@aiready/context-analyzer
v0.9.40
Published
AI context window cost analysis - detect fragmented code, deep import chains, and expensive context budgets
Readme
@aiready/context-analyzer
AIReady Spoke: Analyzes import chains, fragmented code, and context window costs for AI tools.
Overview
AI model context windows are precious and expensive. The Context Analyzer identifies import chains, redundant dependencies, and complex data structures that bloat your context window and degrade AI reasoning performance.
🏛️ Architecture
🎯 USER
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🎛️ @aiready/cli (orchestrator)
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[PAT] [CTX] [CON] [AMP] [DEP] [DOC] [SIG] [AGT] [TST]
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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 ★ = 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
