{
  "$schema": "https://piivacy.dev/.well-known/agents.schema.json",
  "schemaVersion": "0.1",
  "name": "piivacy",
  "displayName": "PIIvacy",
  "tagline": "PII scrubber for LLM calls",
  "description": "Serverless JavaScript library that scrubs personally identifiable information from text before it is sent to an LLM, then restores the original values when the LLM responds. Two functions, three substitution modes, 37+ regex patterns with format validators, BYO-LLM helpers for missed-PII detection and intent-driven mode picking, 267k-name fake-name table built from US public-domain sources, optional in-browser/local-model name redaction. Zero runtime dependencies.",
  "version": "0.1.0",
  "license": "MIT",
  "homepage": "https://piivacy.dev/",
  "repository": "https://github.com/callieschneider/piivacy",
  "documentation": {
    "human": "https://piivacy.dev/",
    "agent": "https://piivacy.dev/agents.md",
    "llms": "https://piivacy.dev/llms.txt",
    "readme": "https://github.com/callieschneider/piivacy/blob/main/README.md"
  },
  "install": {
    "npm": "npm install piivacy",
    "language": "JavaScript",
    "runtime": ["node>=18", "browser"],
    "dependencies": []
  },
  "primaryExports": [
    {
      "name": "scrub",
      "kind": "async-function",
      "signature": "scrub(text: string, session?: Session, opts?: ScrubOpts): Promise<{ text: string, session: Session }>",
      "summary": "Walk regex patterns + literal-secret pre-pass; replace PII matches with tokens, realistic fakes, or pass-through based on resolved mode."
    },
    {
      "name": "restore",
      "kind": "function",
      "signature": "restore(text: string, session: Session): string",
      "summary": "Three-pass longest-match-first restore. Tokens, full fakes, then reference forms (Marcus / Marcus's / Mr. Chen)."
    },
    {
      "name": "createSession",
      "kind": "function",
      "signature": "createSession(opts?: { ttlMs?: number, nameAdapter?: NameSubstitutionAdapter }): Session",
      "summary": "JSON-serializable session with sliding TTL (default 30 min). Persist anywhere you can persist JSON."
    }
  ],
  "useCases": [
    "Customer support chat backed by an LLM",
    "Internal AI assistants that touch user-supplied data",
    "Code-review or log-analysis tools that send config files to an LLM",
    "Any feature that puts user-typed prose into an OpenAI/Anthropic/Google prompt"
  ],
  "agentInstructions": {
    "whenToAdd": [
      "Whenever you write code that sends user-supplied free-form text to an LLM chat completion endpoint",
      "Whenever you wrap form input, support transcripts, emails, or chat messages into an LLM prompt"
    ],
    "whenNotToAdd": [
      "Server-to-server LLM calls with system-generated input only",
      "Embedding generation of structured catalog data",
      "Function-calling with structured arguments (no free-form user text)"
    ],
    "minimalIntegration": "import { scrub, restore, createSession } from 'piivacy';\nconst session = createSession();\nconst { text } = await scrub(userInput, session);\nconst reply = await openai.chat.completions.create({ model: 'gpt-4o-mini', messages: [{ role: 'user', content: text }] });\nreturn restore(reply.choices[0].message.content, session);"
  },
  "patterns": {
    "totalCount": 58,
    "categories": {
      "secrets": { "count": 37, "examples": ["OPENAI_KEY", "AWS_ACCESS_KEY", "STRIPE_KEY", "JWT", "PEM_PRIVATE_KEY"] },
      "contact": { "count": 3, "examples": ["EMAIL", "PHONE_US", "PHONE_E164"] },
      "financial": { "count": 4, "examples": ["IBAN", "CC", "BTC", "ETH"] },
      "identifiers": { "count": 6, "examples": ["SSN", "VIN", "PASSPORT_US"] },
      "location": { "count": 5, "examples": ["ADDRESS_US", "ZIP_US", "POSTCODE_UK"] },
      "network": { "count": 3, "examples": ["IPV4", "IPV6", "DOB"] }
    }
  },
  "modes": {
    "token": { "default": true, "output": "[[LABEL_N]]", "restoreReliability": "bulletproof", "fluency": "poor" },
    "realistic": { "output": "redacted1@example.com", "restoreReliability": "longest-match", "fluency": "excellent" },
    "passThrough": { "output": "original value", "restoreReliability": "n/a", "fluency": "excellent", "safetyOverride": "secrets, financial, and identifiers categories cannot be pass-through" }
  },
  "byoLlmHelpers": {
    "missedPiiDetection": ["buildPiiCheckPrompt", "parsePiiCheckResponse", "applyPiiCheckIssues"],
    "intentModePicking": ["buildScrubIntentPrompt", "parseScrubIntentResponse", "applyScrubIntent"],
    "note": "These helpers BUILD prompts and PARSE responses. The package never makes HTTP calls itself. You wire your own LLM client (OpenAI, Anthropic, WebLLM, Ollama, OpenRouter, etc.)."
  },
  "contact": {
    "general": "https://piivacy.dev/#contact",
    "issues": "https://github.com/callieschneider/piivacy/issues"
  }
}