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Price

面向消费者与企业采购的价格分析 Skill:对比当前价与 90 天低点及历史区间,核算含运费、税费的总成本,判断季节性时机,并识别虚高划线价、动态定价、虚假紧迫感等操纵手法,给出带置信度的购买结论;可在 ~/price/ 工作区维护 watchlist、价格历史与提醒,并按零售、旅行、B2B、收藏品等场景分文件补充规则。

ivangdavila
ivangdavila
热度 87.57
最近更新 2026-05-11 17:25:42
分类:生活依赖:读写文件应用场景:购物 / 市场分析 / 推荐 / 旅行

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add price
Metadata
name
Price
slug
price
version
1.0.0
description
Track prices, detect deals and manipulation, time purchases, and make informed buying decisions as a consumer or business buyer.
metadata
{"clawdbot":{"emoji":"💰","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

When 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:

  1. Historical context — Current vs 90-day low, all-time low, typical range
  2. Total cost — Add shipping, tax, fees, warranty, hidden costs
  3. Timing factors — Seasonal patterns, upcoming sales, event-driven spikes
  4. 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

  1. Ask what categories user buys frequently
  2. Set up preferred retailers list
  3. Configure alert notification preferences
  4. Explain price history data sources available
  5. Add first items to watchlist