@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
                      │
                      ▼
         🎛️  @aiready/cli (orchestrator)
          │     │     │     │     │     │     │     │     │     │
          ▼     ▼     ▼     ▼     ▼     ▼     ▼     ▼     ▼     ▼
        [PAT] [CTX] [CON] [AMP] [DEP] [DOC] [SIG] [AGT] [TST] [CTR]
          │     │     │     │     │     │     │     │     │     │
          └─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┘
                               │
                               ▼
                      🏢 @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 HERE

Features

• 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-analyzer

Usage

aiready scan . --tools context-analyzer

License

MIT