Works with the AI Agents you already use
Retail Deal Intelligence
Rank retail promotions by genuine net savings, product fit, eligibility, stock, and purchase timing.
$9.99
Retail Deal Intelligence
Example session with this skill installed
A retailer advertises 30% off a $200 blender, but the usual price may be $170. Build a deal-verification checklist.
- Read your context and instructions
- Compiled the retail deal intelligence
Retail Deal Intelligence: practical plan
Deal verification
Reference price
Check the retailer’s recent price history and compare the exact model, bundle and warranty. A $200 reference price may not reflect the typical selling price. Calculate the advertised price ($140) and compare it with the recent $170 level: the practical discount is about 17.6% from that observed price, before taxes or shipping.
Product and terms
Verify model number, included accessories, stock, delivery, return window, warranty, open-box status, coupon eligibility and loyalty conditions. Confirm that the item fits the buyer’s actual need.
Total cost
Final cost = checkout price + shipping + tax + required membership or minimum-spend costs − rewards the buyer can realistically redeem. Do not value expiring points at face value.
Decision
Buy only if the product is needed and the verified total beats reasonable alternatives. Consider waiting if price history shows frequent promotions.
Record
Save the date, retailer, model, price and terms. Recheck at checkout because stock and offer eligibility can change. Avoid urgency claims based solely on countdown timers.
Measurement and review
Record the baseline, source, date range, denominator and owner. Use one primary measure plus quality guardrails; compare like-for-like cohorts and disclose missing data. Treat estimates as scenarios, not observed outcomes.
Risks and controls
Check relevance, consent, disclosure, workload and downside before scaling. Keep an evidence trail, obtain human review for material commitments, and pause if trust, quality or compliance signals deteriorate.
Next steps
- Confirm the goal, audience and available capacity.
- Gather the minimum evidence for a first test.
- Assign an owner, budget and review date.
- Run a small pilot, record outcomes and decide whether to iterate, expand or stop.
Connects securely to your tools. The creator never sees your data.
About this skill
Create a practical, evidence-led Retail Deal Intelligence workflow. Rank retail promotions by genuine net savings, product fit, eligibility, stock, and purchase timing. Distinguish observations from assumptions, request missing inputs, give actionable recommendations with owners and measurable outcomes, and flag uncertainty. Avoid fabricated metrics, unsupported guarantees, deceptive tactics and unnecessary personal data.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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