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Escalation Design

skill-owl-listener-ai-design-skills-escalation-design · by Owl-Listener

When and how AI should escalate to humans, refuse, or ask for clarification.

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Install

$ agentstack add skill-owl-listener-ai-design-skills-escalation-design

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Escalation Design

Escalation is what happens when the AI reaches the boundary of what it should handle alone. Designing escalation well means the user gets help instead of a dead end — and the AI knows its limits.

Escalation Triggers

The AI should escalate when:

  • Confidence is low: The AI isn't sure its output is correct or helpful
  • Stakes are high: The decision has significant consequences (financial, medical, legal, safety)
  • Emotional distress: The user shows signs of crisis, distress, or vulnerability
  • Ambiguity is unresolvable: The AI can't determine intent even after clarification
  • Scope boundary: The request is outside what the AI is designed to handle
  • Policy boundary: The request approaches or crosses a guardrail
  • Conflict: The user disagrees with the AI and the disagreement can't be resolved

Escalation Types

  • To human support: Transfer to a human agent with full context
  • To the user themselves: "This decision is yours to make" — handing back agency
  • To a specialist: Routing to domain-specific help (medical, legal, technical)
  • To a supervisor/admin: Flagging for organisational review
  • Self-escalation: The AI flags its own output for review before delivering it

Designing the Escalation Experience

The user's experience of escalation matters:

  • Context transfer: When escalating to a human, pass the full conversation. Don't make the user repeat themselves.
  • Warm handoff: "I'm connecting you with someone who can help with this" — not a cold redirect.
  • Expectation setting: Tell the user what will happen next and how long it might take.
  • Graceful degradation: If no human is available, offer alternatives — not a dead end.
  • Dignity: Never make the user feel stupid for needing escalation.

Escalation Anti-Patterns

  • The infinite loop: AI keeps trying instead of escalating, frustrating the user
  • Premature escalation: AI escalates when it could easily handle the request, annoying the user
  • Context loss: User has to start over after escalation
  • Blame shifting: AI implies the user caused the problem
  • Hidden escalation: Escalation happens without the user knowing

Design Artefacts

  • Escalation trigger matrix: Trigger | Threshold | Escalation Type | User Experience
  • Escalation flow diagrams per feature
  • Context handoff specifications
  • Fallback path designs for when escalation isn't available
  • Escalation quality metrics

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.