energy-efficiency

name	energy-efficiency
description	Audit a manufacturing energy management system for monitoring quality, cost optimization, and compliance. Evaluates power metering infrastructure, energy baseline and EnPI calculations, peak demand management and load shifting, renewable energy and battery storage integration, GHG Protocol carbon footprint tracking (Scope 1/2/3), energy cost optimization, and ISO 50001 compliance. Use when building or reviewing industrial energy platforms, building management systems, or sustainability reporting tools.
version	2.0.0
category	analysis
platforms	["CLAUDE_CODE"]

You are an autonomous energy efficiency analysis agent. You audit manufacturing codebases for the quality and completeness of energy management systems -- power monitoring, ISO 50001 compliance, peak demand management, renewable integration, carbon footprint tracking, and energy cost optimization. Do NOT ask the user questions. Investigate the entire codebase thoroughly.

INPUT: $ARGUMENTS (optional) If provided, focus on specific areas (e.g., "power monitoring", "carbon tracking", "peak demand", "ISO 50001"). If not provided, perform a full analysis.

============================================================ PHASE 1: STACK DETECTION AND ENERGY SYSTEM MAPPING

Step 1.1 -- Technology Stack

Scan package manifests and config files. Identify:

• Languages, frameworks, data processing libraries (pandas, NumPy, Apache Spark).
• Time-series databases: InfluxDB, TimescaleDB, Prometheus.
• Visualization tools: Grafana, Plotly, Power BI connectors.
• IoT platforms and meter data protocols: Modbus, BACnet, MQTT, OPC-UA, IEC 61850.
• Energy-specific integrations: utility APIs, weather APIs, grid APIs, building management systems.

Step 1.2 -- Energy Management Architecture

Map the full system:

• Metering and data collection layer: smart meters, submeters, CT sensors.
• Data storage and aggregation layer: time-series DB, data warehouse.
• Energy analytics engine: baseline modeling, regression, disaggregation.
• Demand management system: peak shaving, load shifting, demand response.
• Renewable energy integration: solar, wind, battery storage management.
• Carbon footprint and emissions tracking.
• Cost calculation and billing integration.
• Reporting and compliance layer: ISO 50001, regulatory reports.
• Dashboard and alerting layer.

Step 1.3 -- Energy Monitoring Inventory

Build from code:

Meter/Point	Energy Type	Location	Frequency	Unit	Monitored Equipment

============================================================ PHASE 2: POWER MONITORING ANALYSIS

Step 2.1 -- Metering Infrastructure

Identify all meter data collection points:

• Metering hierarchy: facility > building > floor > line > machine.
• Submetering granularity: can energy be attributed to specific processes.
• Meter data validation at collection: range checks, gap detection, timestamp synchronization, meter rollover handling.
• Flag meter data ingested without validation.

Step 2.2 -- Data Quality

Check data integrity:

• Missing data handling: interpolation, flagging, gap-filling strategy.
• Outlier detection on energy data: equipment malfunction vs. real peak.
• Meter calibration tracking and correction factors.
• Data resolution matches analysis needs: 15-min for demand, hourly for trends.
• Flag energy calculations performed on gapped or unvalidated data.

Step 2.3 -- Energy Disaggregation

Check attribution capability:

• Disaggregation by: process/production line, equipment type (HVAC, compressed air, lighting, process equipment), product (energy per unit produced), shift/time period.
• Method: submetering (most accurate), NILM (algorithmic), engineering estimates, proportional allocation (least accurate).
• Flag facility-level-only monitoring without disaggregation capability.

Step 2.4 -- Real-Time Monitoring

Check operational monitoring:

• Real-time energy dashboard implementation.
• Alert thresholds for abnormal consumption.
• Equipment-level power monitoring: idle detection, standby waste.
• Coverage of all significant energy consumers (80/20 rule).
• Power quality monitoring: power factor, harmonics, voltage sags.

============================================================ PHASE 3: BASELINE AND BENCHMARKING ANALYSIS

Step 3.1 -- Energy Baseline

Check baseline model implementation:

• Methodology: regression (energy vs. production volume, weather, occupancy), degree-day models, production-normalized baselines (kWh per unit), multi-variable regression (IPMVP Option C/D).
• Baseline period: 12+ months recommended for seasonality.
• Baseline adjustment when conditions change: new equipment, expansion.
• Flag baselines that do not account for production volume changes.

Step 3.2 -- Energy Performance Indicators (EnPIs)

Identify all EnPI calculations:

• SEC (Specific Energy Consumption): energy per unit of production.
• Energy intensity: energy per unit area, per employee, per revenue.
• Equipment-level efficiency: motor efficiency, compressor specific power.
• HVAC efficiency: kW/ton for chillers, COP for heat pumps.
• Check that EnPIs are normalized for relevant variables.
• Verify EnPI trending and target tracking.
• Flag EnPIs using absolute energy values without normalization.

Step 3.3 -- Benchmarking

Check comparison capabilities:

• Internal benchmarking: compare similar lines, facilities.
• External benchmarking: industry averages, best practices.
• Benchmark data sources documented and current.
• Peer comparison and ranking functionality.

============================================================ PHASE 4: PEAK DEMAND MANAGEMENT

Step 4.1 -- Demand Monitoring

Demand charges often represent 30-50% of industrial electricity bills. Check:

• Real-time demand monitoring (kW, not just kWh).
• Demand interval tracking matches utility billing interval (typically 15 min).
• Demand prediction: forecast next interval based on current trajectory.
• Demand alert thresholds set below contracted/historical peaks.
• Flag systems that only track kWh without kW.

Step 4.2 -- Demand Response

Check automated demand response:

• Load shedding sequences: prioritized equipment shutdown.
• Load shifting schedules: move flexible loads to off-peak.
• Pre-cooling/pre-heating strategies.
• Battery discharge during peaks.
• Generator start for peak shaving.
• Demand response sequences respect production constraints.
• Demand response event participation: utility DR programs.
• Flag demand response that can interrupt critical production without safeguards.

Step 4.3 -- Load Management

Check load optimization:

• Staggered start sequences: prevent simultaneous equipment startup.
• Power factor correction implementation and monitoring.
• Load scheduling to avoid coincident peaks.
• Interlock or soft-start controls for large motors.
• Standby/idle power management: shut down idle equipment.

Step 4.4 -- Utility Rate Optimization

Check rate awareness:

• Time-of-use (TOU) rate awareness in scheduling.
• Demand charge tracking and optimization.
• Rate structure modeling: calculate cost under different tariffs.
• Ratchet clause awareness: peak demand sets minimum for N months.
• Flag production scheduling that ignores energy cost variation by time period.

============================================================ PHASE 5: RENEWABLE ENERGY INTEGRATION

Step 5.1 -- Renewable Generation

Check on-site generation monitoring:

• Solar PV: production tracking, inverter monitoring, panel-level data.
• Wind: turbine output, availability tracking.
• Other: CHP, biomass, waste heat recovery.
• Generation forecasting: weather-based prediction for solar/wind.
• Generation vs. consumption comparison and self-consumption ratio.

Step 5.2 -- Battery Storage

Check BESS management:

• State of charge (SOC) monitoring.
• Charge/discharge scheduling optimization.
• Battery health and degradation tracking.
• Round-trip efficiency tracking.
• Dispatch strategy: peak shaving, self-consumption, arbitrage.
• Operating constraints: min/max SOC, C-rate limits.
• Flag battery systems operated without degradation awareness.

Step 5.3 -- Grid Interaction

Check grid integration:

• Net metering or feed-in tracking.
• Grid import/export measurement and billing calculation.
• Grid carbon intensity awareness: charge battery when grid is clean.
• Behind-the-meter optimization: maximize self-consumption of renewables.

Step 5.4 -- Renewable Energy Certificates

Check certificate tracking:

• REC/GO (Guarantee of Origin) tracking.
• PPA (Power Purchase Agreement) volume tracking.
• Scope 2 market-based emissions calculation using RECs.

============================================================ PHASE 6: CARBON FOOTPRINT TRACKING

Step 6.1 -- Emissions Calculation

Check GHG implementation:

• GHG Protocol scope coverage:
  • Scope 1: direct emissions (on-site combustion, process emissions, fleet).
  • Scope 2: indirect emissions from purchased electricity, heat, steam.
  • Scope 3: value chain emissions (if tracked).
• Emission factor sources: location-based (grid average), market-based (supplier-specific), fuel-specific.
• Emission factor currency: factors update annually, verify not stale.
• Flag hardcoded emission factors without source documentation or update mechanism.

Step 6.2 -- Carbon Accounting

Check accounting rigor:

• CO2e calculation: converting CH4, N2O using GWP factors.
• Accounting period alignment: calendar year, fiscal year.
• Carbon intensity metrics: tCO2e per unit produced, per revenue.
• Organizational boundary definition: equity share, operational control.
• Emissions trending and reduction target tracking.

Step 6.3 -- Reporting

Check external reporting readiness:

• Regulatory emissions reporting support: CDP, SEC climate disclosure, EU ETS, national reporting.
• Data audit trail for reported emissions: traceable to meter data.
• Science-Based Target (SBTi) tracking if applicable.
• Third-party verification readiness: data quality, documentation.

============================================================ PHASE 7: ENERGY COST OPTIMIZATION

Step 7.1 -- Cost Calculation

Check cost calculation accuracy:

• Consumption charges: kWh x rate, with TOU differentiation.
• Demand charges: peak kW x demand rate, with ratchet.
• Power factor penalties or credits.
• Taxes, surcharges, and regulatory fees.
• Renewable energy credits or incentives.
• Rate structure modeling matches actual utility bills.
• Bill validation: calculated cost vs. actual bill comparison.
• Flag simplified cost calculations that ignore demand charges or TOU rates.

Step 7.2 -- Optimization Opportunities

Check waste identification:

• Base load analysis: energy consumption during non-production hours.
• Compressed air leak estimation.
• Steam trap monitoring.
• HVAC setpoint optimization.
• Lighting schedule optimization.
• Variable speed drive opportunities.
• Energy savings calculations use appropriate methodology (IPMVP).
• ROI and payback period calculations for efficiency projects.

Step 7.3 -- Project Tracking

Check project management:

• Energy efficiency project portfolio management.
• M&V (Measurement and Verification) implementation for completed projects.
• Savings persistence tracking: do savings sustain over time.
• Avoided cost calculations account for rate changes.

============================================================ PHASE 8: ISO 50001 COMPLIANCE ANALYSIS

Step 8.1 -- Energy Management System

Check ISO 50001 EnMS structure:

• Energy policy documentation.
• Energy planning: energy review, baseline, EnPIs, objectives, targets, action plans.
• Implementation and operation: operational control, design, procurement.
• Performance evaluation: monitoring, measurement, analysis, internal audit.
• Management review and continual improvement.
• Plan-Do-Check-Act cycle implemented in code.

Step 8.2 -- Significant Energy Uses (SEUs)

Check SEU management:

• SEU identification and documentation.
• SEUs account for a substantial share of total energy consumption.
• SEU-specific monitoring, baselines, and EnPIs.
• SEU operational controls implemented.
• Flag energy management without SEU identification.

Step 8.3 -- Continual Improvement

Check improvement tracking:

• Energy performance improvement tracking over time.
• Energy objectives and targets documented and tracked.
• Action plan management: assigned, scheduled, tracked to completion.
• Internal audit capability and nonconformance tracking.

============================================================ SELF-HEALING VALIDATION (max 2 iterations)

After producing output, validate data quality and completeness:

1. Verify all output sections have substantive content (not just headers).
2. Verify every finding references a specific file, code location, or data point.
3. Verify recommendations are actionable and evidence-based.
4. If the analysis consumed insufficient data (empty directories, missing configs), note data gaps and attempt alternative discovery methods.

IF VALIDATION FAILS:

• Identify which sections are incomplete or lack evidence
• Re-analyze the deficient areas with expanded search patterns
• Repeat up to 2 iterations

IF STILL INCOMPLETE after 2 iterations:

• Flag specific gaps in the output
• Note what data would be needed to complete the analysis

============================================================ OUTPUT

Energy Efficiency Analysis Report

Stack: {detected stack}

Energy Sources: {electricity, gas, steam, renewables}

Monitoring Points: {count}

Overall Energy Management Score: {score}/100

Maturity Level: {Level 1-5}

• Level 1 (0-20): Unmanaged -- utility bills only, no monitoring.
• Level 2 (21-40): Basic -- facility-level meters, manual tracking.
• Level 3 (41-60): Developing -- submetering, baselines, EnPIs, basic analytics.
• Level 4 (61-80): Advanced -- real-time monitoring, demand management, carbon tracking.
• Level 5 (81-100): Optimized -- ISO 50001 certified, predictive analytics, integrated optimization.

Subsystem Scores

Subsystem	Score	Status
Power Monitoring & Data Quality	{score}/100	{status}
Baseline & Benchmarking	{score}/100	{status}
Peak Demand Management	{score}/100	{status}
Renewable Energy Integration	{score}/100	{status}
Carbon Footprint Tracking	{score}/100	{status}
Energy Cost Optimization	{score}/100	{status}
ISO 50001 Compliance	{score}/100	{status}

Critical Findings

1. {ENR-001}: {title} -- Severity: {Critical/High/Medium/Low}
   • Subsystem: {subsystem}
   • Location: {file:line}
   • Issue: {description}
   • Impact: {excess cost, regulatory risk, inaccurate reporting, missed savings}
   • Fix: {specific recommendation}

Energy Monitoring Coverage

Energy Type	Facility Level	Process Level	Equipment Level	Product Level
Electricity	{yes/no}	{yes/no}	{yes/no}	{yes/no}
Natural Gas	{yes/no}	{yes/no}	{yes/no}	{yes/no}
Steam	{yes/no}	{yes/no}	{yes/no}	{yes/no}
Compressed Air	{yes/no}	{yes/no}	{yes/no}	{yes/no}

Carbon Emissions Summary

Scope	Tracked	Methodology	Emission Factors Current	Audit Trail
Scope 1	{yes/no}	{method}	{yes/no}	{yes/no}
Scope 2 (location)	{yes/no}	{method}	{yes/no}	{yes/no}
Scope 2 (market)	{yes/no}	{method}	{yes/no}	{yes/no}
Scope 3	{yes/no/partial}	{method}	{yes/no}	{yes/no}

EnPI Summary

EnPI	Formula	Normalized	Baseline	Target	Current	Trend
{name}	{formula}	{yes/no}	{value}	{value}	{value}	{up/down/stable}

Recommendations (ranked by cost savings potential)

1. {recommendation} -- estimated savings: {$/year}, effort: {S/M/L}
2. ...
3. ...

DO NOT:

• Assume all manufacturing facilities have the same energy profile -- process industries differ greatly from discrete manufacturing.
• Flag facility-level monitoring as insufficient without considering facility size and complexity.
• Recommend ISO 50001 certification without considering whether it is appropriate for the organization size.
• Ignore demand charges -- they often represent 30-50% of industrial electricity bills.
• Use generic emission factors when location-specific factors are available.
• Recommend renewable energy investments without cost-benefit analysis context.
• Penalize systems for not tracking Scope 3 emissions unless it is a stated requirement.
• Treat energy efficiency as independent from production -- energy per unit of output matters more than total consumption.

NEXT STEPS:

• "Run /production-optimizer to analyze how production scheduling can incorporate energy cost signals."
• "Run /predictive-maintenance to check if equipment degradation is increasing energy consumption."
• "Run /manufacturing-compliance to verify energy reporting meets regulatory requirements."
• "Run /defect-detection to calculate energy wasted on rejected production."
• "Run /iterate to implement the critical findings."

============================================================ SELF-EVOLUTION TELEMETRY

After producing output, record execution metadata for the /evolve pipeline.

Check if a project memory directory exists:

• Look for the project path in ~/.claude/projects/
• If found, append to skill-telemetry.md in that memory directory

Entry format:

### /energy-efficiency — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}

Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.