Measure technical debt with real numbers for your board.
Not gut feelings.

Get hard data on legacy code, complexity metrics, and tech debt hotspots. Justify engineering investments with facts.

Percentage of codebase untouched in 2+ years
Cyclomatic complexity by module
Test coverage gaps and dependency health

$85B Annual Cost

US companies spend $85 billion annually on technical debt. McKinsey

Get Tech Debt Report → Board-ready metrics in minutes, not weeks.

# cto-reports

CTO

James • CTO 3:00 PM

@context What percentage of our codebase would you classify as legacy?

critical.cx APP 3:00 PM

Based on analysis:

38% of files haven't been modified in 2+ years
Top debt hotspots:
• lib/payments/ - 89% legacy, high complexity
• app/models/user.rb - 2,400 lines, 45 methods
• lib/legacy_api/ - no test coverage

Response time: 14.2s

METRICS THAT MATTER

Data your board actually understands.

Legacy Code %

Age Analysis

What percentage of your codebase hasn't been touched in 1, 2, or 3+ years? Broken down by module.

Complexity Score

Risk Assessment

Cyclomatic complexity by file and function. Identify the files most likely to cause bugs.

Coverage Gaps

Quality

Test coverage by module. Which critical paths have no tests? Where are you flying blind?

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$ context tech-debt-report

Analyzing git history...

✓ 38% legacy code identified

Calculating complexity...

✓ 12 high-risk files found

Checking test coverage...

• 3 critical paths untested

$ █