skill (for renovation costs) into one streamlined pipeline.

The user should walk away with a clear picture: what's it worth, what does it cost to fix, what should I offer, and which exit strategy makes more money.

Pipeline Overview

INTAKE → PHOTO ANALYSIS → COMP ANALYSIS → REHAB ESTIMATE → DEAL MATH → OFFER & EXIT STRATEGY → DELIVERABLES

Each phase feeds into the next. Data flows forward — comp findings inform rehab scope, rehab costs feed deal math, and deal math drives the offer.

Phase 1: Intake

Collect from the user:

Required:

  • Property address (full: street, city, state, zip)
  • Property photos OR condition description (photos strongly preferred)

Helpful (ask if not provided):

  • Square footage / bed / bath / year built (can be researched if address is given)
  • Number of units (default: 1)
  • Occupied? (Y/N) — affects hold time and eviction/vacancy considerations
  • Purchase price or contract price (needed for deal math)
  • Current "As Is" Value (if known — useful for wholesaling spread analysis)
  • Known issues (roof, foundation, HVAC, etc.)
  • Financing structure (supports multiple loans — see Phase 5 for details):
    • First Mortgage / primary lender terms (amount or LTV, rate, points)
    • Second Mortgage / Gap Fund / Private Money (if applicable)
    • Miscellaneous financing or liens (if applicable)
    • If not provided, defaults to 100% LTV hard money on purchase + rehab as a single first mortgage
  • Exit strategy preference (or analyze both flip and wholetail)
  • Evaluator name (for report attribution)
  • Property description (e.g., "Off Market Lead", "MLS Listing", "Driving for Dollars")

If the user only provides an address: Use web search and browser tools to look up the property on Zillow, Redfin, or county records to gather:

  • GLA, bed/bath, year built, lot size
  • Any available listing photos (for condition assessment)
  • Tax records for annual property tax amount

Read the full file on GitHub · 512 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 512 lines · 137 tokens per session scan A 9426e15fc2d1

Subscribe to this mod's changes

deal-analyzer is a skill published in the GitHub repository DataSift-Ty-Personal/SiftStack (23 stars, last pushed 23d ago), licensed MIT. It adds 137 tokens to every session and 6,688 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

deal-analyzer compared with skills from other repositories

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