Amazon Hot Products
Scout Amazon trending products, hot searches, new releases, and rising categories to find blue ocean opportunities early. Triggers: hot products, hot search,...
MIT-0 · Free to use, modify, and redistribute. No attribution required.
⭐ 0 · 54 · 0 current installs · 0 all-time installs
MIT-0
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description (scout Amazon trends) matches the SKILL.md: it defines commands, scoring, and required user-supplied data (BSR, search terms, category). There are no unrelated dependencies or credentials requested.
Instruction Scope
SKILL.md instructs the agent to analyze user-provided trend data and apply heuristics (BSR, search volume, reviews, seasonality). It does not direct reading system files, environment variables, or external endpoints beyond asking the user to paste data. The only persistence hint is 'hot save' which saves opportunities to agent memory — expected for this use case.
Install Mechanism
No install spec and no code files — instruction-only skill. Nothing will be downloaded or written to disk by the skill itself.
Credentials
The skill requests no environment variables, credentials, or config paths. It references Seller Central data conceptually but does not ask the platform for Seller Central credentials — user supplies data manually if desired.
Persistence & Privilege
always:false (normal). The skill includes a 'hot save' command implying use of agent memory to persist opportunities; this is proportionate but users should be aware saved opportunities may be retained by the agent's memory system and could contain sensitive business data.
Assessment
This skill is instruction-only and internally consistent with its purpose. Before installing: (1) Do not paste credentials, CSV files containing Seller Central login tokens, or other secrets — the skill expects pasted data only. (2) Confirm how your agent implementation handles 'memory' (what is stored, retention policy, and how to delete saved items) before using 'hot save'. (3) If you want additional safety, restrict the agent's allowed tools (the SKILL.md lists Bash as an allowed tool) so it cannot execute shell commands in your environment. (4) If you plan to use actual Seller Central/Brand Analytics data, consider extracting and sanitizing only the fields needed (search terms, counts, BSR) rather than full reports. (5) Optionally review the linked GitHub homepage to ensure there is no hidden code you need to be aware of before granting broader runtime privileges.Like a lobster shell, security has layers — review code before you run it.
Current versionv1.0.0
Download ziplatest
License
MIT-0
Free to use, modify, and redistribute. No attribution required.
SKILL.md
Amazon Hot Products & Trending Scout
Track Amazon's real-time hot searches, new releases, and rising categories. Spot trending products before they become saturated — find blue ocean opportunities early.
Commands
hot products # scan trending products across categories
hot search [category] # analyze hot search terms in category
hot new releases [category] # find new releases with early traction
hot movers [category] # find products with rapid BSR improvement
hot seasonal # identify upcoming seasonal trends
hot compare [cat1] [cat2] # compare trend momentum between categories
hot report # generate weekly trend report
hot save [opportunity] # save a trend opportunity to memory
What Data to Provide
- Category — broad (Electronics) or specific (Wireless Earbuds)
- BSR data — paste BSR rankings if you have them
- Search term data — trending search terms from Seller Central
- Time period — last 7/30/90 days
- Market — US, UK, DE, JP, etc.
No API key needed. Provide data verbally or paste raw numbers.
Trend Identification Framework
Signal 1: Search Volume Surge
- Search term appears in Amazon's "Hot New Keywords" (from Seller Central Brand Analytics)
- Week-over-week search volume growth >20%
- Low current competition (fewer than 1,000 results for exact match)
Signal 2: BSR Velocity
| BSR Movement | Signal Strength |
|---|---|
| BSR improved >50% in 30 days | 🔥 Strong |
| BSR improved 20–50% in 30 days | ✅ Moderate |
| BSR stable | ⚪ Neutral |
| BSR declining | ❌ Avoid |
Signal 3: Review Accumulation Rate
- New products getting 50+ reviews in first 60 days = high demand signal
- Multiple competitors launching simultaneously = category heating up
Signal 4: Seasonal Calendar
| Month | Trending Categories |
|---|---|
| Jan–Feb | Fitness, Organization, New Year |
| Mar–Apr | Outdoor, Garden, Spring Cleaning |
| May–Jun | Graduation, Father's Day, Summer |
| Jul–Aug | Back to School, Pool/Beach |
| Sep–Oct | Halloween, Fall Home |
| Nov–Dec | Holiday Gifts, Holiday Decor |
Blue Ocean Score (1–10)
Score each trending product opportunity:
- Demand (1–3): Search volume trend direction
- Competition (1–3): # of sellers, review counts, listing quality
- Margin (1–2): Estimated price point vs. likely COGS
- Differentiation (1–2): Can you improve on existing products?
Score 7+ = Enter aggressively Score 5–6 = Enter cautiously with differentiation Score <5 = Skip or monitor
Output Format
- Trending Opportunities — ranked list with Blue Ocean Score
- Category Heat Map — which categories are rising vs. cooling
- Early Entry Windows — products with <200 reviews but rising BSR
- Avoid List — saturated trends (too late to enter profitably)
- 30-Day Watch List — opportunities to monitor for next scan
Rules
- Always check review count before calling a trend "early" — >500 reviews = not early
- Flag categories with known high return rates (electronics, clothing)
- Distinguish between fad (short spike) and trend (sustained growth)
- Note when seasonal peaks are approaching — timing matters
- Always pair trend data with estimated margin — demand means nothing if margins are thin
Files
1 totalSelect a file
Select a file to preview.
Comments
Loading comments…
