AACE-Recognized Methods · Audit-Trailed Math · Cross-Examination-Ready

Defensible delay analysis. Reproducible from the XER chain up.

The full forensic schedule toolkit — windows analysis (MIP 3.3), collapsed as-built (§3.8), TIA fragnet (52R-06), per-window concurrency, DCMA-14 health, Monte Carlo SRA. Every metric names the AACE recommended practice it implements. Every output cites its inputs. Built for the day a finish-date claim has to survive opposing counsel.

For construction lawyers, claims consultants, expert witnesses, and owners or contractors in dispute. The same thirteen tools are also callable directly from Claude or Cursor — the AI-native delivery path is how the engine stays fast and reproducible, not the headline. If you just want a free DCMA-14 read-out without the full forensic workup, the Schedule Health Report is the right door.

View sample analyses Talk to CPP

Schedule Health & Compliance

Grade the schedule before anyone argues over it.

DCMA-14 metrics, BEI, CPLI, false-criticality detection — the schedule audit that comes before any forensic argument. If the schedule fails compliance, the finish-date claim built on it is already weak.

dcma14_health_check

Schedule Health Dashboard

Full self-contained HTML dashboard — DCMA-14 plus CPLI, BEI, baseline-vs-current variance, slip register, GAO/AACE compliance bands, and a reproducibility manifest. Renders via headless Chromium.

DCMA 14-Point · GAO/AACE Bands

critical_path_validator

Critical-Path Validation

Logic health audit at the JSON layer — surfaces false criticality, constraint-driven CP segments, open ends, and the 14 DCMA metrics at the chosen profile (commercial, nuclear, mining). BEI when a baseline is supplied.

DCMA 14-Point · AACE 24R-03 §4

xer_parser

XER Table Summary

Parses a Primavera P6 XER and returns the table inventory — field lists, record counts, P6 export header, project name and data date. The structural confirmation step every downstream tool relies on.

Primavera P6 · XER Format

Forensic Delay Analysis

Six tools across the AACE-recognized methods.

Three AACE-recognized methods — windows analysis (MIP 3.3), collapsed as-built (§3.8), TIA fragnet (52R-06) — plus per-window concurrency, calendar-shaped execution, and slip-rate trending. Run independently on the same XER chain. When the windows result and the but-for result agree, the claim is defensible. When they diverge, the divergence is itself the story.

forensic_windows_analysis

Windows Analysis (Headline Tool)

Multi-snapshot forensic windows analysis — per-window completion shifts, slip register, critical-path duration growth, per-party attribution (Owner / Contractor / Concurrent / Force Majeure / Unattributed), and cumulative project drift.

AACE 29R-03 §3.3 · MIP 3.3 Observational/Dynamic

collapsed_as_built

Collapsed As-Built / But-For

Subtractive but-for analysis on the post-impact XER — per-event but-for finish, cumulative but-for finish, and a dual-method gap report that validates the windows-analysis result independently.

*Independent in methodology (windows + collapsed are mathematically distinct approaches); both are computed by CPP’s open-source engine — see DAUBERT.md §3 for the same-author crossval caveat.*

AACE 29R-03 §3.8 · Modeled/Subtractive

time_impact_analysis_fragnet

TIA Fragnet Insertion

Prospective fragnet insertion into a pre-impact baseline — per-fragnet completion impact in calendar AND project-calendar working days, plus cumulative impact across all fragnets.

AACE RP 52R-06 · Modeled/Additive

concurrent_delay_matrix^{[pre-publication]}

Per-Window Concurrency Matrix

Window-by-window apportionment grid — how each window distributed its shift across the parties. Conservation-checked: column totals equal grand-total shift within rounding.

AACE 29R-03 §4.1 · §4.2.B Concurrency

woet_classifier^{[pre-publication]}

Worked-vs-On-time Timeline

Calendar-shaped per-activity day classifier — PROGRESS, GAIN, EXTENDED, VOID. Gives the trier-of-fact a calendar picture of how the project executed against how it was supposed to.

MIP 3.4 Enhancement Layer

slip_velocity^{[pre-publication]}

Slip Velocity & Acceleration

Per-window slip-rate trend on top of windows analysis — signed velocity (days per day), finite-difference acceleration, and centroid midpoint estimate. Honest probabilistic caveats embedded.

AACE 29R-03 §3.3 · Trend Layer

Path Analysis

Why is this activity critical — and what does it drive?

Single-activity logic-trace investigation, with constraint-driven artificial-criticality detection cited per AACE 24R-03.

path_explorer

Driver-Chain Explorer

Traces driving predecessors back to project start (the "why critical" chain) and successors forward to finish (the "what it drives" chain). Detects constraint-driven artificial criticality, supports MCPM and near-critical paths.

AACE RP 24R-03 §4 · MCPM-Aware

Risk & Probabilistic

P50, P80, and the maturity tier behind them.

Monte Carlo SRA with sensitivity tornado, plus a QRAMM maturity badge that grades the SRA evidence on a CMMI-style 1-to-4 tier — with the right caveats.

monte_carlo_p50_p80

Monte Carlo Schedule Risk

Probabilistic finish-date forecast — P10/P50/P80/P90 with linear-interpolation percentiles. Triangular, BetaPERT, Uniform, Lognormal distributions. Per-activity sensitivity tornado correlated to project finish.

AACE-Style Quantitative SRA

qramm_maturity

QRAMM Maturity Tier

Scores an SRA result against the AACE 122R-22 Quantitative Risk Analysis Maturity Model — tier 1 (Initial) through tier 4 (Optimized) — with disclosed evidence, gaps to next tier, and an interpretive caveat.

AACE RP 122R-22 QRAMM

Evidence Workflow

From a folder of mixed evidence to a unified workbench.

The way real claim files actually arrive: schedule updates, owner correspondence, RFIs, change orders, meeting minutes — all mixed together in one folder. This tool turns that into structured forensic output.

claim_workbench_evidence_ledger

Evidence Ledger + Chain-Diff

Takes one folder of mixed evidence and produces: chronological evidence ledger, 14-category schedule manipulation chain-diff, per-activity rolling baseline, statistical-impossibility trust score, and a slip-to-evidence cross-reference.

XER Chain · MSG/PDF/DOCX/XLSX

MCP Tools

Analysis Modules

29R-03 · 122R-22
52R-06 · DCMA-14

Standards

728

Regression Tests

Why AI-Native

SaaS gives you a screen. MCP gives you a partner.

Conventional forensic software ships as a desktop app or a SaaS dashboard — you click, you wait, you copy results out. CPP's toolkit is exposed as MCP, which means Claude (or any agent) can chain the tools, reason over the JSON output, and write the analyst's draft. Different paradigm.

Callable from Claude

Conversation-driven analysis

"Run windows analysis on these XERs, then a collapsed as-built validation, then summarize the cumulative drift and which window contributed most." That's one prompt to Claude, three tool calls, one paragraph back. The tools chain themselves.

Scriptable

Same tools, batched in Python

Every MCP tool also has a Python entry point in the underlying engine. Run a hundred Monte Carlo simulations across a portfolio, batch a year of monthly DCMA reports, automate the claim package — same code path as the live demo.

Audit-trailed

JSON-safe outputs, deterministic math

Every tool returns structured JSON with raw values alongside rounded values, the standard it implements named in the response, and a methodology field explaining what the tool can and cannot conclude. Reproducible. Auditable. Defensible in deposition.

vs. SaaS competitors

No vendor lock-in, no per-seat tax

SmartPM, Forensic PM, the rest — great products, but you're locked into their UI and pay per seat. The CPP MCP is open-source-style: connect it from your own AI client, self-host if your firm requires air-gapped tools, source-access available on engagement.

Methodology Compliance

Each tool names the AACE recommended practice it implements.

No house-brand methods. Every forensic tool in the suite traces back to a published AACE Recommended Practice, DCMA standard, or peer-reviewed treatise — named in the tool output, traced in the dashboard, defensible on cross-examination.

forensic_windows_analysis

AACE MIP 3.3

Observational, dynamic, contemporaneous as-is windows analysis — per AACE 29R-03 §3.3.

collapsed_as_built

AACE MIP 3.8

Modeled, subtractive, single-simulation but-for analysis — per AACE 29R-03 §3.8.

time_impact_analysis_fragnet

AACE RP 52R-06

Modeled, additive, multiple-base TIA fragnet insertion (also known as MIP 3.7).

concurrent_delay_matrix

AACE 29R-03 §4

Concurrency apportionment per AACE §4.1 / §4.2.B; conservation-checked.

woet_classifier

MIP 3.4 Layer

Per-activity calendar-shaped day classifier, layered on the windows result.

slip_velocity

AACE 29R-03 §3.3

Slip-rate trend on top of windows analysis — honest probabilistic caveats embedded.

dcma14_health_check

DCMA 14-Point

DoD Defense Contract Management Agency 14-Point Schedule Assessment — full coverage.

critical_path_validator

AACE 24R-03 §4

Constraint-driven artificial-criticality detection per AACE 24R-03 §4; profile-aware.

path_explorer

AACE 24R-03 §4

Logic-trace driver-chain explorer with MCPM and near-critical-path detection.

monte_carlo_p50_p80

AACE-style QSRA

P10/P50/P80/P90 with linear-interpolation percentiles per AACE convention; tornado sensitivity.

qramm_maturity

AACE RP 122R-22

Quantitative Risk Analysis Maturity Model — tier 1 (Initial) to tier 4 (Optimized).

claim_workbench_evidence_ledger

SCL Protocol §11.5

Evidence ledger + 14-category chain-diff + statistical trust score + slip-to-evidence cross-reference.

xer_parser

Primavera P6

Canonical XER parser; structural confirmation every downstream tool relies on.

How to Connect

Three steps. Same thirteen tools either way.

Hosted MCP at mcp.criticalpathpartners.ca — pick your client, paste the URL or JSON, start using the tools. Full setup walkthrough on the Connect Claude page.

Install Claude (or your MCP client)

Claude.ai web (Pro / Max plan), Claude Desktop, Cursor, Cline — any client that speaks MCP works. The hosted server handles both Streamable-HTTP and SSE transports.

claude.ai · Claude Desktop
Cursor · Cline · others

Paste the MCP config

Web Claude: Settings → Connectors → Add custom connector. Desktop / Cursor / Cline: paste the JSON into your MCP config file. Same endpoint, two transport flavors.

https://mcp.criticalpathpartners.ca/mcp

Start using the tools

Ask your AI: "What MCP tools are available from cpp-forensic?" You'll see all thirteen. From there, drop in an XER pair and ask for windows analysis, a DCMA-14 check, or a Monte Carlo — whatever you need.

"Run forensic_windows_analysis
on baseline.xer + current.xer"

Just want a quick health check?

The Schedule Health Report runs DCMA-14 + GAO 16-89G + CPP Quality Overlay in 10 seconds — no setup, no Claude, no install. Drop two XERs in a browser tab and you're done.

Try the Schedule Health Report →

Connect the toolkit. Or hire the analyst behind it.

Thirteen tools, JSON-safe, connectable from Claude. The deeper work — deposable opinions, expert testimony, claims that survive cross-examination — runs through the analyst.

Connect via Claude → Just want a health check? Talk to CPP