ContextThese prompts are engineered to make a CTO, CFO or data team stop scrolling and lean forward. Each one chains multiple MCP tools, crosses data domains, and produces something a human analyst would take hours - or days - to assemble. Say these exactly as written for maximum impact.
★ The Signature Move · Use this first
The End-to-End Intelligence Brief
This single prompt forces MCP to search, query, reason, build, and govern - all in one shot.
It demonstrates every capability tier simultaneously and produces a boardroom-ready deliverable on the spot.
A Qlik consultant with 15 years' experience would need 3 hours. MCP does it in under 90 seconds.
You are acting as my Principal Qlik Consultant.
I want a complete supplier quality intelligence brief on the SAP Procurement app.
Please do the following in a single workflow:
1. Find the top 5 vendors by defect rate
2. For each vendor, identify their worst-performing product
3. Calculate the financial cost of those defects using Cost of Goods
4. Build a new sheet called "Supplier Risk Brief" with:
- A KPI for total defect cost
- A bar chart: top vendors ranked by defect rate
- A table: vendor × product × defects × cost
5. Create a glossary term "Defect Rate" with a business definition and link it to this app
6. Give me a 5-sentence executive summary I can paste into a board report
Why it's a showstopper
1
Search + describe - MCP locates the app and reads its full metadata without you touching Qlik
2
Live computation - Defect rates calculated on real data, not pre-cached, using master measures
3
Instant visualisation - A production-quality sheet is built programmatically in the live app
4
Governed data catalog - A business glossary entry is created and linked to the actual data asset
5
Board-ready output - The executive summary is generated with real numbers, not placeholders
WHAT THE AUDIENCE SEES
A consultant typing one paragraph - and Qlik building itself in real time. That's the moment that sells MCP to a room.
Analytical Power
01
Cross-Domain Analysis
The Anomaly Hunt
⚡ Instant outlier detection
Without applying any selections, find me every vendor where the defect rate is more than 2× the company average.
For each one tell me:
- Which product drives it
- The cost exposure in USD
- Whether the same vendor appears in multiple company codes
Why it lands: "More than 2× the average" requires MCP to compute a benchmark first, then filter against it - two sequential analytical steps. It also crosses vendor, product and company code dimensions in one answer. No pre-built sheet does this.
02
Temporal Intelligence
Year-on-Year Regression
📈 Trend narrative, not just numbers
Compare defect rates year-by-year from 2016 to 2020.
Identify:
- Which year had the single biggest jump
- Which vendors drove that spike
- Whether the trend has been improving or deteriorating
Then tell me: if the current trajectory continues, what does 2021 look like?
Why it lands: Asks MCP to loop through years, compute deltas, identify causality, and forecast. The 2021 extrapolation forces real reasoning on top of live data - not just retrieval.
03
Risk Intelligence
The Concentration Risk Check
🔴 Board-level supply chain risk
I need a supplier concentration risk report.
Find any vendor that:
- Supplies to 3 or more company codes
- Has a defect rate above 0.15%
- Accounts for more than 5% of total spend
For each: name them, quantify the exposure, and tell me which single product I should put under incoming inspection first.
Why it lands: Three simultaneous filter conditions applied live to 505K rows. The "incoming inspection" recommendation forces MCP to prioritise - this is consulting-level output, not just a table dump.
Build & Govern
04
Dashboard Creation
Build the Sheet I Would Build
🏗️ Consultant-grade sheet, zero clicks
Act as a senior Qlik dashboard designer.
Build me a "Procurement Health Monitor" sheet with:
- 4 KPI tiles: Total Spend, Defect Rate, Cost of Defects, # At-Risk Vendors
- 1 combo chart: Monthly spend (bars) vs defect rate (line) for 2019–2020
- 1 treemap: Spend by vendor, coloured by defect rate
- 1 filter pane: Company Code, Year, Vendor Country
Use master items where available. Label everything for a CFO audience.
Why it lands: Calling MCP a "senior designer" and specifying chart types, audience tone and master item usage shows the audience that governance is automatic - the AI picks master items without being told which ones.
05
Data Governance
Instant Data Dictionary
📖 Governed catalog in minutes
Create a complete business glossary called "Procurement Quality Standards".
Add these terms with professional definitions:
- Defect Rate (link to the Defect Rate master measure)
- Cost of Poor Quality (link to Cost of Defective Products)
- Supplier Risk Tier (define High/Medium/Low criteria)
- Incoming Inspection (when it applies)
For each term, set status to "Under Review" and link it to the SAP Procurement app.
Why it lands: A governed data dictionary is normally a week-long governance project. Watching it happen live - with links back to actual measures - makes the "AI doing governance" moment visceral.
06
Expression Mastery
Translate This Expression
🧠 Make Qlik readable to anyone
Explain this Qlik expression in plain English, as if presenting to a finance director who has never used Qlik:
Sum({$<[POSTING_DATE.autoCalendar.Year]
={'$(=max(year([POSTING_DATE
.autoCalendar.Year]))-1)'}>}
[Defects])
Then tell me:
- What business question it answers
- How to modify it for a rolling 12-month window instead
- Whether a master measure already exists for this
Why it lands: MCP reads the actual measure library to confirm whether it already exists - it's not guessing. The rolling 12-month modification shows the AI can write new Qlik syntax on demand, not just read it.
Consultant Finesse
07
Geo Intelligence
The Sourcing Geography Audit
🌍 Supply chain geo-risk in seconds
Map our procurement risk by geography.
Tell me:
- Which vendor countries account for the highest defect rates
- Whether any single country represents more than 30% of defective spend
- Which country I should prioritise for supplier development if I had one budget line
Rank countries by a combined score of: spend volume × defect rate.
Why it lands: "Prioritise for supplier development if I had one budget line" is a constraint-based decision prompt. MCP has to rank, score and recommend - genuine advisory output, not reporting.
08
What-If Scenario
The Elimination Test
💡 Scenario modelling, live
Hypothetically remove our top 3 highest-risk vendors from the data.
What would happen to:
- Overall defect rate
- Total cost of poor quality
- Which vendor would become the new top risk
Give me the before/after as a clean comparison table, and tell me if the improvement justifies the supply chain disruption risk.
Why it lands: Exclusion-based set analysis is a Qlik superpower most analysts never learn. Watching MCP apply and clear selections to simulate vendor removal is a "how did it do that?" moment every time.
09
The Full Audit
Describe This App Like You Built It
🗂️ Instant app documentation
You are inheriting this app from another consultant.
Give me a full technical handover document covering:
- Data model: tables, relationships, row counts
- All master measures and what they calculate
- All master dimensions and their source fields
- Any calculated dimensions or time intelligence
- Data sources and last reload date
- 3 things a new developer should know before editing this app
Why it lands: Documentation is the most-skipped step in every Qlik project. MCP does it instantly and completely - using the "inheriting consultant" framing makes it feel like a real handover, not a metadata dump.
All data, outputs, and examples presented on this site are based on demo datasets for illustrative purposes only. No real customer, vendor, or business data is represented.