AI-era identity patterns: Identity for AI, Verified Trust, agent identity, agent security, and AI application authentication.
What this skill does for you: Guides you through architecture, patterns, and design decisions for securing AI agents with Ping. It is currently conceptual rather than executable — there are no dedicated ID4AI MCP tools, so it does not generate ID4AI-specific configuration. For the parts that map to existing platform capabilities (e.g. agent client credentials, PingGateway routes), it hands off to ping-foundation and ping-app-integration, which generate config and code.
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:
ping-foundation— register the AI agent application and configure the environment.ping-identity-for-ai— design the token scoping and delegation model (this skill).ping-orchestration— build the step-up MFA flow using DaVinci or Journey.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
- 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.