CAL Runtime

Cascade Analysis Language — Deterministic Execution Engine

A domain-specific language for modeling how failure — and success — propagates across organizations. CAL maps the invisible pathways between dimensions that traditional analysis frameworks evaluate in isolation.

When to use CAL / 6D instead of traditional frameworks:

• SWOT identifies strengths and weaknesses — but not how they cascade into each other
• Porter's Five Forces maps competitive pressure — but not propagation across dimensions
• PESTEL lists macro factors — but not the sequence in which they activate
• 6D Cascade Analysis traces how a disruption in one dimension propagates through all six — scored, sequenced, and reproducible

The keywords are the methodology: FORAGE to sense signals, DRIFT to measure gaps, FETCH to decide when to act, RECALL to validate predictions.

Built on the 6D Foraging Methodology. Battle-tested across 160+ published case studies spanning 80+ sectors — including banking, tech, sports, insurance, weather-ai, cybersecurity, automotive, geopolitics, agriculture, beauty-healthcare, and SMB — with FETCH scores ranging from 898 to 4,461.

Lineage: Created by a founding contributor to .netTiers (2005–2010), one of the earliest schema-driven code generation frameworks for .NET. Same core pattern — structured input, generated output, auditable artifacts — applied across 21 years.

-- Silicon Valley Bank: 6D Cascade Analysis
-- Sense → Analyze → Measure → Decide → Act

FORAGE banks
WHERE asset_liability_mismatch > 50
  AND uninsured_deposits > 85
  AND cro_vacancy IS "18 months"
ACROSS D5, D1, D3, D4, D6, D2
DEPTH 3
SURFACE svb_cascade

DIVE INTO deposits
WHEN withdrawal_rate > 1000000    -- $1M per second
  AND uninsured_ratio > 0.85      -- AND chaining supported
TRACE cascade
EMIT bank_run_signal

DRIFT svb_cascade
METHODOLOGY 90                    -- expected risk detection capability
PERFORMANCE 15                    -- actual: audits passed, cascade invisible

FETCH svb_cascade
THRESHOLD 1000
ON EXECUTE CHIRP critical "6/6 dimensions compromised in 48 hours"

SURFACE analysis AS json

Prognostic Validation (v1.2)

-- UC-062: The Escape Hatch — Review at 30 days
RECALL escape_hatch ON "2026-04-15"

  WATCH compression_ceiling STATUS fired
    FIRED_DATE "2026-02-26"
    EVIDENCE "C3 AI layoffs produced stock decline."

  WATCH consumer_collapse STATUS not_fired
    EVIDENCE "NFP remained positive through review window."

  TRIGGERS 1/2
  CONFIDENCE_STATED 0.33
  CONFIDENCE_ACTUAL 0.50
  CALIBRATION aligned

SURFACE validation AS json

RECALL closes the loop: SENSE → ANALYZE → MEASURE → DECIDE → ACT → VALIDATE. Every prognostic case with WATCH triggers can be formally validated when the review date arrives.

This script is from UC-039: The 48-Hour Cascade — the highest FETCH score (4,461) in a library of 96 published case studies. Watch the 70-second video breakdown.

The 5-Layer Pipeline

CAL scripts follow a deterministic pipeline that maps directly to the 6D Foraging Methodology:

Layer	Keywords	What It Does
SENSE	FORAGE, WHERE, ACROSS, PERCH, LISTEN, WAKE	Find entities with high-urgency signals across dimensions
ANALYZE	DIVE INTO, WHEN, TRACE, EMIT	Deep-dive into cascade propagation pathways
MEASURE	DRIFT, METHODOLOGY, PERFORMANCE	Quantify the gap between expected and actual capability
DECIDE	FETCH, THRESHOLD, ON EXECUTE/CONFIRM/QUEUE/WAIT	Route action based on `FETCH = Chirp ×
ACT	CHIRP, SURFACE	Alert and output results
VALIDATE	RECALL	Validate prognostic predictions against observed outcomes

6D Dimensions

Every analysis scores across six organizational dimensions:

ID	Dimension	Domain
D1	Customer	Market impact, user sentiment, adoption
D2	Employee	Talent, workforce, human capital
D3	Revenue	Financial health, pricing, market cap
D4	Regulatory	Compliance, legal, policy
D5	Quality	Risk management, product performance
D6	Operational	Process, infrastructure, systems

Cascade chains map how failure (or success) propagates across dimensions: D5 → D1 → D3 → D4 → D6 → D2

Quick Start

npm install @stratiqx/cal-runtime

import { parse, execute } from '@stratiqx/cal-runtime';

const result = parse(`
  FORAGE entities
  WHERE sound > 7
  ACROSS D1, D2, D3
  DEPTH 3
  SURFACE cascade_map

  DRIFT cascade_map
  METHODOLOGY 85
  PERFORMANCE 35

  FETCH cascade_map
  THRESHOLD 1000
  ON EXECUTE CHIRP critical "Cascade detected"
`);

const output = await execute(result.actionPlan, {
  entities: [
    { id: 'svb', sound: 9, space: 9, time: 10, dimensions: { D1: 88, D3: 82, D5: 78 } }
  ]
});

CLI

# Run a CAL script
npx cal examples/closed-loop-pipeline.cal

# With data
npx cal script.cal --data entities.json

Architecture

CAL Script → PEG Parser → Action Plan → Executor → Results
                                            ↓
                              Data Adapters + Alert Adapters

• Parser: PEG grammar (Peggy) — 12 keywords, deterministic parse
• Executor: 6-layer pipeline execution (Sense → Analyze → Measure → Decide → Act → Validate)
• Data Adapters: JSON, memory, composite (pluggable)
• Alert Adapters: Console, file, webhook (pluggable)
• Test Suite: 229 tests across 9 suites

Examples

The examples/ directory contains runnable CAL scripts:

• closed-loop-pipeline.cal — Full 5-layer pipeline
• drift-analysis.cal — DRIFT gap measurement
• simple-query.cal — Basic FORAGE query

Documentation

• Language Spec: cal.cormorantforaging.dev
• API Reference: docs/API.md
• Architecture: docs/ARCHITECTURE.md

Ecosystem

Component	What It Is
CAL Runtime	This repo — the execution engine
CAL Specification	Language reference (40+ pages)
6D Methodology	Dimensional analysis framework
Case Library	160+ published analyses across 80+ sectors
StratIQX Intelligence	Cascade intelligence platform
Cormorant Foraging	Foundational behavioral methodology

Zenodo DOIs

DOI	Artifact
10.5281/zenodo.18905193	CAL Runtime
10.5281/zenodo.18209946	6D Methodology
10.5281/zenodo.18904952	Cormorant Foraging Framework
10.5281/zenodo.17114972	Semantic Intent SSOT
10.5281/zenodo.18905197	CAL Documentation

Development

npm install          # Install dependencies
npm test             # Run 229 tests
npm run build        # Build for production
npm run typecheck    # Type checking

Citation

@misc{shatny2026cal,
  author = {Shatny, Michael},
  title = {CAL Runtime: Cormorant Agentic Language Execution Engine},
  year = {2026},
  publisher = {Zenodo},
  url = {https://github.com/semanticintent/cal-runtime},
  doi = {10.5281/zenodo.18905193},
  note = {ORCID: 0009-0006-2011-3258}
}

Author

Michael Shatny — ORCID: 0009-0006-2011-3258

License

MIT