Rank brokers and agents by motivated seller distress signals, with configurable price segment and market
Rank brokers and agents by motivated seller distress signals, with configurable price segment and market
npx skills add https://github.com/ParclLabs/parcl-ai-connect --skill broker-analytics이 명령을 Claude Code에 복사하여 붙여넣어 스킬을 설치하세요
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| name | broker-analytics |
| description | Rank brokers and agents by motivated seller distress signals, with configurable price segment and market |
| user-invocable | true |
| argument-hint | [market name] [optional: min price, e.g. 500k, 2M, or 'all'] |
| allowed-tools | Read, Grep, Glob, Bash, Write, Edit, WebFetch |
Generates a 5-sheet Excel workbook analyzing agent and brokerage performance in a target market, ranked by motivated seller distress signals.
Target market: First argument (e.g., "Hamptons", "Houston", "Tampa")
Price segment: Second argument controls the minimum listing price filter:
2M or 2m (default if omitted): luxury segment, properties over $2,000,000500k or 500K: mid-market, properties over $500,0001M or 1m: upper market, properties over $1,000,0005M or 5m: ultra-luxury, properties over $5,000,000all or 0: no price filter, analyze the entire marketParse the second argument by stripping the letter suffix and converting: k/K = multiply by 1,000, m/M = multiply by 1,000,000. If no second argument is provided, default to $2,000,000.
Examples:
/broker-analytics Hamptons # Hamptons luxury (>$2M)
/broker-analytics Houston 500k # Houston mid-market (>$500K)
/broker-analytics Tampa all # Tampa full market (no filter)
/broker-analytics "Beverly Hills" 5M # Beverly Hills ultra-luxury (>$5M)
Audience: Real estate teams prospecting for listing opportunities by identifying underperforming agents and brokerages with distressed inventory.
Never display raw parcl_id values in user-facing output. Always resolve to human-readable names:
5452730 to "East Hampton (11937)")2900417 to "Tampa-St. Petersburg-Clearwater, FL")search_investorsNote: some MCP endpoints return IDs as floats with .0 suffix (e.g., 5452730.0). Strip the .0 before any lookup or display.
| Step | Tool | Purpose |
|---|---|---|
| Resolve market | search_locations | Convert market name to parcl_id(s). Get all relevant ZIP codes and cities. |
| Pull listings | motivated_seller_properties | All active for-sale listings with agent info, price, DOM, motivated seller scores. |
Use search_locations to resolve the market name into parcl_id(s). Think broadly. Most markets span multiple ZIP codes and town names. Run multiple searches to capture all relevant areas. Focus on ZIP-level IDs.
Call motivated_seller_properties with:
parcl_ids: all resolved market IDssort_by: "latest_listing_price"sort_order: "desc"limit: 50000Always run preview=True first to check credit cost, then preview=False to download.
Retrieve the CSV via the presigned download_url. Filter to properties where latest_listing_price exceeds the parsed price threshold. If the user specified all, skip filtering and use all listings.
Use the bundled script:
python3 ${CLAUDE_SKILL_DIR}/scripts/build_workbook.py <input_csv> <output_xlsx> --market "Market Name"
If the script isn't available, follow the workbook structure below using openpyxl.
| Element | Color | Hex |
|---|---|---|
| Title bar background | Dark navy | #1F4E79 |
| Title text | White bold Arial 14 | #FFFFFF |
| Subtitle text | Gray Arial 10 | #666666 |
| Warning subtitle text | Dark red bold Arial 10 | #C00000 |
| Properties header row | Medium blue | #2E75B6 |
| Brokerage header row | Orange | #ED7D31 |
| Agent/Distress header row | Dark red | #C00000 |
| Fire sale row highlight | Light red | #FFC7CE |
| Motivated row highlight | Light yellow | #FFEB9C |
| Above-market-avg row highlight | Cream | #FFF2CC |
| "vs Market Avg" negative delta cell | Red text on red bg | text #9C0006, bg #FFC7CE |
| "vs Market Avg" positive delta cell | Green text on green bg | text #006100, bg #C6EFCE |
$#,##0, Percent 0.0%, Score 0.00, DOM 0, vs-Market +0.00;-0.00;0.00motivated_seller_index_label:
fire_sale → entire row gets #FFC7CEmotivated → entire row gets #FFEB9Cstubborn / neutral → no highlightA dashboard with market-level KPIs. Layout (A=labels, B=values):
Row 1 (merged A1:H1): {MARKET} FOR-SALE MARKET: MOTIVATED SELLER ANALYSIS BY BROKER/AGENT, dark navy bg, white bold 14pt
Row 2 (merged A2:H2): Properties Listed Over {PRICE_THRESHOLD} | Data as of {date} | Source: Parcl Labs, gray 10pt
Row 4 (merged A4:C4): MARKET SNAPSHOT, bold, light blue bg (#D6E4F0), navy text (#1F4E79)
| Row | A (bold label) | B (value) |
|---|---|---|
| 5 | Total Listings | count |
| 6 | Listings with Agent Data | count where agent_name is not null |
| 7 | Unique Brokerages | nunique of agent_business |
| 8 | Unique Agents | nunique of agent_name |
| 9 | Median Listing Price | median of latest_listing_price (fmt: $#,##0) |
| 10 | Avg Days on Market | mean of days_on_market (fmt: 0) |
| 11 | Avg Motivated Seller Score | mean of motivated_seller_index_value (fmt: 0.00) |
| 12 | Fire Sale Properties | count where label == fire_sale |
| 13 | Motivated Properties | count where label == motivated |
| 14 | Stubborn Properties | count where label == stubborn |
| 15 | Neutral Properties | count where label == neutral |
Row 17 (merged A17:E17): MOTIVATED SELLER LABEL DISTRIBUTION, bold, light blue bg, navy text
| Row | A (bold) | B | C | D | E |
|---|---|---|---|---|---|
| 18 | Label | Count | % of Total | Avg Price | Avg DOM |
| 19-22 | fire_sale / motivated / stubborn / neutral | computed values |
Row 24 (merged A24:H24): KEY INSIGHT, bold, light blue bg, navy text
Rows 25-26 (merged A25:H26): Narrative insight paragraph:
Market avg motivated seller score is {avg_score:.2f}. Brokerages/agents scoring ABOVE this average have listings that are sitting longer, cutting prices more, and signaling more seller distress, a potential indicator of overpricing or underperformance relative to the market.
Column widths: A=32, B=22, C=16, D-H=13
All listings above the price threshold sorted by motivated_seller_index_value descending (most distressed first), then by days_on_market descending.
Row 1 (merged): ALL {MARKET} PROPERTIES FOR SALE OVER {PRICE_THRESHOLD}, dark navy bg, white 14pt bold
Row 2 (header row): medium blue bg (#2E75B6), white bold Arial 10pt
| Column | Header | Source Field | Format |
|---|---|---|---|
| A | Parcl Property ID | parcl_property_id | |
| B | Address | address1 | |
| C | City | city | |
| D | ZIP | zip5 | |
| E | Type | property_type | |
| F | Beds | bedrooms | |
| G | Baths | bathrooms | |
| H | Sq Ft | sq_ft | |
| I | Year Built | year_built | |
| J | Current Price | latest_listing_price | $#,##0 |
| K | Initial Price | initial_listing_price | $#,##0 |
| L | Days on Market | days_on_market | |
| M | Price Cuts | num_price_cuts | |
| N | % Price Change | percent_change_listing_price | 0.0% |
| O | Motivated Score | motivated_seller_index_value | 0.00 |
| P | Motivated Label | motivated_seller_index_label | |
| Q | Agent Name | agent_name | |
| R | Brokerage | agent_business | |
| S | Agent Email | agent_email | |
| T | Agent Phone | agent_phone | |
| U | Owner Entity | entity_name | |
| V | Original Purchase Price | original_purchase_price | $#,##0 |
| W | Unrealized P&L | unrealized_net | $#,##0 |
Row coloring: #FFC7CE for fire_sale, #FFEB9C for motivated, no fill for others.
Freeze pane: A3. Auto-filter on row 2.
Aggregated by agent_business, ranked by avg motivated seller score descending (worst performers at top).
Row 1 (merged): BROKERAGE PERFORMANCE: RANKED BY MOTIVATED SELLER SCORE (UNDERPERFORMERS AT TOP), dark navy bg, white 14pt bold
Row 2 (merged): Market Avg Motivated Score: {avg:.2f} | Brokerages above this line are underperforming the market, dark red bold 10pt (#C00000)
Row 3 (header): Orange bg (#ED7D31), white bold Arial 10pt
| Column | Header | Calculation |
|---|---|---|
| A | Brokerage | Group key (bold in data rows) |
| B | # Listings | Count |
| C | Avg Motivated Score | Mean motivated_seller_index_value (fmt: 0.00) |
| D | vs Market Avg | score - market_avg (fmt: +0.00;-0.00;0.00) |
| E | Avg Days on Market | Mean DOM (fmt: 0) |
| F | Avg Price Cuts | Mean num_price_cuts (fmt: 0.0) |
| G | Avg % Price Change | Mean percent_change_listing_price (fmt: 0.0%) |
| H | Total Listing Value | Sum latest_listing_price (fmt: $#,##0) |
| I | Avg Listing Price | Mean latest_listing_price (fmt: $#,##0) |
| J | Fire Sale | Count where label == fire_sale |
| K | Motivated | Count where label == motivated |
| L | Neutral + Stubborn | Count where label in (neutral, stubborn) |
Row highlighting: rows where avg score > market avg get cream bg (#FFF2CC). The "vs Market Avg" cell: positive values get red text (#9C0006) on red bg (#FFC7CE); negative/zero get green text (#006100) on green bg (#C6EFCE).
Freeze pane: A4. Auto-filter on row 3.
Aggregated by agent_name + agent_business, ranked by avg motivated seller score descending.
Row 1 (merged): AGENT PERFORMANCE: RANKED BY MOTIVATED SELLER SCORE (UNDERPERFORMERS AT TOP), dark navy bg, white 14pt bold
Row 2 (merged): Market Avg Motivated Score: {avg:.2f} | Agents above this line have more distressed listings, dark red bold 10pt
Row 3 (header): Dark red bg (#C00000), white bold Arial 10pt
| Column | Header | Calculation |
|---|---|---|
| A | Agent | Group key (bold in data rows) |
| B | Brokerage | Group key |
| C | # Listings | Count |
| D | Avg Motivated Score | Mean score (fmt: 0.00) |
| E | vs Market Avg | score - market_avg (fmt: +0.00;-0.00;0.00) |
| F | Avg Days on Market | Mean DOM (fmt: 0) |
| G | Avg Price Cuts | Mean cuts (fmt: 0.0) |
| H | Avg % Price Change | Mean pct change (fmt: 0.0%) |
| I | Total Value | Sum latest_listing_price (fmt: $#,##0) |
| J | Fire Sales | Count fire_sale |
| K | Motivated | Count motivated |
Row highlighting: same logic as Sheet 3.
Freeze pane: A4. Auto-filter on row 3.
Only properties with motivated_seller_index_label in (fire_sale, motivated), sorted by score descending then DOM descending.
Row 1 (merged): FIRE SALE & MOTIVATED PROPERTIES: {MARKET}, dark red bg (#C00000), white 14pt bold
Row 2 (header): Dark red bg (#C00000), white bold Arial 10pt
| Column | Header | Source | Format |
|---|---|---|---|
| A | Parcl Property ID | parcl_property_id | |
| B | Address | address1 | |
| C | City | city | |
| D | ZIP | zip5 | |
| E | Current Price | latest_listing_price | $#,##0 |
| F | Initial Price | initial_listing_price | $#,##0 |
| G | Days on Market | days_on_market | |
| H | Price Cuts | num_price_cuts | |
| I | % Price Change | percent_change_listing_price | 0.0% |
| J | Motivated Score | motivated_seller_index_value | 0.00 |
| K | Label | motivated_seller_index_label | |
| L | Agent | agent_name | |
| M | Brokerage | agent_business | |
| N | Owner Entity | entity_name | |
| O | Unrealized P&L | unrealized_net | $#,##0 |
Row coloring: fire_sale rows get #FFC7CE, motivated rows get no special fill (to distinguish from fire_sale).
Freeze pane: A3. Auto-filter on row 2.
/broker-analytics Hamptons
/broker-analytics Beverly Hills
/broker-analytics Palm Beach
/broker-analytics Aspen