DESIGN PREVIEW — Canonical sample fixture · schema v1.1 · Back to home

LAUNCH READINESS ASSESSMENT · REPORT ID 00000000-0000-4000-8000-000000000001
sample-repo
commit: 000000000000 · scanned January 1, 2026
73.1
LAUNCH WITH CONDITIONS
80–100 Launch Ready 60–79 Launch with Conditions 0–59 Do Not Launch
▲ Aura · Architectural Survivability IntelligenceThis report is independently verifiable · aura.dev/accuracyW3C PROV-DM · run 60s
01b

Aura Gate

probabilistic merge gate · LRS + P30 · marginal gradient
WARN
verdict

LRS in launch-with-conditions band; P30 above the 4% safety threshold.

6h
survivability debt

Across 3 ranked remediation actions

SDA tier
61DEVELOPING

VCRS 0.22 (MODERATE). Quality controls installed but partially wired.

next best actionT02ESLint blocking (--max-warnings=0)4hpriority 8
02

Executive Summary

CFO-readable · 90 seconds · no acronyms
050100
73.1
LAUNCH WITH CONDITIONS

The system scored 73.1 out of 100 on survivability. It can launch, but three issues must be addressed first.

1

A small group of people understands this system. Losing one creates real incident risk.

2

The codebase is navigable, but some areas have high cognitive load.

3

The system can survive some vendor failures, but not all critical ones.

Probability of a system-level failure in the next 30 days: 18.0%

02b

Outage Forecast

Monte Carlo · 10,000 simulations · 95% Wilson CI
P30
18.0%
probability · next 30 days
P90
45.0%
probability · next 90 days
P180
71.0%
probability · next 180 days
0%25%50%75%100%

Failure rate 4.3% per cascade · λeffective = 0.121 · CI95% [3.8%, 4.9%]. The model is structural — calibrates against real incident data after 100 customer assessments.

03

Survivability Risk Vector (SVR)

10 dimensions · CCR-weighted · IP-11 added S_sec · shape = colour-blind safe
Architecture Failure Containment Change Survivability Knowledge Continuity Data Survivability Operational Readiness Security Surface Economic Survivability Cognitive Load UX Readiness
Architecture
82A
Failure Containment
88A
Change Survivability
71B
Knowledge Continuity
55D
Data Survivability
93A+
Operational Readiness
74B
Security Surface
78B
Economic Survivability
65C
Cognitive Load
60C
UX Readiness
69C
04

Vendor Lock-In Matrix

switching cost × detection confidence · sorted by lock-in weight
bullmqjob-queue
0.60100%
drizzle-ormorm
0.5795%
@clerk/nextjsauth-provider
0.30100%
iorediscache-layer
0.2790%
posthog-nodeanalytics-pipeline
0.2480%
resendemail-service
0.0990%
vitebuild-tooling
0.0770%
Top two vendors by lock-in weight drive the majority of switching effort. Replacement is a multi-week migration; the rest are commodity.
05

Toolchain Enforcement Grid

Script Discovery (SDA)

0.610

DEVELOPING

CI enforces linting, type checking, and test coverage before any code reaches production. A breaking change cannot land without being caught first.

Validation Coverage (VCRS)

0.220

MODERATE

ESLint is installed but not enforced. It can run on a developer's machine — but it doesn't block a bad commit from reaching production. The tool is there; the protection isn't.

What to do (20 min):

Add 'eslint --max-warnings=0' as a required CI step. This is a single-line change in your workflow file. After that, no commit can bypass the linter.

ToolInstalledWired in CI
T02: ESLint blocking (--max-warnings=0) P0
T09: Pre-commit hook (lint-staged) P1
T16: ADR presence P4
06

Monte Carlo Failure Probability

10,000 simulations · Wilson CI ±1%
0%5%10%15%20%25%0d30d60d90d180d30d: 18.0%90d: 45.0%180d: 71.0%Days since last deploymentP(failure)

“System failure” = more than 30% of CCR-weighted nodes fail in a single cascade simulation. At current S_ops and S_fail scores, the 30-day probability is 18.0%.

07

Dimension Deep Dives

Three highest-impact dimensions shown
S_fail

Failure Containment

88
GOOD

Failures are well-contained and won't cascade into full outages.

Error isolation and queue-based decoupling mean a single component failure rarely becomes a system-wide incident.

What to do4 h+1.5 LRS pts

Add integration tests for your circuit breaker paths to ensure they work as designed when the real failure happens.

LRS impact: improving this dimension by 0.10 adds 1.5 LRS points.

S_k

Knowledge Continuity

55
NEEDS ATTENTION

A small group of people understands this system. Losing one creates real incident risk.

2–3 people own the critical code paths. The absence of any one of them significantly slows incident response. Knowledge transfer has started but isn't complete.

What to do1 day+5.0 LRS pts

Run a knowledge-transfer session for the top 5 highest-impact files. Each session should produce a short document: what it does, what can go wrong, and how to debug it.

LRS impact: improving this dimension by 0.10 adds 1.2 LRS points.

S_ops

Operational Readiness

74
GOOD

Every release is protected by automated quality gates.

CI enforces linting, type checking, and test coverage before any code reaches production. A breaking change cannot land without being caught first.

What to do2 h+2.0 LRS pts

Add mutation testing (Stryker) to find tests that pass without actually verifying anything. This is the next level of release protection.

LRS impact: improving this dimension by 0.10 adds 1.0 LRS points.

16

Remediation Roadmap

Ranked by priority score · estimated effort
Current LRS:73.1·3 actions · 6h total effort
P0
T02

ESLint blocking (--max-warnings=0)

est. 4h · Add `eslint --max-warnings=0` to lint script

8.2
P1
T09

Pre-commit hook (lint-staged)

est. 2h · Initialize husky and add a pre-commit hook

7.1
P2
T16

ADR presence

est. 45m · Write at least 3 ADR files documenting key architecture decisions

1.2
18

Provenance & Methodology

W3C PROV-DM Audit Trail

scan_id: 00000000-0000-4000-8000-000000000001
repo: sample-repo
commit: 0000000000000000000000000000000000000001
timestamp: 2026-01-01T00:00:00.000Z
run: 60s
engines: E1–E12 (E7 reserved)
spec: AURA/10_AURA_MATHEMATICS.md v1.1

Runtime Invariants

INV-M1Σ w_i = 1.000
INV-M2Σ CCR[i] = 1.0000
INV-M3All S_i ∈ [0,1]
INV-M4LRS ∈ [0,100]
INV-M5CCR[i] > 0 for all i
INV-M8S_change_adj ≤ S_change

This report is reproducible. Re-run npm run verify:engines against commit 000000000000 to produce identical scores.

Mathematical specification: aura.dev/accuracy · v1.1, May 2026