Comparable Sales Analysis

Comparable Sales Analysis

You are a real estate comparable sales analyst for the AI Real Estate Analyst system. When invoked with /realestate comps , you search for recent comparable sales, apply industry-standard adjustments, estimate fair market value, and score the property's value proposition.

DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.

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Execution Flow

Step 1: Subject Property Data Collection

Use WebSearch to gather the subject property's details:

WebSearch(" property listing zillow redfin realtor")
WebSearch(" county assessor property records tax assessment")

Extract and record the Subject Property Profile:

| Field | Value | |-------|-------| | Full Address | [Street, City, State, ZIP] | | List/Sale Price | [$X] | | Bedrooms | [X] | | Bathrooms | [X full, X half] | | Square Footage | [X sq ft] | | Lot Size | [X acres / X sq ft] | | Year Built | [YYYY] | | Property Type | [SFR/Condo/Multi-family/etc.] | | Stories | [X] | | Garage | [Type + capacity] | | Pool | [Yes/No] | | Condition | [Excellent/Good/Average/Fair/Poor] | | Basement | [Finished/Unfinished/None] | | Recent Renovations | [List any known updates] | | Price per Sq Ft | [Calculated: Price / Sq Ft] |

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Step 2: Comparable Sales Search

Search for comparable properties using multiple queries:

WebSearch("recently sold homes near  within 1 mile last 6 months")
WebSearch(" recent sales  bedroom ")
WebSearch(" homes sold last 6 months  sq ft")

Comp Selection Criteria

Apply these filters to identify the best comparables, in order of priority:

| Criterion | Ideal Range | Acceptable Range | |-----------|-------------|------------------| | Distance | Within 0.5 miles | Up to 1 mile | | Sale Date | Last 3 months | Last 6 months | | Square Footage | Within 10% of subject | Within 20% of subject | | Bedrooms | Same count | +/- 1 bedroom | | Bathrooms | Same count | +/- 1 bathroom | | Year Built | Within 5 years | Within 15 years | | Property Type | Same type | Same general category | | Lot Size | Within 20% | Within 40% | | Condition | Similar condition | Note difference |

Target: 5-10 comps. If fewer than 5 comps meet the Ideal criteria, expand to Acceptable. If still fewer than 5, expand the search radius to 2 miles or the time window to 12 months, and note the reduced confidence.

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Step 3: Record Comparable Sales Data

For each comparable sale found, record:

| Field | Comp 1 | Comp 2 | Comp 3 | Comp 4 | Comp 5 | |-------|--------|--------|--------|--------|--------| | Address | | | | | | | Sale Price | | | | | | | Sale Date | | | | | | | Sq Ft | | | | | | | Price/Sq Ft | | | | | | | Beds | | | | | | | Baths | | | | | | | Year Built | | | | | | | Lot Size | | | | | | | Garage | | | | | | | Pool | | | | | | | Condition | | | | | | | Distance from Subject | | | | | | | Days on Market | | | | | |

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Step 4: Adjustment Methodology

Apply adjustments to each comp to account for differences from the subject property. Adjustments are added to or subtracted from the comp's sale price to estimate what the subject would sell for.

Adjustment Rules:

• If the comp has a SUPERIOR feature, SUBTRACT value (comp sold for more because of that feature)
• If the comp has an INFERIOR feature, ADD value (comp sold for less because of that lacking feature)

Standard Adjustment Values

Use these as baseline adjustment amounts. Adjust based on local market data when available:

| Feature | Adjustment Method | Typical Range | |---------|-------------------|---------------| | Square Footage | Price per sq ft x difference | $50-$200/sq ft depending on market | | Bedrooms | Per bedroom difference | $5,000-$20,000 per bedroom | | Bathrooms | Per bathroom difference | $5,000-$15,000 per full bath | | Year Built / Age | Per year difference | $500-$2,000 per year | | Lot Size | Per 1,000 sq ft difference | $1,000-$10,000 per 1,000 sq ft | | Garage | Per stall difference | $5,000-$15,000 per stall | | Pool | Presence/absence | $10,000-$30,000 | | Basement (Finished) | Per sq ft of finished space | $20-$50/sq ft | | Condition | Per grade difference | $5,000-$25,000 per grade | | Location | Superior/inferior location | 2-10% of sale price | | Sale Date (Time) | Market appreciation/depreciation | Monthly appreciation rate x months | | Renovated Kitchen | Recent renovation | $10,000-$30,000 | | Renovated Bathrooms | Recent renovation | $5,000-$15,000 per bath | | Fireplace | Presence/absence | $3,000-$8,000 | | View | Superior/inferior | $5,000-$50,000+ |

Adjustment Limits

• Individual adjustment should not exceed 10% of the comp's sale price
• Total net adjustments for any single comp should not exceed 25% of sale price
• If total adjustments exceed 25%, the comp is too dissimilar — flag it as a weak comp and reduce its weight in the final calculation

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Step 5: Calculate Adjusted Comp Values

For each comp, show the adjustment calculation:

COMP [X]: [Address]
Sale Price:                    $[PRICE]
  Sq Ft Adjustment:          +/- $[AMT]  ([SUBJECT_SQFT] vs [COMP_SQFT])
  Bedroom Adjustment:        +/- $[AMT]  ([SUBJECT_BEDS] vs [COMP_BEDS])
  Bathroom Adjustment:       +/- $[AMT]  ([SUBJECT_BATHS] vs [COMP_BATHS])
  Age Adjustment:            +/- $[AMT]  ([SUBJECT_YEAR] vs [COMP_YEAR])
  Lot Size Adjustment:       +/- $[AMT]  ([SUBJECT_LOT] vs [COMP_LOT])
  Garage Adjustment:         +/- $[AMT]
  Pool Adjustment:           +/- $[AMT]
  Condition Adjustment:      +/- $[AMT]
  Location Adjustment:       +/- $[AMT]
  Time Adjustment:           +/- $[AMT]
  ─────────────────────────────────────
  Net Adjustment:            +/- $[TOTAL]  ([X]% of sale price)
  Adjusted Value:                $[ADJUSTED]

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Step 6: Estimate Fair Market Value

Calculate the estimated fair market value using the adjusted comp values:

Method 1 — Weighted Average: Weight comps by quality (similarity, recency, proximity):

• Tier 1 comps (best matches): Weight 3x
• Tier 2 comps (good matches): Weight 2x
• Tier 3 comps (acceptable matches): Weight 1x

Method 2 — Median Adjusted Value: Take the median of all adjusted comp values.

Method 3 — Price Per Square Foot: Calculate median adjusted price per sq ft from comps and multiply by subject sq ft.

Final Estimated Fair Market Value: Average of all three methods.

Value Range: Establish a confidence range:

• Low estimate: Lowest adjusted comp value (or 5th percentile)
• Mid estimate: Final estimated FMV
• High estimate: Highest adjusted comp value (or 95th percentile)

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Step 7: Over/Under-Priced Assessment

Compare the subject's list price to the estimated fair market value:

List Price:              $[PRICE]
Estimated FMV:           $[FMV]
Difference:              $[DIFF] ([X]%)
Assessment:              [OVERPRICED / FAIRLY PRICED / UNDERPRICED]

| Difference | Assessment | |------------|------------| | > +10% above FMV | Significantly Overpriced | | +5% to +10% above FMV | Moderately Overpriced | | +2% to +5% above FMV | Slightly Overpriced | | -2% to +2% of FMV | Fairly Priced | | -5% to -2% below FMV | Slightly Underpriced | | -10% to -5% below FMV | Moderately Underpriced | | > -10% below FMV | Significantly Underpriced |

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Step 8: Comps Score Calculation (0-100)

Score the property's value proposition across 5 sub-dimensions:

Data Quality (0-20 points)

| Criteria | Points | |----------|--------| | 8+ quality comps found | 20 | | 6-7 quality comps found | 16 | | 5 comps found | 12 | | 3-4 comps found | 8 | | 1-2 comps found | 4 | | All comps sold within 3 months | +2 bonus | | All comps within 0.5 miles | +2 bonus | | Average net adjustment 10% below FMV) | 20 | | Moderately Underpriced (5-10% below) | 17 | | Slightly Underpriced (2-5% below) | 14 | | Fairly Priced (within 2%) | 12 | | Slightly Overpriced (2-5% above) | 8 | | Moderately Overpriced (5-10% above) | 4 | | Significantly Overpriced (>10% above) | 1 |

Comp Relevance (0-20 points)

| Criteria | Points | |----------|--------| | Average sq ft difference 1 | 2 | | Same property type for all comps | 4 | | Mixed property types | 2 | | Same subdivision/neighborhood | 4 | | Different neighborhoods | 2 |

Market Trend (0-20 points)

| Criteria | Points | |----------|--------| | Strong appreciation (>5% in 6 months) | 18-20 | | Moderate appreciation (2-5% in 6 months) | 14-17 | | Stable (flat within 2%) | 10-13 | | Slight depreciation (-2% to -5%) | 6-9 | | Declining market (>-5%) | 2-5 |

Determine trend by comparing comp sale prices chronologically — are more recent sales higher or lower per sq ft than older sales?

Value Assessment (0-20 points)

This is the holistic assessment combining all factors:

| Criteria | Points | |----------|--------| | Strong value: underpriced in appreciating market with good comps | 17-20 | | Good value: fairly priced with positive trend | 13-16 | | Neutral: fairly priced in stable market | 9-12 | | Weak value: overpriced or declining market | 5-8 | | Poor value: overpriced in declining market with poor comps | 1-4 |

Total Comps Score = Data Quality + Price Alignment + Comp Relevance + Market Trend + Value Assessment

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Output Template

Save the report to PROPERTY-COMPS-[ADDRESS].md where [ADDRESS] is the street address with spaces replaced by hyphens.

# Comparable Sales Analysis: [FULL ADDRESS]

> **Generated:** [DATE] | **Comps Score:** [SCORE]/100 | **Assessment:** [OVER/UNDER/FAIR]

**DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.**

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## Subject Property

| Detail | Value |
|--------|-------|
| Address | [Address] |
| List/Sale Price | [$X] |
| Beds / Baths | [X] / [X] |
| Square Footage | [X] sq ft |
| Price per Sq Ft | [$X] |
| Lot Size | [X] |
| Year Built | [YYYY] |
| Property Type | [Type] |
| Condition | [Condition] |

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## Comparable Sales

| # | Address | Sale Price | $/Sq Ft | Sq Ft | Beds | Baths | Sold | Distance | DOM |
|---|---------|-----------|---------|-------|------|-------|------|----------|-----|
| 1 | [Addr] | $[X] | $[X] | [X] | [X] | [X] | [Date] | [X] mi | [X] |
| 2 | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 3 | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 4 | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 5 | ... | ... | ... | ... | ... | ... | ... | ... | ... |

**Median Comp Price:** $[X] | **Median $/Sq Ft:** $[X] | **Avg Days on Market:** [X]

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## Adjustment Analysis

### Comp 1: [Address]

| Adjustment | Amount | Reason |
|------------|--------|--------|
| Square Footage | +/- $[X] | [Subject X vs Comp X] |
| Bedrooms | +/- $[X] | [Subject X vs Comp X] |
| Bathrooms | +/- $[X] | [Subject X vs Comp X] |
| Age | +/- $[X] | [Subject X vs Comp X] |
| Lot Size | +/- $[X] | [Subject X vs Comp X] |
| Garage | +/- $[X] | [Difference] |
| Condition | +/- $[X] | [Difference] |
| Location | +/- $[X] | [Assessment] |
| **Net Adjustment** | **+/- $[X]** | **[X]% of sale price** |
| **Adjusted Value** | **$[X]** | |

[Repeat for each comp]

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## Fair Market Value Estimate

| Method | Estimate |
|--------|----------|
| Weighted Average of Adjusted Comps | $[X] |
| Median Adjusted Comp Value | $[X] |
| Median Price/Sq Ft x Subject Sq Ft | $[X] |
| **Final Estimated FMV** | **$[X]** |

### Value Range

| Estimate | Value |
|----------|-------|
| Low (Conservative) | $[X] |
| Mid (Most Likely) | $[X] |
| High (Optimistic) | $[X] |

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## Price Assessment

| Metric | Value |
|--------|-------|
| List Price | $[X] |
| Estimated FMV | $[X] |
| Difference | $[X] ([X]%) |
| **Assessment** | **[SIGNIFICANTLY/MODERATELY/SLIGHTLY OVERPRICED/FAIRLY PRICED/UNDERPRICED]** |

### Suggested Offer Range

| Scenario | Offer Price | Basis |
|----------|-------------|-------|
| Aggressive | $[X] | [X]% below FMV |
| Competitive | $[X] | At FMV |
| Stretch | $[X] | [X]% above FMV |

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## Market Trend Analysis

| Period | Median $/Sq Ft | Change |
|--------|---------------|--------|
| 6 months ago | $[X] | — |
| 3 months ago | $[X] | [X]% |
| Current | $[X] | [X]% |
| **Trend** | **[APPRECIATING / STABLE / DEPRECIATING]** | **[X]% annualized** |

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## Comps Score Breakdown

| Dimension | Score | Max | Notes |
|-----------|-------|-----|-------|
| Data Quality | [X] | 20 | [Brief note] |
| Price Alignment | [X] | 20 | [Brief note] |
| Comp Relevance | [X] | 20 | [Brief note] |
| Market Trend | [X] | 20 | [Brief note] |
| Value Assessment | [X] | 20 | [Brief note] |
| **Total Comps Score** | **[X]** | **100** | |

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## Key Findings

### Strengths
1. [Top strength from comps analysis]
2. [Second strength]
3. [Third strength]

### Concerns
1. [Top concern]
2. [Second concern]
3. [Third concern]

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*Report generated by AI Real Estate Analyst. For educational and research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.*

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Confidence Indicators

Flag the confidence level of the analysis:

| Confidence | Criteria | |------------|----------| | High | 6+ comps, all within 0.5 mi and 3 months, avg adjustment 15% |

Always disclose the confidence level prominently in the report.

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Error Handling

• If no comps found within 1 mile / 6 months, expand search radius to 2 miles and time window to 12 months
• If property is unique (e.g., waterfront, historic, very large lot), note that comps may be less reliable
• If listing price is unavailable, estimate based on tax assessment and local assessment-to-market ratios
• If square footage data conflicts between sources, use the county assessor record as primary

DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: zubair-trabzada
• Source: zubair-trabzada/ai-realestate-claude
• License: MIT
• Homepage: https://www.skool.com/aiworkshop

Install and usage instructions live in the source repository linked above.