🏘️ Real Estate · Deal Analysis

Pull comps that actually justify price

Comparable selection by similarity and recency, adjusted transparently.

foundation~25 minAgentsInvestorsProperty Managers

Steps

1Filter to same submarket within 0.5mi and 90 days where inventory allows
2Match on bed/bath/GLA/lot first; style second
3Adjust for condition differences with documented per-item estimates
4Drop outlier sales unexplained by visible factors
5Weight closest-and-newest heaviest; show the grid
6State confidence range; thin comp sets widen it honestly

Common Pitfalls

▲Cherry-picked high comps justifying wishful list prices
▲Foreclosures mixed silently into arms-length sets

Commands

Install with skills CLI

$ npx skills add aniruddhaadak80/skills --skill deal-analysis-comps-analysis-rigorous

Install globally

$ npx skills add aniruddhaadak80/skills --skill deal-analysis-comps-analysis-rigorous -g

Tags

#comps#valuation#market#real-estate#deal-analysis

Install this skill

$ npx skills add aniruddhaadak80/skills --skill deal-analysis-comps-analysis-rigorous -a opencode

SKILL.md

# Pull comps that actually justify price

> Comparable selection by similarity and recency, adjusted transparently.

## When to Use This Skill

Comparable selection by similarity and recency, adjusted transparently.

## Steps

1. Filter to same submarket within 0.5mi and 90 days where inventory allows
2. Match on bed/bath/GLA/lot first; style second
3. Adjust for condition differences with documented per-item estimates
4. Drop outlier sales unexplained by visible factors
5. Weight closest-and-newest heaviest; show the grid
6. State confidence range; thin comp sets widen it honestly

## Common Pitfalls

- Cherry-picked high comps justifying wishful list prices
- Foreclosures mixed silently into arms-length sets

View source on GitHub ↗

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