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Track product prices across time and stores, alert on price drops, and predict the best time to buy.\n\nTags: latest:0.1.1\n\nVersion history:\n\nv0.1.1 | 2026-08-14T06:18:53.570Z | auto\n\n- Removed the skill card file (skill-card.md).\n- No changes to core functionality or documentation.\n\nv0.1.0 | 2026-08-11T11:57:20.829Z | auto\n\nInitial public release: Track, analyze, and get alerts on product prices over time.\n\n- Track prices for products across stores and time, with category-aware insights.\n- Receive alerts when a product drops significantly below its historical median price.\n- Predict the best time to buy using built-in seasonal patterns for each category.\n- View price history using ASCII sparklines.\n- Full suite of CLI commands: add, update, remove, list products, show history, get alerts, see detailed product info, and generate reports.\n- Simple, dependency-free Python script with JSON database support.\n\nArchive index:\n\nArchive v0.1.1: 10 files, 15272 bytes\n\nFiles: LICENSE (1070b), README.md (2924b), references (0b), references/price-tracking-strategies.md (4087b), references/seasonal-buying-calendar.md (3658b), scripts (0b), scripts/price_predator.py (21649b), skill-card.md (2363b), SKILL.md (3218b), _meta.json (133b)\n\nFile v0.1.1:SKILL.md\n\n---\nname: price-predator\nversion: 1.0.0\nauthor: Denis Voronin\nlicense: MIT\ndescription: Track product prices across time and stores, alert on price drops, and predict the best time to buy.\n---\n\n# Price Predator\n\nTrack product prices across time and stores, get alerts on price drops, and predict the best time to buy.\n\n## Quick Start\n\n```bash\n# Track a product with its current price\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Record a new price observation\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View ASCII sparkline price history\npython3 scripts/price_predator.py history <product-id>\n\n# Check for price drop alerts (all products)\npython3 scripts/price_predator.py alert\n\n# Check best time to buy by category\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report\n```\n\n## Commands\n\n| Command | Description |\n|---------|-------------|\n| `track` | Add a product to track (name + price + category + optional URL/target) |\n| `update` | Record a new price observation for a tracked product |\n| `history` | Show price history with ASCII sparkline chart |\n| `alert` | Check for price drops exceeding threshold (>10% below median by default) |\n| `best-time` | Predict best time to buy based on seasonal patterns by category |\n| `report` | Full summary report of all tracked products |\n| `list` | List all tracked products |\n| `remove` | Remove a tracked product |\n| `info` | Show detailed info about a product |\n\n## How It Works\n\n- **Database**: JSON file (`~/.price_predator_db.json` by default). Override with `--db`.\n- **Price tracking**: Each `update` records price + timestamp + source. Build a history over time.\n- **Alerts**: When the latest price drops more than the threshold (default 10%) below the median of all recorded prices, an alert fires.\n- **Seasonal prediction**: Uses a built-in calendar of best months to buy each category (see `references/seasonal-buying-calendar.md`).\n- **Depreciation**: Category-aware annual depreciation rates provide a rough price prediction model.\n\n## Category-Aware Patterns\n\nPrice Predator knows seasonal discount windows for 15+ categories:\n\n- **Electronics / TVs / Laptops** → Black Friday (Nov), Cyber Monday\n- **Mattresses** → May (Memorial Day), February (Presidents' Day)\n- **Appliances** → September (Labor Day), May (Memorial Day)\n- **Smartphones** → September (new model launches), November (Black Friday)\n- **Furniture** → January & July (inventory clearance)\n- See `references/seasonal-buying-calendar.md` for the full calendar.\n\n## Options\n\n- `--db <path>` — Use a custom database file (global flag, before subcommand)\n- `--target <price>` — Set a target buy price when tracking\n- `--threshold <frac>` — Set alert threshold as a fraction (0.15 = 15%)\n- `--category <cat>` — Set product category for seasonal predictions\n\n## Files\n\n- `scripts/price_predator.py` — Main script (Python stdlib only, no dependencies)\n- `references/seasonal-buying-calendar.md` — Best months to buy each category\n- `references/price-tracking-strategies.md` — Strategies for effective price tracking\n\nFile v0.1.1:README.md\n\n# Price Predator 🦈\n\nTrack product prices across time and stores, get alerts on price drops, and predict the best time to buy.\n\n## Features\n\n- **Price tracking** — Add products and record price observations over time\n- **ASCII sparkline charts** — Visual price history right in your terminal\n- **Drop alerts** — Get notified when prices drop below your threshold (default: 10% below median)\n- **Seasonal buying guide** — Know the best month to buy each product category\n- **Category-aware predictions** — Depreciation rates and seasonal patterns for 15+ categories\n- **Target prices** — Set a buy target and get notified when it's reached\n- **Pure Python stdlib** — No dependencies, no pip install, just works\n\n## Quick Start\n\n```bash\n# Track a product\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Update with a new price\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View price history with sparkline\npython3 scripts/price_predator.py history <product-id>\n\n# Check for alerts\npython3 scripts/price_predator.py alert\n\n# Best time to buy\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report\n```\n\n## Commands\n\n| Command | Description |\n|---------|-------------|\n| `track` | Add a product to track |\n| `update <id> --price N` | Record a new price observation |\n| `history <id>` | Show price history with ASCII sparkline |\n| `alert [id]` | Check for price drops (all or one product) |\n| `best-time --category CAT` | Predict best time to buy by category |\n| `report` | Full summary of all tracked products |\n| `list` | List all tracked products |\n| `remove <id>` | Remove a tracked product |\n| `info <id>` | Show detailed product info |\n\n## Categories with Seasonal Data\n\nElectronics, TVs, Laptops, Smartphones, Cameras, Video Games, Mattresses, Appliances, Furniture, Clothing, Toys, Tools, Fitness Equipment, Outdoor Gear, Jewelry.\n\n## Example Session\n\n```bash\n$ python3 scripts/price_predator.py track --name \"MacBook Air M3\" --price 1099 --category laptops --target 999\n✅ Tracking product 'MacBook Air M3' (id: a1b2c3d4)\n   Initial price: $1099.00\n   Category: laptops\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 1049 --source amazon\n✅ Updated 'MacBook Air M3' → $1049.00\n   ↓ -50.00 (-4.5%) from previous $1099.00\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 989 --source bestbuy\n✅ Updated 'MacBook Air M3' → $989.00\n   ↓ -60.00 (-5.7%) from previous $1049.00\n\n$ python3 scripts/price_predator.py alert a1b2c3d4\n🔔 ALERT: 'MacBook Air M3' (id: a1b2c3d4)\n   Latest: $989.00 | Median: $1049.00\n   Drop: 5.7% below median (threshold: 10%)\n\n$ python3 scripts/price_predator.py history a1b2c3d4\n📊 Price History: MacBook Air M3 (id: a1b2c3d4)\n   Sparkline: █▆▄\n```\n\n## License\n\nMIT © Denis Voronin\n\nFile v0.1.1:_meta.json\n\n{\n  \"ownerId\": \"kn75wwn4x6djaf28jbykeamazd81gtdp\",\n  \"slug\": \"price-predator\",\n  \"version\": \"0.1.1\",\n  \"publishedAt\": 1786688333570\n}\n\nFile v0.1.1:references/price-tracking-strategies.md\n\n# Price Tracking Strategies\n\nEffective strategies for tracking product prices and timing purchases.\n\n## 1. Establish a Baseline\n\nBefore tracking for drops, record at least 2–3 price observations over a few weeks. This establishes a realistic median and helps filter out short-term noise.\n\n```bash\npython3 scripts/price_predator.py track --name \"Product\" --price 400.00 --category electronics\npython3 scripts/price_predator.py update <id> --price 395.00\npython3 scripts/price_predator.py update <id> --price 389.99\n```\n\n## 2. Set a Target Price\n\nDefine the price at which you're ready to buy. Price Predator will flag when it's reached.\n\n```bash\npython3 scripts/price_predator.py track --name \"Product\" --price 400.00 --target 300.00 --category electronics\n```\n\n## 3. Adjust Alert Sensitivity\n\nThe default alert threshold is 10% below median. For high-volatility items, raise it; for stable items, lower it.\n\n```bash\n# 15% threshold — only alert on significant drops\npython3 scripts/price_predator.py track --name \"Product\" --price 1000.00 --threshold 0.15\n```\n\n## 4. Check Seasonal Timing\n\nBefore buying, check whether the current month is a known discount window for the product's category.\n\n```bash\npython3 scripts/price_predator.py best-time --category electronics\n```\n\nIf it says \"NOW is a great time to buy,\" you're in a prime window. If the next window is months away, waiting could save 10–30%.\n\n## 5. Regular Price Checks\n\nUpdate prices regularly for the best data. Strategies:\n\n- **Manual checks**: Visit the store/website weekly and record the price.\n- **Sale events**: Always check during Black Friday, Prime Day, and holiday weekends.\n- **Multiple sources**: Use the `--source` flag to tag where each price came from (e.g., amazon, bestbuy, costco).\n\n```bash\npython3 scripts/price_predator.py update <id> --price 349.00 --source amazon\npython3 scripts/price_predator.py update <id> --price 339.00 --source bestbuy\n```\n\n## 6. Read the Sparkline\n\nThe ASCII sparkline gives a quick visual of price trend:\n\n```\n▁▂▂▃▄▅▅▆▇█\n```\n\n- **Upward stairs** (▁▃▅▇): Price rising — buy soon or wait for seasonal dip.\n- **Downward stairs** (█▇▅▃▁): Price falling — good sign, may drop further.\n- **Flat line** (▄▄▄▄): Price stable — wait for a sale event.\n- **Sharp drop** (█▁): Flash sale or clearance — act fast.\n\n## 7. Use the Report for Portfolio Review\n\nRun `report` periodically to review all tracked products at once. It shows:\n- Current price vs. median for each product\n- Whether any product is near its all-time low\n- Whether target prices have been reached\n- Recommended best-buy months\n\n## 8. Category-Specific Tips\n\n### Electronics\n- New models typically launch in Sep–Oct; previous gen drops immediately.\n- Black Friday doorbuster deals may be on lower-quality variants — verify model numbers.\n\n### Mattresses\n- Mattress prices are highly negotiable; MSRP is inflated.\n- Memorial Day and Labor Day offer the most predictable discounts.\n\n### Appliances\n- New appliance models ship in Sep–Oct; last year's models get clearanced.\n- Bundle deals during holiday weekends can stack savings.\n\n### Clothing\n- Buy at the end of each season for the steepest markdowns.\n- January and July are the best clearance months.\n\n## 9. When NOT to Wait\n\nSometimes buying now is better than waiting for a sale:\n\n- **Limited stock / clearance**: If the item is being discontinued, the current price may be the best you'll get.\n- **Urgent need**: If you need it now, the utility of having it outweighs a potential 10% savings months later.\n- **Price is already near all-time low**: Check `report` — if it says \"Near all-time low,\" waiting has diminishing returns.\n\n## 10. Database Management\n\n- The default database is at `~/.price_predator_db.json`.\n- Use `--db` to maintain separate databases (e.g., personal vs. gift tracking).\n- Use `list` to see all tracked products at a glance.\n- Use `remove` to clean up products you've purchased or no longer care about.\n- Back up the JSON file periodically — it's your price history.\n\nFile v0.1.1:references/seasonal-buying-calendar.md\n\n# Seasonal Buying Calendar\n\nBest months to buy each product category, based on retail industry sales cycles.\n\n## Electronics\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Electronics (general)** | November, December | Black Friday & Cyber Monday offer the deepest discounts on TVs, laptops, headphones, and gadgets | July (Amazon Prime Day), August (back-to-school) |\n| **TVs** | November, January | Black Friday is the biggest TV discount event; January brings Super Bowl promotions | Cyber Monday, Presidents' Day |\n| **Laptops** | November, August | Black Friday/Cyber Monday and back-to-school season | July (Prime Day), April (spring refresh) |\n| **Smartphones** | September, November | New iPhones/Androids launch Sep–Oct; prior models drop in price | March (spring launches), Black Friday |\n| **Cameras** | November, April | Black Friday and spring rebate season | January (CES clearance), September |\n| **Video Games** | November, December | Holiday shopping season; deepest game/console discounts | June (E3/Summer Game Fest), January (Steam Winter Sale end) |\n\n## Home\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Mattresses** | May | Memorial Day sales are the prime mattress buying event | February (Presidents' Day), September (Labor Day) |\n| **Appliances** | September, May | Labor Day and Memorial Day bring major appliance clearance | November (Black Friday), January (New Year clearance) |\n| **Furniture** | January, July | Dealers clear inventory for new lines | November (Black Friday), May (Memorial Day) |\n\n## Lifestyle\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Clothing** | January, July | End-of-season clearance: January (winter), July (summer) | August (back-to-school), December (post-holiday) |\n| **Jewelry** | January, July | Slower retail periods yield better prices | February (Valentine's clearance), November |\n| **Toys** | November, December | Holiday shopping season; deepest discounts early December | January (post-holiday clearance), July |\n\n## Tools & Outdoor\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Tools** | June, December | Father's Day and holiday sales on power tools | November (Black Friday), May (spring DIY) |\n| **Outdoor Gear** | September, August | End-of-summer clearance on grills, patio furniture, camping gear | May (Memorial Day), November |\n| **Fitness Equipment** | January, December | New Year resolutions and holiday sales | September (end of outdoor season), May |\n\n## Depreciation Rates (Annual)\n\nExpected year-over-year price decline used for predictions:\n\n| Category | Annual Depreciation |\n|----------|-------------------|\n| Smartphones | 25% |\n| TVs | 20% |\n| Laptops | 18% |\n| Electronics (general) | 15% |\n| Cameras | 15% |\n| Video Games | 12% |\n| Clothing | 10% |\n| Toys | 8% |\n| Fitness Equipment | 8% |\n| Tools | 6% |\n| Outdoor Gear | 6% |\n| Mattresses | 5% |\n| Appliances | 5% |\n| Furniture | 4% |\n| Jewelry | 3% |\n\n## General Tips\n\n- **Black Friday (November)** is the broadest discount window across almost all categories.\n- **Amazon Prime Day (July)** has expanded into a major mid-year sale event.\n- **End-of-season clearance** is predictable for clothing, outdoor gear, and furniture.\n- **New model launches** create price drops on previous-generation electronics (especially smartphones and laptops).\n- **Holiday weekends sales** (Memorial Day, Labor Day, Presidents' Day) are reliable for big-ticket home items.\n\nFile v0.1.1:skill-card.md\n\n## Description:\n\nTrack product prices across time and stores, alert on price drops, and predict the best time to buy.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[voronindenis5](https://clawhub.ai/user/voronindenis5)\n\n### License/Terms of Use:\n\nMIT\n\n## Use Case:\n\nExternal users and developers use Price Predator to maintain a local price history for products, check target-price and median-drop alerts, and get category-based timing guidance before buying.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Product names, product URLs, prices, sources, and price history may be stored in a local JSON database.\n\nMitigation: Use --db for a separate database when needed, avoid storing sensitive product URLs, and protect or delete the local database according to the user's data-handling needs.\n\nRisk: Removing a product permanently deletes that product record from the local database.\n\nMitigation: Confirm the product ID before running remove and keep a backup of the JSON database when records need to be recoverable.\n\nRisk: Buying recommendations are based on stored observations, seasonal calendars, and depreciation patterns rather than guaranteed market prices.\n\nMitigation: Treat alerts and best-time guidance as decision support, and verify current retailer prices before purchasing.\n\n## Reference(s):\n\n- [Price Predator ClawHub Skill Page](https://clawhub.ai/voronindenis5/skills/price-predator)\n- [Source Repository](https://github.com/voronindenis5/price-predator)\n- [Price Tracking Strategies](references/price-tracking-strategies.md)\n- [Seasonal Buying Calendar](references/seasonal-buying-calendar.md)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Shell commands, Guidance]\n\n**Output Format:** [Markdown with inline shell commands and command-line text output]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May write or update a local JSON database path configured by --db; the default path is ~/.price_predator_db.json.]\n\n## Skill Version(s):\n\n0.1.1 (source: ClawHub release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v0.1.1:LICENSE\n\nMIT License\n\nCopyright (c) 2026 Denis Voronin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\nArchive v0.1.0: 10 files, 15199 bytes\n\nFiles: LICENSE (1070b), README.md (2924b), references (0b), references/price-tracking-strategies.md (4087b), references/seasonal-buying-calendar.md (3658b), scripts (0b), scripts/price_predator.py (21649b), skill-card.md (2165b), SKILL.md (3218b), _meta.json (133b)\n\nFile v0.1.0:SKILL.md\n\n---\nname: price-predator\nversion: 1.0.0\nauthor: Denis Voronin\nlicense: MIT\ndescription: Track product prices across time and stores, alert on price drops, and predict the best time to buy.\n---\n\n# Price Predator\n\nTrack product prices across time and stores, get alerts on price drops, and predict the best time to buy.\n\n## Quick Start\n\n```bash\n# Track a product with its current price\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Record a new price observation\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View ASCII sparkline price history\npython3 scripts/price_predator.py history <product-id>\n\n# Check for price drop alerts (all products)\npython3 scripts/price_predator.py alert\n\n# Check best time to buy by category\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report\n```\n\n## Commands\n\n| Command | Description |\n|---------|-------------|\n| `track` | Add a product to track (name + price + category + optional URL/target) |\n| `update` | Record a new price observation for a tracked product |\n| `history` | Show price history with ASCII sparkline chart |\n| `alert` | Check for price drops exceeding threshold (>10% below median by default) |\n| `best-time` | Predict best time to buy based on seasonal patterns by category |\n| `report` | Full summary report of all tracked products |\n| `list` | List all tracked products |\n| `remove` | Remove a tracked product |\n| `info` | Show detailed info about a product |\n\n## How It Works\n\n- **Database**: JSON file (`~/.price_predator_db.json` by default). Override with `--db`.\n- **Price tracking**: Each `update` records price + timestamp + source. Build a history over time.\n- **Alerts**: When the latest price drops more than the threshold (default 10%) below the median of all recorded prices, an alert fires.\n- **Seasonal prediction**: Uses a built-in calendar of best months to buy each category (see `references/seasonal-buying-calendar.md`).\n- **Depreciation**: Category-aware annual depreciation rates provide a rough price prediction model.\n\n## Category-Aware Patterns\n\nPrice Predator knows seasonal discount windows for 15+ categories:\n\n- **Electronics / TVs / Laptops** → Black Friday (Nov), Cyber Monday\n- **Mattresses** → May (Memorial Day), February (Presidents' Day)\n- **Appliances** → September (Labor Day), May (Memorial Day)\n- **Smartphones** → September (new model launches), November (Black Friday)\n- **Furniture** → January & July (inventory clearance)\n- See `references/seasonal-buying-calendar.md` for the full calendar.\n\n## Options\n\n- `--db <path>` — Use a custom database file (global flag, before subcommand)\n- `--target <price>` — Set a target buy price when tracking\n- `--threshold <frac>` — Set alert threshold as a fraction (0.15 = 15%)\n- `--category <cat>` — Set product category for seasonal predictions\n\n## Files\n\n- `scripts/price_predator.py` — Main script (Python stdlib only, no dependencies)\n- `references/seasonal-buying-calendar.md` — Best months to buy each category\n- `references/price-tracking-strategies.md` — Strategies for effective price tracking\n\nFile v0.1.0:README.md\n\n# Price Predator 🦈\n\nTrack product prices across time and stores, get alerts on price drops, and predict the best time to buy.\n\n## Features\n\n- **Price tracking** — Add products and record price observations over time\n- **ASCII sparkline charts** — Visual price history right in your terminal\n- **Drop alerts** — Get notified when prices drop below your threshold (default: 10% below median)\n- **Seasonal buying guide** — Know the best month to buy each product category\n- **Category-aware predictions** — Depreciation rates and seasonal patterns for 15+ categories\n- **Target prices** — Set a buy target and get notified when it's reached\n- **Pure Python stdlib** — No dependencies, no pip install, just works\n\n## Quick Start\n\n```bash\n# Track a product\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Update with a new price\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View price history with sparkline\npython3 scripts/price_predator.py history <product-id>\n\n# Check for alerts\npython3 scripts/price_predator.py alert\n\n# Best time to buy\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report\n```\n\n## Commands\n\n| Command | Description |\n|---------|-------------|\n| `track` | Add a product to track |\n| `update <id> --price N` | Record a new price observation |\n| `history <id>` | Show price history with ASCII sparkline |\n| `alert [id]` | Check for price drops (all or one product) |\n| `best-time --category CAT` | Predict best time to buy by category |\n| `report` | Full summary of all tracked products |\n| `list` | List all tracked products |\n| `remove <id>` | Remove a tracked product |\n| `info <id>` | Show detailed product info |\n\n## Categories with Seasonal Data\n\nElectronics, TVs, Laptops, Smartphones, Cameras, Video Games, Mattresses, Appliances, Furniture, Clothing, Toys, Tools, Fitness Equipment, Outdoor Gear, Jewelry.\n\n## Example Session\n\n```bash\n$ python3 scripts/price_predator.py track --name \"MacBook Air M3\" --price 1099 --category laptops --target 999\n✅ Tracking product 'MacBook Air M3' (id: a1b2c3d4)\n   Initial price: $1099.00\n   Category: laptops\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 1049 --source amazon\n✅ Updated 'MacBook Air M3' → $1049.00\n   ↓ -50.00 (-4.5%) from previous $1099.00\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 989 --source bestbuy\n✅ Updated 'MacBook Air M3' → $989.00\n   ↓ -60.00 (-5.7%) from previous $1049.00\n\n$ python3 scripts/price_predator.py alert a1b2c3d4\n🔔 ALERT: 'MacBook Air M3' (id: a1b2c3d4)\n   Latest: $989.00 | Median: $1049.00\n   Drop: 5.7% below median (threshold: 10%)\n\n$ python3 scripts/price_predator.py history a1b2c3d4\n📊 Price History: MacBook Air M3 (id: a1b2c3d4)\n   Sparkline: █▆▄\n```\n\n## License\n\nMIT © Denis Voronin\n\nFile v0.1.0:_meta.json\n\n{\n  \"ownerId\": \"kn75wwn4x6djaf28jbykeamazd81gtdp\",\n  \"slug\": \"price-predator\",\n  \"version\": \"0.1.0\",\n  \"publishedAt\": 1786449440829\n}\n\nFile v0.1.0:references/price-tracking-strategies.md\n\n# Price Tracking Strategies\n\nEffective strategies for tracking product prices and timing purchases.\n\n## 1. Establish a Baseline\n\nBefore tracking for drops, record at least 2–3 price observations over a few weeks. This establishes a realistic median and helps filter out short-term noise.\n\n```bash\npython3 scripts/price_predator.py track --name \"Product\" --price 400.00 --category electronics\npython3 scripts/price_predator.py update <id> --price 395.00\npython3 scripts/price_predator.py update <id> --price 389.99\n```\n\n## 2. Set a Target Price\n\nDefine the price at which you're ready to buy. Price Predator will flag when it's reached.\n\n```bash\npython3 scripts/price_predator.py track --name \"Product\" --price 400.00 --target 300.00 --category electronics\n```\n\n## 3. Adjust Alert Sensitivity\n\nThe default alert threshold is 10% below median. For high-volatility items, raise it; for stable items, lower it.\n\n```bash\n# 15% threshold — only alert on significant drops\npython3 scripts/price_predator.py track --name \"Product\" --price 1000.00 --threshold 0.15\n```\n\n## 4. Check Seasonal Timing\n\nBefore buying, check whether the current month is a known discount window for the product's category.\n\n```bash\npython3 scripts/price_predator.py best-time --category electronics\n```\n\nIf it says \"NOW is a great time to buy,\" you're in a prime window. If the next window is months away, waiting could save 10–30%.\n\n## 5. Regular Price Checks\n\nUpdate prices regularly for the best data. Strategies:\n\n- **Manual checks**: Visit the store/website weekly and record the price.\n- **Sale events**: Always check during Black Friday, Prime Day, and holiday weekends.\n- **Multiple sources**: Use the `--source` flag to tag where each price came from (e.g., amazon, bestbuy, costco).\n\n```bash\npython3 scripts/price_predator.py update <id> --price 349.00 --source amazon\npython3 scripts/price_predator.py update <id> --price 339.00 --source bestbuy\n```\n\n## 6. Read the Sparkline\n\nThe ASCII sparkline gives a quick visual of price trend:\n\n```\n▁▂▂▃▄▅▅▆▇█\n```\n\n- **Upward stairs** (▁▃▅▇): Price rising — buy soon or wait for seasonal dip.\n- **Downward stairs** (█▇▅▃▁): Price falling — good sign, may drop further.\n- **Flat line** (▄▄▄▄): Price stable — wait for a sale event.\n- **Sharp drop** (█▁): Flash sale or clearance — act fast.\n\n## 7. Use the Report for Portfolio Review\n\nRun `report` periodically to review all tracked products at once. It shows:\n- Current price vs. median for each product\n- Whether any product is near its all-time low\n- Whether target prices have been reached\n- Recommended best-buy months\n\n## 8. Category-Specific Tips\n\n### Electronics\n- New models typically launch in Sep–Oct; previous gen drops immediately.\n- Black Friday doorbuster deals may be on lower-quality variants — verify model numbers.\n\n### Mattresses\n- Mattress prices are highly negotiable; MSRP is inflated.\n- Memorial Day and Labor Day offer the most predictable discounts.\n\n### Appliances\n- New appliance models ship in Sep–Oct; last year's models get clearanced.\n- Bundle deals during holiday weekends can stack savings.\n\n### Clothing\n- Buy at the end of each season for the steepest markdowns.\n- January and July are the best clearance months.\n\n## 9. When NOT to Wait\n\nSometimes buying now is better than waiting for a sale:\n\n- **Limited stock / clearance**: If the item is being discontinued, the current price may be the best you'll get.\n- **Urgent need**: If you need it now, the utility of having it outweighs a potential 10% savings months later.\n- **Price is already near all-time low**: Check `report` — if it says \"Near all-time low,\" waiting has diminishing returns.\n\n## 10. Database Management\n\n- The default database is at `~/.price_predator_db.json`.\n- Use `--db` to maintain separate databases (e.g., personal vs. gift tracking).\n- Use `list` to see all tracked products at a glance.\n- Use `remove` to clean up products you've purchased or no longer care about.\n- Back up the JSON file periodically — it's your price history.\n\nFile v0.1.0:references/seasonal-buying-calendar.md\n\n# Seasonal Buying Calendar\n\nBest months to buy each product category, based on retail industry sales cycles.\n\n## Electronics\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Electronics (general)** | November, December | Black Friday & Cyber Monday offer the deepest discounts on TVs, laptops, headphones, and gadgets | July (Amazon Prime Day), August (back-to-school) |\n| **TVs** | November, January | Black Friday is the biggest TV discount event; January brings Super Bowl promotions | Cyber Monday, Presidents' Day |\n| **Laptops** | November, August | Black Friday/Cyber Monday and back-to-school season | July (Prime Day), April (spring refresh) |\n| **Smartphones** | September, November | New iPhones/Androids launch Sep–Oct; prior models drop in price | March (spring launches), Black Friday |\n| **Cameras** | November, April | Black Friday and spring rebate season | January (CES clearance), September |\n| **Video Games** | November, December | Holiday shopping season; deepest game/console discounts | June (E3/Summer Game Fest), January (Steam Winter Sale end) |\n\n## Home\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Mattresses** | May | Memorial Day sales are the prime mattress buying event | February (Presidents' Day), September (Labor Day) |\n| **Appliances** | September, May | Labor Day and Memorial Day bring major appliance clearance | November (Black Friday), January (New Year clearance) |\n| **Furniture** | January, July | Dealers clear inventory for new lines | November (Black Friday), May (Memorial Day) |\n\n## Lifestyle\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Clothing** | January, July | End-of-season clearance: January (winter), July (summer) | August (back-to-school), December (post-holiday) |\n| **Jewelry** | January, July | Slower retail periods yield better prices | February (Valentine's clearance), November |\n| **Toys** | November, December | Holiday shopping season; deepest discounts early December | January (post-holiday clearance), July |\n\n## Tools & Outdoor\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Tools** | June, December | Father's Day and holiday sales on power tools | November (Black Friday), May (spring DIY) |\n| **Outdoor Gear** | September, August | End-of-summer clearance on grills, patio furniture, camping gear | May (Memorial Day), November |\n| **Fitness Equipment** | January, December | New Year resolutions and holiday sales | September (end of outdoor season), May |\n\n## Depreciation Rates (Annual)\n\nExpected year-over-year price decline used for predictions:\n\n| Category | Annual Depreciation |\n|----------|-------------------|\n| Smartphones | 25% |\n| TVs | 20% |\n| Laptops | 18% |\n| Electronics (general) | 15% |\n| Cameras | 15% |\n| Video Games | 12% |\n| Clothing | 10% |\n| Toys | 8% |\n| Fitness Equipment | 8% |\n| Tools | 6% |\n| Outdoor Gear | 6% |\n| Mattresses | 5% |\n| Appliances | 5% |\n| Furniture | 4% |\n| Jewelry | 3% |\n\n## General Tips\n\n- **Black Friday (November)** is the broadest discount window across almost all categories.\n- **Amazon Prime Day (July)** has expanded into a major mid-year sale event.\n- **End-of-season clearance** is predictable for clothing, outdoor gear, and furniture.\n- **New model launches** create price drops on previous-generation electronics (especially smartphones and laptops).\n- **Holiday weekends sales** (Memorial Day, Labor Day, Presidents' Day) are reliable for big-ticket home items.\n\nFile v0.1.0:skill-card.md\n\n## Description:\n\nTrack product prices across time and stores, alert on price drops, and predict the best time to buy.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[voronindenis5](https://clawhub.ai/user/voronindenis5)\n\n### License/Terms of Use:\n\nMIT\n\n## Use Case:\n\nExternal users and developers use this skill to maintain a local product price history, review price trends, receive threshold-based drop alerts, and get category-aware buying timing guidance.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Tracked products, prices, timestamps, sources, and optional product URLs are retained in a local JSON database.\n\nMitigation: Use --db to select a separate database for sensitive shopping lists or shared systems, and delete or edit the JSON file when the history is no longer needed.\n\nRisk: Seasonal buying guidance and depreciation estimates may not reflect current retail conditions for a specific product.\n\nMitigation: Treat recommendations as decision support and verify current prices, product model numbers, and seller terms before purchasing.\n\n## Reference(s):\n\n- [Price Tracking Strategies](references/price-tracking-strategies.md)\n- [Seasonal Buying Calendar](references/seasonal-buying-calendar.md)\n- [GitHub Source Repository](https://github.com/voronindenis5/price-predator)\n- [ClawHub Skill Page](https://clawhub.ai/voronindenis5/skills/price-predator)\n- [ClawHub Publisher Profile](https://clawhub.ai/user/voronindenis5)\n\n## Skill Output:\n\n**Output Type(s):** [text, shell commands, guidance]\n\n**Output Format:** [Terminal text with command-line examples and report-style summaries]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Uses a local JSON database; the default path is ~/.price_predator_db.json unless --db is provided.]\n\n## Skill Version(s):\n\n0.1.0 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v0.1.0:LICENSE\n\nMIT License\n\nCopyright (c) 2026 Denis Voronin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.","readmeExcerpt":"Skill: price-predator Owner: voronindenis5 Summary: Track product prices across time and stores, alert on price drops, and predict the best time to buy. Tags: latest:0.1.1 Version history: v0.1.1 | 2026-08-14T06:18:53.570Z | auto - Removed the skill card file (skill-card.md). - No changes to core functionality or documentation. v0.1.0 | 2026-08-11T11:57:20.829Z | auto Initial public release: Track, analyze, and get a","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"# Track a product with its current price\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Record a new price observation\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View ASCII sparkline price history\npython3 scripts/price_predator.py history <product-id>\n\n# Check for price drop alerts (all products)\npython3 scripts/price_predator.py alert\n\n# Check best time to buy by category\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report"},{"language":"bash","snippet":"# Track a product\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Update with a new price\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View price history with sparkline\npython3 scripts/price_predator.py history <product-id>\n\n# Check for alerts\npython3 scripts/price_predator.py alert\n\n# Best time to buy\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report"},{"language":"bash","snippet":"$ python3 scripts/price_predator.py track --name \"MacBook Air M3\" --price 1099 --category laptops --target 999\n✅ Tracking product 'MacBook Air M3' (id: a1b2c3d4)\n   Initial price: $1099.00\n   Category: laptops\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 1049 --source amazon\n✅ Updated 'MacBook Air M3' → $1049.00\n   ↓ -50.00 (-4.5%) from previous $1099.00\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 989 --source bestbuy\n✅ Updated 'MacBook Air M3' → $989.00\n   ↓ -60.00 (-5.7%) from previous $1049.00\n\n$ python3 scripts/price_predator.py alert a1b2c3d4\n🔔 ALERT: 'MacBook Air M3' (id: a1b2c3d4)\n   Latest: $989.00 | Median: $1049.00\n   Drop: 5.7% below median (threshold: 10%)\n\n$ python3 scripts/price_predator.py history a1b2c3d4\n📊 Price History: MacBook Air M3 (id: a1b2c3d4)\n   Sparkline: █▆▄"},{"language":"bash","snippet":"python3 scripts/price_predator.py track --name \"Product\" --price 400.00 --category electronics\npython3 scripts/price_predator.py update <id> --price 395.00\npython3 scripts/price_predator.py update <id> --price 389.99"},{"language":"bash","snippet":"python3 scripts/price_predator.py track --name \"Product\" --price 400.00 --target 300.00 --category electronics"},{"language":"bash","snippet":"# 15% threshold — only alert on significant drops\npython3 scripts/price_predator.py track --name \"Product\" --price 1000.00 --threshold 0.15"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: price-predator\nversion: 1.0.0\nauthor: Denis Voronin\nlicense: MIT\ndescription: Track product prices across time and stores, alert on price drops, and predict the best time to buy.\n---\n\n# Price Predator\n\nTrack product prices across time and stores, get alerts on price drops, and predict the best time to buy.\n\n## Quick Start\n\n```bash\n# Track a product with its current price\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Record a new price observation\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View ASCII sparkline price history\npython3 scripts/price_predator.py history <product-id>\n\n# Check for price drop alerts (all products)\npython3 scripts/price_predator.py alert\n\n# Check best time to buy by category\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report\n```\n\n## Commands\n\n| Command | Description |\n|---------|-------------|\n| `track` | Add a product to track (name + price + category + optional URL/target) |\n| `update` | Record a new price observation for a tracked product |\n| `history` | Show price history with ASCII sparkline chart |\n| `alert` | Check for price drops exceeding threshold (>10% below median by default) |\n| `best-time` | Predict best time to buy based on seasonal patterns by category |\n| `report` | Full summary report of all tracked products |\n| `list` | List all tracked products |\n| `remove` | Remove a tracked product |\n| `info` | Show detailed info about a product |\n\n## How It Works\n\n- **Database**: JSON file (`~/.price_predator_db.json` by default). Override with `--db`.\n- **Price tracking**: Each `update` records price + timestamp + source. Build a history over time.\n- **Alerts**: When the latest price drops more than the threshold (default 10%) below the median of all recorded prices, an alert fires.\n- **Seasonal prediction**: Uses a built-in calendar of best months to buy each category (see `references/seasonal-buying-calendar.md`).\n- **Depreciation**: Category-aware annual depreciation rates provide a rough price prediction model.\n\n## Category-Aware Patterns\n\nPrice Predator knows seasonal discount windows for 15+ categories:\n\n- **Electronics / TVs / Laptops** → Black Friday (Nov), Cyber Monday\n- **Mattresses** → May (Memorial Day), February (Presidents' Day)\n- **Appliances** → September (Labor Day), May (Memorial Day)\n- **Smartphones** → September (new model launches), November (Black Friday)\n- **Furniture** → January & July (inventory clearance)\n- See `references/seasonal-buying-calendar.md` for the full calendar.\n\n## Options\n\n- `--db <path>` — Use a custom database file (global flag, before subcommand)\n- `--target <price>` — Set a target buy price when tracking\n- `--threshold <frac>` — Set alert threshold as a fraction (0.15 = 15%)\n- `--category <cat>` — Set product category for seasonal predictions\n\n## Files\n\n- `scripts/price_predator.py` — Main script (Python "},{"path":"README.md","content":"# Price Predator 🦈\n\nTrack product prices across time and stores, get alerts on price drops, and predict the best time to buy.\n\n## Features\n\n- **Price tracking** — Add products and record price observations over time\n- **ASCII sparkline charts** — Visual price history right in your terminal\n- **Drop alerts** — Get notified when prices drop below your threshold (default: 10% below median)\n- **Seasonal buying guide** — Know the best month to buy each product category\n- **Category-aware predictions** — Depreciation rates and seasonal patterns for 15+ categories\n- **Target prices** — Set a buy target and get notified when it's reached\n- **Pure Python stdlib** — No dependencies, no pip install, just works\n\n## Quick Start\n\n```bash\n# Track a product\npython3 scripts/price_predator.py track --name \"Sony WH-1000XM5\" --price 350.00 --category electronics\n\n# Update with a new price\npython3 scripts/price_predator.py update <product-id> --price 299.99\n\n# View price history with sparkline\npython3 scripts/price_predator.py history <product-id>\n\n# Check for alerts\npython3 scripts/price_predator.py alert\n\n# Best time to buy\npython3 scripts/price_predator.py best-time --category electronics\n\n# Full report\npython3 scripts/price_predator.py report\n```\n\n## Commands\n\n| Command | Description |\n|---------|-------------|\n| `track` | Add a product to track |\n| `update <id> --price N` | Record a new price observation |\n| `history <id>` | Show price history with ASCII sparkline |\n| `alert [id]` | Check for price drops (all or one product) |\n| `best-time --category CAT` | Predict best time to buy by category |\n| `report` | Full summary of all tracked products |\n| `list` | List all tracked products |\n| `remove <id>` | Remove a tracked product |\n| `info <id>` | Show detailed product info |\n\n## Categories with Seasonal Data\n\nElectronics, TVs, Laptops, Smartphones, Cameras, Video Games, Mattresses, Appliances, Furniture, Clothing, Toys, Tools, Fitness Equipment, Outdoor Gear, Jewelry.\n\n## Example Session\n\n```bash\n$ python3 scripts/price_predator.py track --name \"MacBook Air M3\" --price 1099 --category laptops --target 999\n✅ Tracking product 'MacBook Air M3' (id: a1b2c3d4)\n   Initial price: $1099.00\n   Category: laptops\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 1049 --source amazon\n✅ Updated 'MacBook Air M3' → $1049.00\n   ↓ -50.00 (-4.5%) from previous $1099.00\n\n$ python3 scripts/price_predator.py update a1b2c3d4 --price 989 --source bestbuy\n✅ Updated 'MacBook Air M3' → $989.00\n   ↓ -60.00 (-5.7%) from previous $1049.00\n\n$ python3 scripts/price_predator.py alert a1b2c3d4\n🔔 ALERT: 'MacBook Air M3' (id: a1b2c3d4)\n   Latest: $989.00 | Median: $1049.00\n   Drop: 5.7% below median (threshold: 10%)\n\n$ python3 scripts/price_predator.py history a1b2c3d4\n📊 Price History: MacBook Air M3 (id: a1b2c3d4)\n   Sparkline: █▆▄\n```\n\n## License\n\nMIT © Denis Voronin"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn75wwn4x6djaf28jbykeamazd81gtdp\",\n  \"slug\": \"price-predator\",\n  \"version\": \"0.1.1\",\n  \"publishedAt\": 1786688333570\n}"},{"path":"references/price-tracking-strategies.md","content":"# Price Tracking Strategies\n\nEffective strategies for tracking product prices and timing purchases.\n\n## 1. Establish a Baseline\n\nBefore tracking for drops, record at least 2–3 price observations over a few weeks. This establishes a realistic median and helps filter out short-term noise.\n\n```bash\npython3 scripts/price_predator.py track --name \"Product\" --price 400.00 --category electronics\npython3 scripts/price_predator.py update <id> --price 395.00\npython3 scripts/price_predator.py update <id> --price 389.99\n```\n\n## 2. Set a Target Price\n\nDefine the price at which you're ready to buy. Price Predator will flag when it's reached.\n\n```bash\npython3 scripts/price_predator.py track --name \"Product\" --price 400.00 --target 300.00 --category electronics\n```\n\n## 3. Adjust Alert Sensitivity\n\nThe default alert threshold is 10% below median. For high-volatility items, raise it; for stable items, lower it.\n\n```bash\n# 15% threshold — only alert on significant drops\npython3 scripts/price_predator.py track --name \"Product\" --price 1000.00 --threshold 0.15\n```\n\n## 4. Check Seasonal Timing\n\nBefore buying, check whether the current month is a known discount window for the product's category.\n\n```bash\npython3 scripts/price_predator.py best-time --category electronics\n```\n\nIf it says \"NOW is a great time to buy,\" you're in a prime window. If the next window is months away, waiting could save 10–30%.\n\n## 5. Regular Price Checks\n\nUpdate prices regularly for the best data. Strategies:\n\n- **Manual checks**: Visit the store/website weekly and record the price.\n- **Sale events**: Always check during Black Friday, Prime Day, and holiday weekends.\n- **Multiple sources**: Use the `--source` flag to tag where each price came from (e.g., amazon, bestbuy, costco).\n\n```bash\npython3 scripts/price_predator.py update <id> --price 349.00 --source amazon\npython3 scripts/price_predator.py update <id> --price 339.00 --source bestbuy\n```\n\n## 6. Read the Sparkline\n\nThe ASCII sparkline gives a quick visual of price trend:\n\n```\n▁▂▂▃▄▅▅▆▇█\n```\n\n- **Upward stairs** (▁▃▅▇): Price rising — buy soon or wait for seasonal dip.\n- **Downward stairs** (█▇▅▃▁): Price falling — good sign, may drop further.\n- **Flat line** (▄▄▄▄): Price stable — wait for a sale event.\n- **Sharp drop** (█▁): Flash sale or clearance — act fast.\n\n## 7. Use the Report for Portfolio Review\n\nRun `report` periodically to review all tracked products at once. It shows:\n- Current price vs. median for each product\n- Whether any product is near its all-time low\n- Whether target prices have been reached\n- Recommended best-buy months\n\n## 8. Category-Specific Tips\n\n### Electronics\n- New models typically launch in Sep–Oct; previous gen drops immediately.\n- Black Friday doorbuster deals may be on lower-quality variants — verify model numbers.\n\n### Mattresses\n- Mattress prices are highly negotiable; MSRP is inflated.\n- Memorial Day and Labor Day offer the most predictable discounts.\n\n### Appliances\n- New appliance models ship in Sep–Oct;"},{"path":"references/seasonal-buying-calendar.md","content":"# Seasonal Buying Calendar\n\nBest months to buy each product category, based on retail industry sales cycles.\n\n## Electronics\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Electronics (general)** | November, December | Black Friday & Cyber Monday offer the deepest discounts on TVs, laptops, headphones, and gadgets | July (Amazon Prime Day), August (back-to-school) |\n| **TVs** | November, January | Black Friday is the biggest TV discount event; January brings Super Bowl promotions | Cyber Monday, Presidents' Day |\n| **Laptops** | November, August | Black Friday/Cyber Monday and back-to-school season | July (Prime Day), April (spring refresh) |\n| **Smartphones** | September, November | New iPhones/Androids launch Sep–Oct; prior models drop in price | March (spring launches), Black Friday |\n| **Cameras** | November, April | Black Friday and spring rebate season | January (CES clearance), September |\n| **Video Games** | November, December | Holiday shopping season; deepest game/console discounts | June (E3/Summer Game Fest), January (Steam Winter Sale end) |\n\n## Home\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Mattresses** | May | Memorial Day sales are the prime mattress buying event | February (Presidents' Day), September (Labor Day) |\n| **Appliances** | September, May | Labor Day and Memorial Day bring major appliance clearance | November (Black Friday), January (New Year clearance) |\n| **Furniture** | January, July | Dealers clear inventory for new lines | November (Black Friday), May (Memorial Day) |\n\n## Lifestyle\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Clothing** | January, July | End-of-season clearance: January (winter), July (summer) | August (back-to-school), December (post-holiday) |\n| **Jewelry** | January, July | Slower retail periods yield better prices | February (Valentine's clearance), November |\n| **Toys** | November, December | Holiday shopping season; deepest discounts early December | January (post-holiday clearance), July |\n\n## Tools & Outdoor\n\n| Category | Best Months | Why | Secondary Windows |\n|----------|------------|-----|-------------------|\n| **Tools** | June, December | Father's Day and holiday sales on power tools | November (Black Friday), May (spring DIY) |\n| **Outdoor Gear** | September, August | End-of-summer clearance on grills, patio furniture, camping gear | May (Memorial Day), November |\n| **Fitness Equipment** | January, December | New Year resolutions and holiday sales | September (end of outdoor season), May |\n\n## Depreciation Rates (Annual)\n\nExpected year-over-year price decline used for predictions:\n\n| Category | Annual Depreciation |\n|----------|-------------------|\n| Smartphones | 25% |\n| TVs | 20% |\n| Laptops | 18% |\n| Electronics (general) | 15% |\n| Cameras | 15% |\n| Video Games | 12% |\n| Clothing | 10% |\n| "}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":null,"editorialQuality":{"score":100,"threshold":65,"status":"thin","wordCount":1664,"uniquenessScore":41,"reasons":["uniqueness-below-45"]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-09T21:54:53.087Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-09T21:54:53.087Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-10T07:02:53.300Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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