ping-identity-for-ai

ping-identity-for-ai

AI-era identity patterns: Identity for AI, Verified Trust, agent identity, agent security, and AI application authentication.

Invocation

Invoke explicitly with /ping-identity-for-ai or by saying "use ping-identity-for-ai to...".

When to use this skill

• "Give my AI agent a verified identity for API access"
• "Use Verified Trust signals in my MCP server"
• "Secure agent-to-agent authentication using Ping"
• "Workforce helpdesk AI — how do I authenticate users for my AI assistant?"
• "Identity for AI architecture with Ping"
• "AI app authentication patterns on PingOne"
• "Agent security and authorization for agentic workflows"
• "Short-lived tokens or token rotation for an autonomous agent"
• "Delegated token for an AI assistant acting on behalf of an employee"
• "Revoke a compromised AI agent's access immediately"

When NOT to use this skill

• General platform setup or tenant administration: use ping-foundation.
• Building a journey or DaVinci flow for human authentication (not AI-specific): use ping-orchestration.
• App SDK integration without AI context: use ping-app-integration.
• User is orienting or selecting a platform: use ping-quickstart.
• Using Ping Protect, PingOne Verify, or PingOne Authorize as standalone services without AI agent context: use ping-universal-services.
• "Automated process", "batch job", "scheduled task", or "service account" without any AI / LLM / agent context — ask a clarifying question to determine whether this involves an AI agent or a conventional machine process before routing here.

Multi-skill use cases

A complete AI identity solution typically spans multiple skills:

Layer	Skill
Platform setup and app registration	ping-foundation
Auth flow / journey / DaVinci design	ping-orchestration
AI identity patterns and Verified Trust	ping-identity-for-ai (this skill)
App / SDK integration	ping-app-integration

Example sequence:

1. ping-foundation — register the AI agent application and configure the environment.
2. ping-identity-for-ai — design the token scoping and delegation model (this skill).
3. ping-orchestration — build the step-up MFA flow using DaVinci or Journey.
4. ping-app-integration — integrate the OIDC client in the AI application.

Complete agent token scoping, Verified Trust signal design, and delegation model here, then hand off to ping-orchestration for step-up MFA flows and ping-app-integration for SDK/OIDC client wiring.

Routing — Step 1: What are you trying to do?

Task	Curated anchor
Overview / strategy for Identity for AI (5-pillar)	references/curated/identity-for-ai-overview.md
Register an AI agent as a managed identity	references/curated/agent-security-patterns.md
Machine-to-machine auth, token scoping, rotation, revocation	references/curated/agent-security-patterns.md
CIBA human-in-the-loop approvals for high-risk agent actions	references/curated/agent-security-patterns.md
Bot / agentic AI detection in flows (Protect)	references/curated/agent-security-patterns.md
Protect / secure an MCP server (PingGateway)	references/curated/agent-gateway-mcp.md
Apply Verified Trust signals or verifiable credentials	references/curated/verified-trust-overview.md
Workforce helpdesk AI — delegation + step-up pattern	references/curated/workforce-helpdesk-ai.md
AI application end-user authentication (delegated)	references/curated/workforce-helpdesk-ai.md

Step 2: Load curated anchors (1–3 max)

Load the anchors identified in Step 1. Stop if the curated anchor is sufficient. Do not load all four anchors unless the user's task explicitly spans all sub-areas.

MCP execution

See references/runtime/mcp-preflight.md for MCP config and Cursor preflight steps.

Retrieval escalation

1. Curated anchors (references/curated/) — load 1–3 max. Stop if sufficient.

Output discipline

Curated anchors provide accuracy context — they are not a substitute for the required output. If the task asks for code, a configuration file, or a design document, always produce that artifact. Do not return a prose summary that points at the anchor and stops.