@opena2a/ai-classifier

@opena2a/ai-classifier

Decides whether a package is AI-native, AI-adjacent, or unrelated so ai-trust, hackmyagent, and opena2a can route it correctly.

Why it exists

ai-trust is for AI packages. Scanning lodash with it produces confusing scores and wastes the user's time. This package is the shared rulebook that every OpenA2A CLI uses to answer one question: does AI trust apply to this package?

Tiers (v0.1)

Tier	Meaning	Example	ai-trust behavior
native	AI-specific (MCP server, A2A agent, skill, AI tool, LLM)	@modelcontextprotocol/server-filesystem	Full trust verification
adjacent	General-purpose but in the AI trust boundary	openai, dotenv	Stubbed in v0.3 → v0.4
unrelated	General-purpose library, no AI surface	express, chalk, typescript	Defer to HMA
unknown	Can't classify confidently	novel or unnamed packages	Surface uncertainty, let user decide

Usage

import { classify, isAiTrustScope } from "@opena2a/ai-classifier";

const result = classify({ name: "express", packageType: "library" });
// { tier: "unrelated", reasons: [], reasoning: "Registered as a general-purpose library" }

if (isAiTrustScope(result)) {
  // run ai-trust verification
} else {
  // route to HMA
}

Design rules

• Registry package_type is the strongest signal. We trust the registry's classification first.
• Name-based fallback is conservative. We only call a package "unrelated" by name when it's on a curated allowlist of well-known libraries (chalk, typescript, @types/*, etc.).
• Never false-classify as unrelated. Ambiguous packages return unknown, not unrelated. False rejections (dropping an AI package from an audit) are worse than uncertainty.