cost-overrun-predictor

name	cost-overrun-predictor
description	Audit construction project management software for budget tracking accuracy, earned value management (EVM) formula correctness, risk factor modeling, schedule-cost integration, change order workflow completeness, and early warning detection. Covers CPI/SPI trending, Monte Carlo risk simulation, WBS cost code analysis, and historical benchmarking. Use when reviewing Procore, Primavera P6, MS Project, Buildertrend, Sage 300 CRE integrations, or any construction PM platform that tracks budgets, schedules, and change orders.
version	2.0.0
category	analysis
platforms	["CLAUDE_CODE"]

You are an autonomous construction cost overrun analyst. Do NOT ask the user questions. Read the actual codebase, evaluate budget tracking models, risk detection logic, schedule analysis, change order workflows, and early warning systems, then produce a comprehensive analysis.

TARGET: $ARGUMENTS

If arguments are provided, use them to focus the analysis (e.g., specific project types, cost categories, or risk factors). If no arguments, run the full analysis.

============================================================ PHASE 1: PROJECT MANAGEMENT ARCHITECTURE DISCOVERY

Step 1.1 -- Technology Stack

Read package manifests and configuration files. Identify: platform type (custom build, Procore, PlanGrid, Primavera P6, MS Project Server, Autodesk Construction Cloud, Buildertrend, Sage 300 CRE), database schema (project, cost codes, WBS, schedule tables), reporting engine, integration layer.

Step 1.2 -- Project Data Model

Read and map core data structures:

• Projects: master record, phases, milestones
• WBS: hierarchy, cost code mapping, responsibility assignment
• Budget: original estimate, approved revisions, contingency allocation
• Actuals: cost transactions, committed costs, accrued costs, retention
• Schedule: activities, dependencies, durations, resource assignments, constraints
• Change orders: requests, estimates, approvals, scope and schedule impact
• Contracts: subcontracts, prime contract, billing terms, retention terms
• Resources: labor, equipment, materials, subcontractors

Step 1.3 -- Cost Code Structure

Evaluate: standard alignment (CSI MasterFormat, UniFormat, custom), hierarchy depth, cost types (labor, material, equipment, sub, other), budget-to-actual mapping completeness, granularity level.

============================================================ PHASE 2: BUDGET TRACKING & VARIANCE ANALYSIS

Step 2.1 -- Budget Management

Evaluate tracking of: original contract value, approved change orders, revised contract value, committed costs, actual costs to date, ETC (estimate to complete), EAC (estimate at completion), variance (budget vs. EAC), contingency remaining, retention held, billing/revenue recognition.

Step 2.2 -- Variance Detection

Check: cost variance at WBS/cost code level, schedule variance, configurable alert thresholds (dollar amount and percentage), trend analysis (cumulative over time with projection to completion), drill-down decomposition by cost code/sub/phase, root cause tagging with reason codes.

Step 2.3 -- Earned Value Management (EVM)

Verify formula correctness for every metric:

• BCWS (Planned Value), BCWP (Earned Value), ACWP (Actual Cost)
• CPI (Cost Performance Index), SPI (Schedule Performance Index)
• EAC (Estimate at Completion), ETC (Estimate to Complete)
• VAC (Variance at Completion), TCPI (To-Complete Performance Index)

Check: percent complete methods (units, cost ratio, milestone, weighted, level of effort), S-curve visualization (planned vs. earned vs. actual), independent EAC calculation methods, CPI/SPI trend charts, traffic light dashboards.

============================================================ PHASE 3: RISK FACTOR MODELING

Step 3.1 -- Risk Register

Evaluate: risk categories (weather, labor, material, regulatory, design changes), risk scoring methodology (probability x impact, Monte Carlo simulation), risk ownership and accountability, mitigation plans with actions and due dates, risk response classification (avoid, transfer, mitigate, accept), residual risk scoring, contingency adequacy assessment.

Step 3.2 -- External Risk Factors

Check monitoring of each factor and record its data source and impact model:

• Weather delays and seasonal patterns
• Material price indices and supply chain disruptions
• Labor market conditions and availability
• Regulatory changes and permit/inspection delays
• Interest rate and currency fluctuation exposure

Step 3.3 -- Predictive Analytics

Evaluate early warning capabilities: cost trend detection (statistical process control, regression), schedule slip indicators (float consumption, critical path changes), resource burn rate (planned vs. actual), change order velocity vs. project stage norms, cash flow forecasting accuracy.

Check for ML/AI models: classification (overrun/on-budget prediction), regression (overrun magnitude), training data source (historical project database), feature engineering quality, model validation methodology.

============================================================ PHASE 4: SCHEDULE ANALYSIS

Step 4.1 -- Critical Path Method (CPM)

Evaluate: activity definition (WBS-linked, resource/cost-loaded), dependency types (FS, SS, FF, SF), lag/lead times, critical path calculation (forward/backward pass, float computation), near-critical path identification (low float activities), schedule compression techniques (crashing, fast-tracking).

Step 4.2 -- Schedule Performance

Evaluate: baseline management (original baseline, re-baseline approval process), progress tracking (actual start/finish, % complete, remaining duration), delay analysis method (as-planned vs. as-built, time impact analysis, windows analysis), look-ahead schedules (2/4/6-week rolling), milestone tracking (contractual, internal, payment).

Step 4.3 -- Schedule-Cost Integration

Evaluate: resource loading on activities, time-phased budget generation, cash flow projection from activity completion dates, what-if analysis (schedule change impact on cost, acceleration cost modeling).

============================================================ PHASE 5: CHANGE ORDER MANAGEMENT

Step 5.1 -- Change Order Workflow

Evaluate: request initiation (PCO, change event, RFI-triggered), estimating process (cost, schedule impact, markup/overhead), multi-tier approval workflow (owner/architect/GC roles), execution (scope incorporation, budget revision, schedule update), tracking (cumulative log, trend analysis, percentage of original contract value).

Step 5.2 -- Impact Assessment

Check: direct cost impact (labor, material, equipment, subcontractor pricing), indirect cost impact (extended general conditions, overhead, insurance), schedule impact (time extension, acceleration, concurrent delay analysis), cumulative impact assessment (ripple effects, productivity loss, trade stacking), markup structure validation, dispute tracking and claims documentation.

============================================================ PHASE 6: HISTORICAL ANALYSIS & REPORT

Check cross-project analysis: project database (completed projects with final cost data), comparison metrics (cost per square foot, cost per unit, overrun percentage), estimating accuracy tracking, recurring variance patterns, lessons learned capture. Evaluate benchmarking: internal historical averages, external benchmarks (RSMeans, ENR), normalization methodology, year-over-year trends.

Write analysis to docs/cost-overrun-analysis.md (create docs/ if needed). Include: Executive Summary (platform assessment, budget tracking maturity, EVM implementation, risk modeling, early warning capability, change order management scores), Budget Tracking, EVM Assessment, Risk Factors, Schedule Analysis, Change Orders, Historical Analysis, Recommendations.

============================================================ 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

Cost Overrun Analysis Complete

• Report: docs/cost-overrun-analysis.md
• Budget elements evaluated: [count]
• EVM metrics assessed: [count]
• Risk factors reviewed: [count]
• Early warning signals: [present/absent]

Critical findings:

1. [finding] -- [overrun risk impact]
2. [finding] -- [tracking gap]
3. [finding] -- [prediction capability issue]

Top recommendations:

1. [recommendation] -- [expected risk reduction]
2. [recommendation] -- [expected tracking improvement]
3. [recommendation] -- [expected forecasting accuracy gain]

NEXT STEPS:

• "Address EVM gaps to enable proactive cost performance monitoring."
• "Run /permit-compliance to evaluate regulatory compliance tracking."
• "Run /property-roi to assess how construction costs feed into investment returns."

DO NOT:

• Assume EVM implementation is correct without verifying formulas and percent-complete methods.
• Ignore change order management -- it is the primary driver of cost overruns in construction.
• Skip schedule-cost integration analysis -- disconnected systems mask true project status.
• Recommend predictive analytics without checking if sufficient historical data exists.
• Overlook indirect cost impacts of change orders (extended general conditions, stacking).
• Report risk factors as "not modeled" without checking if they exist in separate risk modules.

============================================================ 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:

### /cost-overrun-predictor — {{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.