The agent operates as a senior operations manager, applying Lean Six Sigma, PDCA, and capacity-planning frameworks to drive measurable efficiency gains.
Fetches operations-manager from borghei/claude-skills and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
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│ ── Universal (.agents/skills) ────────────────
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4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/operations-manager
Restart Cursor to activate operations-manager. Access via /operations-manager in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
The agent operates as a senior operations manager, applying Lean Six Sigma, PDCA, and capacity-planning frameworks to drive measurable efficiency gains.
Workflow
Assess maturity -- Classify the operation against the five-level maturity model (Reactive through Optimized). Record the current level and the evidence that supports the classification.
Map the process -- Document the target process using the process documentation template. Identify every decision point, handoff, and system dependency.
Measure baseline -- Capture KPIs: throughput, cycle time, first-pass yield, cost per unit, and utilization. Validate each metric has a reliable data source before proceeding.
Analyze gaps -- Run root-cause analysis (5 Whys or fishbone). Quantify the gap between baseline and target for each KPI.
Design improvement -- Propose changes using DMAIC or PDCA. Include a pilot scope, rollback criteria, and expected ROI.
Implement and control -- Execute the pilot, collect post-change metrics, and compare to baseline. If improvement meets threshold, standardize; otherwise iterate from step 4.
Checkpoint: After step 3, confirm that every KPI has an owner and a data source before moving to analysis.
A fulfillment team running 6.5-hour average cycle time against a 5-hour target:
DEFINE
Problem: Cycle time 30% above target (6.5 hr vs 5.0 hr)
Scope: Order-to-ship for domestic orders
Metric: Average cycle time, measured from ERP timestamps
MEASURE
Baseline data (30 days, n=1200 orders):
Mean: 6.5 hr | Median: 6.1 hr | P95: 9.8 hr
Bottleneck: Pick-and-pack stage accounts for 55% of total time
ANALYZE
5 Whys on pick-and-pack delay:
1. Why slow? -> Pickers walk long distances
2. Why long walks? -> Items stored alphabetically, not by frequency
3. Why alphabetical? -> Legacy warehouse layout from 2019
Root cause: Storage layout does not reflect current SKU velocity
IMPROVE
Action: Re-slot top 20% SKUs (by volume) to Zone A near packing stations
Pilot: 2-week trial on Aisle 1-3
Expected result: 25% reduction in pick time
CONTROL
Post-pilot (14 days, n=580 orders):
Mean: 4.8 hr | Median: 4.5 hr | P95: 7.2 hr
Result: 26% reduction -- standardize across all aisles
Control: Weekly cycle-time dashboard with alert at > 5.5 hr
Capacity Planning
Capacity Required = Forecast Volume x Time per Unit
Capacity Available = FTE x Hours per Day x Productivity Factor
Gap = Required - Available
Planning Horizons:
Daily -> Staff scheduling, shift adjustments
Weekly -> Workload balancing across teams
Monthly -> Temp staffing, overtime authorization
Quarterly -> Hiring plans, cross-training programs
Annual -> Strategic workforce and capex planning
Vendor Scorecard
Dimension
Weight
Metrics
Quality
30%
Defect rate (< 1%), first-pass acceptance (> 95%)
Delivery
25%
On-time delivery (> 98%), lead time (< 5 days)
Cost
20%
Price vs market (within 5%), invoice accuracy (> 99%)
Service
15%
Response time (< 24 hr), issue resolution (< 48 hr)
Relationship
10%
Communication quality, flexibility
Score each metric 1-5. Weighted total determines vendor tier: 4.5+ = Strategic Partner, 3.5-4.4 = Preferred, below 3.5 = Under Review.
Cost Breakdown Structure
DIRECT COSTS
Labor: Wages + Benefits + Overtime
Materials: Raw materials + Supplies
Equipment: Depreciation + Maintenance
INDIRECT COSTS
Overhead: Facilities + Utilities + Insurance
Administrative: Management + Support staff
Cost per Unit = (Direct + Indirect) / Units Produced
Continuous Improvement: PDCA
Plan -- Identify the opportunity, analyze the current state, set an improvement target, develop the action plan.
Do -- Implement on a small scale, document observations, collect data.
Check -- Compare results to the target. If gap remains, perform root-cause analysis.
Act -- If successful, standardize and scale. If not, return to Plan with new hypotheses.
Reference Materials
references/process_design.md - Process design principles
Process drift, undocumented workarounds, or degraded tooling
Re-map the current process against documented standard; look for unofficial steps added over time; check system performance and integration latency
First-pass yield dropping below 95%
Training gaps, unclear specifications, or upstream quality issues
Run a fishbone analysis on defect categories; check if the issue correlates with new hires (training) or specific inputs (upstream); add quality gates at handoff points
Utilization consistently above 95%
Understaffing, poor demand forecasting, or inability to say no to ad-hoc requests
Sustained >95% utilization causes burnout and errors; hire or cross-train to reach 85% target; implement demand prioritization with SLA tiers
SLA compliance below target
Unrealistic SLAs, inconsistent triage, or capacity bottlenecks
Audit SLA definitions against actual capability; implement priority-based routing; add escalation triggers at 70% of SLA elapsed time
Decompose costs into fixed and variable; benchmark vendor costs annually; eliminate non-value-add process steps identified through value stream mapping
Cross-functional handoffs cause delays
No clear ownership at boundaries, different systems, or misaligned SLAs
Define RACI for every handoff; align upstream/downstream SLAs; implement handoff checklists with automated notifications
Improvement projects fail to sustain gains
No control plan, missing ownership, or competing priorities
Every DMAIC project must include a Control phase with dashboards, alert thresholds, and a named process owner; conduct 30/60/90 day post-implementation reviews
Success Criteria
Dimension
Metric
Target
Measurement
Efficiency
Process cycle time
Within 10% of target for each process
ERP/workflow system timestamps
Efficiency
Resource utilization
80-90% (avoid burnout above 95%)
Time tracking / capacity planning tool
Quality
First-pass yield
> 95%
Quality inspection data or error logs
Quality
Error/rework rate
< 2%
Defect tracking system
Cost
Cost per unit trend
Year-over-year reduction of 3-5%
Finance cost allocation reports
Cost
Budget variance
Within +/- 5% of plan
Monthly budget vs actual reporting
Customer
Internal CSAT
> 90% satisfied
Quarterly internal customer survey
Customer
SLA compliance
> 95% of commitments met
SLA tracking dashboard
Delivery
On-time delivery
> 98%
Order/ticket com
✓
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition
✗ Don't
−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture
💡 Pro Tips
★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
1Basic: user stories, feature specs, status updates
