@aiready/context-analyzer
v0.22.31
Published
AI context window cost analysis - detect fragmented code, deep import chains, and expensive context budgets
Maintainers
Readme
@aiready/context-analyzer
AIReady Spoke: Analyzes import chains, fragmented code, and context window costs for AI tools.
Overview
AI tokens are expensive and context windows are finite. Context Analyzer helps you map dependencies and identify fragmentation that wastes AI resources.
Language Support
- Full Support: TypeScript, JavaScript, Python, Java, Go, C#
- Capabilities: Import depth, context budget, dependency mapping.
🏛️ Architecture
🎯 USER
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🎛️ @aiready/cli (orchestrator)
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[PAT] [CTX] [CON] [AMP] [DEP] [DOC] [SIG] [AGT] [TST] [CTR]
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🏢 @aiready/core
Legend:
PAT = pattern-detect CTX = context-analyzer ★
CON = consistency AMP = change-amplification
DEP = deps-health DOC = doc-drift
SIG = ai-signal-clarity AGT = agent-grounding
TST = testability CTR = contract-enforcement
★ = YOU ARE HEREFeatures
- Import Chain Analysis: Detects deep dependency trees that force unnecessary files into AI context.
- Fragmentation detection: Identifies modules that are split across too many small, non-semantic files.
- Context Budgeting: Projects the dollar cost of loading specific modules into frontier models (GPT-4, Claude 3.5).
Installation
pnpm add @aiready/context-analyzerUsage
aiready scan . --tools context-analyzerLicense
MIT
