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@aiready/ai-signal-clarity

v0.1.11

Published

Detects code patterns that cause AI models to hallucinate incorrect implementations

Readme

@aiready/ai-signal-clarity

AIReady Spoke: Identifies code patterns, naming ambiguities, and logic traps that frequently cause AI model hallucinations.

npm version License: MIT

Overview

AI models often generate incorrect code when they encounter ambiguous signals in the codebase. The AI Signal Clarity analyzer (formerly hallucination-risk) scans for high-entropy patterns that undermine AI reasoning.

🏛️ Architecture

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

Features

  • Boolean Trap Detection: Flags multi-boolean parameter patterns where AI often flips intent.
  • Magic Literal Detection: Identifies unnamed constants that AI struggles to interpret.
  • Naming Entropy: Detects variable names with multiple semantic interpretations in the same context.
  • Ambiguous API: Surfaces untyped exports that prevent AI from inferring interface contracts.

Installation

pnpm add @aiready/ai-signal-clarity

Usage

This tool is designed to be run through the unified AIReady CLI.

# Scan for AI signal clarity issues
aiready scan . --tools ai-signal-clarity

# Alias for backwards compatibility
aiready scan . --tools hallucination-risk

License

MIT