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Impact analysis example

What breaks when you change Trigger.dev (packages/trigger-sdk)?

Real arc impact output on Trigger.dev (packages/trigger-sdk) — same structure as the homepage demo. Know blast radius before you merge.

Project: Trigger.dev (packages/trigger-sdk) · Score: 92.7/100 (Excellent architecture) · 49 modules · 93 edges

Engineering decision simulation

Validation procedure 01 · merge vs. hold before output

Before arc impact

You plan a change to a high fan-in module in Trigger.dev (packages/trigger-sdk). Would you merge without knowing blast radius?

Typical answer: hold — need dependency context.

After arc impact

Structured output below: score, hotspots, corridors, and high-risk modules — same field schema as the homepage proof.

Decision: confirm hold, narrow change, or inspect paths first.

Published as part of the validation record. Run locally: arc impact <file-you-are-changing>

Architectural Risk Map

Where risk accumulates by control surface — drill down Surface → Substrate → Mechanism → Evidence.

See control surfaces →

Dependency evidence

Architecture visualization

Diagrams are generated from ArcSight analysis data. Dependency graph and risk map show key modules; subsystem view shows high-level structure.

Dependency graph
Dependency graph for this codebase
Subsystem architecture
Subsystem architecture for this codebase
Risk map
Risk map for this codebase

Architecture score & metrics

Score: 92.7/100 · Stability: 61/100 · Status: healthy · Confidence: 100%

  • Duplicate authorities: 19

Modules to inspect

One row per module. Fan-in is direct dependents. Blast radius is downstream modules reachable from that file.

Fan-in, direct dependents
  • src/v3/tracer17 dependents
  • src/v3/shared7 dependents
  • src/v3/ai-shared5 dependents
  • src/imports/ai-runtime3 dependents
  • src/v3/prompt3 dependents
  • src/v3/sessions3 dependents
  • src/v3/locals3 dependents
  • src/version1 dependents
Blast radius, downstream modules
  • src/v3/tracer24 modules
  • src/v3/shared7 modules
  • src/v3/ai-shared5 modules
  • src/imports/ai-runtime5 modules
  • src/v3/prompt5 modules
  • src/v3/sessions5 modules
  • src/v3/locals4 modules
ModuleFan-inBlastRisk
src/v3/tracer1724MEDIUM
src/v3/shared77LOW
src/v3/ai-shared55LOW
src/imports/ai-runtime35LOW
src/v3/prompt35HIGH
src/v3/sessions35HIGH
src/v3/locals34HIGH
src/version1LOW

Architectural gravity centers

  • src/v3/tracer— concentrates too many responsibilities
  • src/v3/tracer— shared utility hub

CLI workflow

Scan → Fix → Finish → Watch. Nothing else required.

  • arc scanFind issues
  • arc fixApply fixes
  • arc finishResolve remaining
  • arc watchKeep clean

More commands (explain, impact, guard…) →

Key takeaways

  • •Architecture score 92.7/100 indicates a healthy structure with room to reduce cycles and violations.
  • •High fan-in modules are change-risk zones; run arc explain <path> before refactoring.
  • •Run the full workflow (analyze, hotspots, explain, impact, snapshot, drift) in your repo for deterministic architecture insights.

Run ArcSight on your repo

Install the CLI and run analyze, then hotspots and explain for the same workflow.

npm install -g arcsight
arc analyze
Install ArcSight →

This case study is generated from ArcSight analysis data. View short analysis. View all analyses