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Evaluate CKB for Your Codebase

10 real-world testing scenarios for large codebases, monorepos, and enterprise teams. Each scenario tells you exactly what to try, which tools to use, and what to expect.

Quick Start (5 Minutes)

Step 1
Install
npm install -g @tastehub/ckb
Step 2
Initialize
cd your-repo && ckb init
Step 3
Index
ckb index
Step 4
Connect AI Tool
ckb setup
Step 5
Verify
ckb status && ckb doctor

Testing Scenarios

01

Tame Large Pull Requests

PRs with 600+ files burn tokens and overwhelm reviewers. AI tools hit context limits before they even start.

What to Try

  1. 1.Pick a recent large PR (ideally 100+ files)
  2. 2.Run summarizePr to get an intelligent summary without loading the full diff
  3. 3.Use analyzeImpact on the changed modules to see downstream effects
  4. 4.Run getAffectedTests to identify which tests actually need to run
Expected Result

A concise, structured PR overview instead of scrolling through hundreds of files. Reviewers see what matters.

Tools Used

summarizePrsummarizeDiffanalyzeImpactgetAffectedTests
02

Blast Radius Analysis

Changing a core header, shared utility, or base class in a monorepo can silently break dozens of modules. You only find out after the merge.

What to Try

  1. 1.Pick a central, frequently-included file (e.g. a shared header or core utility)
  2. 2.Run analyzeImpact to see the full propagation chain
  3. 3.Use getCallGraph to trace the dependency depth
  4. 4.Run auditRisk for a multi-factor risk assessment
Expected Result

Precise visibility into how far a change propagates. Risk scores that confirm your gut feeling with data.

Tools Used

analyzeImpactgetCallGraphtraceUsageauditRisk
03

Hidden Dependencies & Coupling

In a large, grown codebase, modules develop invisible coupling. Files that always change together, but no one knows why.

What to Try

  1. 1.Run analyzeCoupling on your core modules to see co-change patterns from git history
  2. 2.Use findCycles to detect circular dependencies at module or directory level
  3. 3.Run getArchitecture for a module dependency map
Expected Result

A data-driven view of your actual architecture vs. your intended architecture. Hidden coupling made visible.

Tools Used

analyzeCouplingfindCyclesgetArchitecture
04

Hotspot & Tech Debt Tracking

Everyone knows "that one file" that causes problems. But how many are there really? And which ones are getting worse?

What to Try

  1. 1.Run getHotspots on your repository to see churn data with trend analysis
  2. 2.Use auditRisk on the top hotspots for a deeper multi-factor assessment
  3. 3.Run suggestRefactorings to get actionable recommendations sorted by severity and effort
Expected Result

A prioritized list of problem areas with trend data. Not gut feelings, but numbers.

Tools Used

getHotspotsauditRisksuggestRefactorings
05

Ownership & Review Intelligence

CODEOWNERS says Team A owns a module, but Team B has been doing all the commits for months. Reviews go to the wrong people.

What to Try

  1. 1.Run getOwnership on a few key directories
  2. 2.Use getOwnershipDrift to compare CODEOWNERS vs. actual commit activity
  3. 3.Run getModuleResponsibilities to see what each module is supposed to do
Expected Result

Accurate, data-driven ownership that reflects reality. The right reviewers for every PR.

Tools Used

getOwnershipgetOwnershipDriftgetModuleResponsibilitiesgetReviewers
06

Dead Code & Cleanup

Years of development leave behind dead code, unused functions, abandoned features. Nobody dares to delete anything.

What to Try

  1. 1.Run findDeadCode for static dead code detection across the codebase
  2. 2.Use justifySymbol on suspicious symbols to check if they have any remaining purpose
  3. 3.If OpenTelemetry is available: use getObservedUsage to cross-reference with runtime data
Expected Result

Confidence-scored dead code candidates. Safe cleanup based on evidence, not hope.

Tools Used

findDeadCodefindDeadCodeCandidatesjustifySymbolgetObservedUsage
07

Trace Critical Paths

In safety-critical software, you need to know exactly how data flows through the system. How does a sensor input reach the UI? Where does a command pass through authorization?

What to Try

  1. 1.Use listEntrypoints to find all ingress points to a critical module
  2. 2.Run traceUsage to follow a symbol from definition to all consumers
  3. 3.Use explainPath to understand the call chain between two specific points
  4. 4.Run getCallGraph for a complete dependency visualization
Expected Result

Complete traceability from entry to exit. Essential for audit requirements and safety reviews.

Tools Used

traceUsageexplainPathgetCallGraphlistEntrypoints
08

Onboarding & Knowledge Transfer

New developers take weeks to understand a large codebase. Documentation is outdated. Tribal knowledge is everywhere.

What to Try

  1. 1.Use explore on a module to get a structured overview
  2. 2.Run understand on key symbols for deep dives with context
  3. 3.Use explainOrigin to understand why code exists and how it evolved
  4. 4.Query getDecisions to find Architectural Decision Records
Expected Result

AI-powered onboarding that gives new team members instant access to the full code knowledge base.

Tools Used

exploreunderstandexplainSymbolexplainFileexplainOrigingetDecisions
09

API Change Management

Internal APIs change, external integrations break. Nobody has a clear view of what changed between versions.

What to Try

  1. 1.Run compareAPI between two versions to see all API changes
  2. 2.Use listContracts to see all defined API contracts
  3. 3.Run analyzeContractImpact to check what breaks when a contract changes
Expected Result

Clear API change visibility across the monorepo. No more surprise breakages from internal API changes.

Tools Used

compareAPIlistContractsanalyzeContractImpactgetContractDependencies
10

CI/CD Integration

Running the full test suite on every PR takes too long. Static analysis generates noise, not signal.

What to Try

  1. 1.Set up the CKB daemon for automatic index refresh
  2. 2.Integrate getAffectedTests into your CI pipeline to run only relevant tests
  3. 3.Use the webhook API to trigger re-indexing from CI
  4. 4.Add quality gates with configurable risk thresholds
Expected Result

Faster CI pipelines that run targeted tests. Quality gates that catch real issues, not noise.

Tools Used

getAffectedTestsgetStatusreindex

Language Support

Enhanced Tier (SCIP Index)

Full symbol resolution, cross-references, call graphs, impact analysis. Supports Go, TypeScript, Python, Rust, Java, Kotlin, C++, Dart, Ruby, C#.

Basic Tier (LSP)

Any language with a language server. Navigation and references work, but no deep analysis.

Minimal Tier (Git)

Git-based features work for every file: ownership, hotspots, coupling, churn. No SCIP needed.

Custom or proprietary languages automatically get Minimal Tier coverage. All git-based analysis tools work regardless of language.

CKB Complements Your Existing Tools

CKB is not a linter or static analyzer. It makes your AI tools smarter by giving them structured code knowledge instead of raw source text.

Static Analyzers (SonarQube, etc.)

Find code smells, bugs, vulnerabilities. Rule-based analysis. Reports and dashboards.

CKB

Understands code structure, ownership, impact, and relationships. Answers questions. Feeds AI tools with intelligence instead of raw text.

Ready to try it?

Install CKB, index your codebase, and work through the scenarios that match your pain points. Most teams see value within the first hour.

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