Price
Verified@ivangdavila
npx machina-cli add skill @ivangdavila/price --openclawWhen to Use
User asks: "is this a good price?", "should I buy now or wait?", "track this price", "price history", "is this sale real?", "hidden fees", "compare prices", "price alert", "shrinkflation", "fair market value".
NOT for: setting prices as a seller (use pricing), general buying process (use buy), negotiation tactics.
Quick Reference
| Area | File |
|---|---|
| Retail & electronics | retail.md |
| Travel & hospitality | travel.md |
| B2B & enterprise | b2b.md |
| Collectibles & investments | collectibles.md |
| Manipulation detection | manipulation.md |
| Price tracking setup | tracking.md |
Workspace Structure
All data lives in ~/price/:
~/price/
├── config.md # Preferred retailers, alert thresholds
├── watchlist.md # Items being tracked with targets
├── history/ # Price history by item
├── alerts.md # Active price alerts
└── purchases.md # Past decisions for learning
Core Operations
Evaluate price: Current price + item → Check historical range → Calculate vs 90-day low → Factor total cost → Verdict with confidence level.
Set alert: Item + target price → Add to watchlist → Monitor across retailers → Notify when hit.
Track item: Product URL/name → Poll price periodically → Log to history → Detect changes.
Time purchase: Category + timeframe → Check seasonal patterns → Recommend buy/wait → Explain reasoning.
Price Assessment Framework
For EVERY price evaluation:
- Historical context — Current vs 90-day low, all-time low, typical range
- Total cost — Add shipping, tax, fees, warranty, hidden costs
- Timing factors — Seasonal patterns, upcoming sales, event-driven spikes
- Manipulation check — Inflated "was" price, dynamic pricing, fake urgency
Output Format
## Price Assessment: [Item]
**Current:** $X | **90-day low:** $Y | **All-time low:** $Z
**Total cost:** $W (includes: shipping, tax, fees)
**Verdict:** [Good deal | Fair | Wait | Overpriced]
**Why:** [Data-backed reasoning]
**Action:** [Buy now | Set alert for $X | Wait until Y]
**Confidence:** [High | Medium | Low] — [data quality note]
Critical Rules (ALWAYS Apply)
- Show data sources — Never claim price history without citing where it came from
- Include total cost — Listed price is not final price, always add fees
- State confidence level — Be honest about data quality and limitations
- Explain "why now" — If recommending buy, explain what makes timing good
- Flag manipulation — Always check for inflated comparisons, dynamic pricing
On First Use
- Ask what categories user buys frequently
- Set up preferred retailers list
- Configure alert notification preferences
- Explain price history data sources available
- Add first items to watchlist
Overview
Price helps consumers and businesses monitor item prices, detect genuine deals, and time purchases for total cost savings. It tracks price history, analyzes total cost including shipping, tax, and fees, and flags manipulation signals to inform buy decisions.
How This Skill Works
Core operations include evaluating current price against historical context, tracking items by URL or name, and setting alerts when a target price is reached. When evaluating, it uses historical context (90-day low, all-time low, typical range), adds total cost (shipping, tax, fees, warranty), considers timing factors, and runs a manipulation check before returning a data-backed verdict and recommended action.
When to Use It
- Is this a good price for a consumer item or business purchase?
- Should I buy now or wait for a sale based on seasonal patterns and upcoming events?
- Track this price across retailers to compare total cost over time.
- Is the current sale real, and are there hidden fees or inflated 'was' prices?
- Plan purchases by category and time horizon, weighing total cost and timing factors.
Quick Start
- Step 1: Set up your price workspace (~/price), and configure preferred retailers and alert thresholds.
- Step 2: Add items to your watchlist with target prices and data sources, then enable alerts.
- Step 3: Run your first price assessment and review the data-backed verdict and recommended action.
Best Practices
- Define a watchlist with realistic target prices for each item and retailer.
- Always include total cost (shipping, tax, fees, warranty, hidden costs) in the decision.
- Track multiple retailers to avoid single-source bias and verify price trends.
- Review price history data sources and data quality before acting.
- Use manipulation checks to flag inflated comparisons and dynamic pricing.
Example Use Cases
- A consumer tracks a laptop across electronics retailers and buys when the price reaches the target after including shipping and tax.
- A small business monitors printer ink pricing across vendors and times purchases during seasonal discounts for lower total cost.
- A traveler tracks flight prices and hotel rates and receives alerts when a price drop meets the target.
- The system flags a 'was' price that seems inflated on a television sale to avoid overpaying due to fake urgency.
- A retailer adds a bulk purchase alert to optimize procurement timing and minimize unit cost.
