Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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5-level error recovery escalation: retry, nudge, replan, fallback, force-done — each with entry criteria and timeout before escalating
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Provide a structured, 5-level escalation ladder for recovering from agent errors. Each level has specific entry criteria, an action, and a timeout before escalating to the next level.
Level 1: RETRY — Same action, transient error
Level 2: NUDGE — Adjust parameters, same approach
Level 3: REPLAN — New approach, same goal
Level 4: FALLBACK — Different agent or model
Level 5: FORCE-DONE — Partial results with explanation
Skill({ skill: 'error-recovery-escalation' });
Invoke when:
behavioral-loop-detection)Entry criteria:
Action:
Timeout: 3 attempts × backoff = max ~30 seconds total Escalate to Level 2 when: 3 retries exhausted without success
Example:
Read('.claude/context/data/index.db') → ENOENT
→ Level 1: Retry 3 times with 1s backoff
→ Still fails → escalate to Level 2
Entry criteria:
Action:
Timeout: 5 minutes total for all nudge variants Escalate to Level 3 when: All nudge variants fail or timeout expires
Example:
Write('output/result.json', ...) → EPERM
→ Level 2: Try .claude/context/tmp/result.json, then /tmp/result.json
→ All fail → escalate to Level 3
Entry criteria:
Action:
planner agent or invoke plan-generator skill for a new planTimeout: 15 minutes for new plan + initial execution Escalate to Level 4 when: Replan also fails, or planner cannot produce a viable plan
Example:
Auth middleware implementation fails repeatedly
→ Level 3: Replan with different auth library (passport → jose)
→ New plan also fails due to dependency conflict → escalate to Level 4
Entry criteria:
Action:
developer → devops-troubleshooter)Timeout: 20 minutes for fallback agent execution Escalate to Level 5 when: Fallback agent also fails or timeout expires
Example:
Developer agent cannot resolve platform-specific build error
→ Level 4: Spawn devops-troubleshooter with full error log
→ Still unresolved after 20min → escalate to Level 5
Entry criteria:
Action:
{ partial: true, escalationLevel: 5, explanation: '...' }Output contract:
{
"status": "partial",
"completedSteps": ["step1", "step2"],
"failedAt": "step3",
"failureReason": "<specific error>",
"escalationPath": [1, 2, 3, 4, 5],
"recommendation": "<what a human should do to finish>"
}
Example:
External API service is down
→ Level 5: Emit partial results (all non-API steps completed)
→ TaskUpdate with partial: true, explanation of API outage
→ Recommend retry when service is restored
| Error Type | Entry Level | Rationale |
|---|---|---|
| Network timeout | 1 (retry) | Transient, safe to retry |
| Rate limit | 1 (retry with backoff) | Transient, wait and retry |
| File not found | 2 (nudge) | Wrong path, try alternatives |
| Permission denied | 2 (nudge) | Wrong path/permissions |
| Wrong output format | 2 (nudge) | Adjust input parameters |
| Goal misalignment (judge FAIL) | 3 (replan) | Need different approach |
| Agent capability mismatch | 4 (fallback) | Need different agent |
| External service down | 5 (force-done) | Cannot resolve programmatically |
| Missing credentials | 5 (force-done) | Requires human intervention |
Every level transition MUST be recorded:
// On entering a level
TaskUpdate({
taskId: '<task-id>',
status: 'in_progress',
metadata: {
recoveryLevel: <1-5>,
recoveryAction: 'retry|nudge|replan|fallback|force-done',
errorType: '<classification>',
previousLevels: [<completed levels>],
enteredAt: new Date().toISOString(),
}
});
// On Level 5 completion
TaskUpdate({
taskId: '<task-id>',
status: 'completed',
metadata: {
partial: true,
escalationLevel: 5,
escalationPath: [1, 2, 3, 4, 5],
completedSteps: ['<step1>', '<step2>'],
failedAt: '<step>',
failureReason: '<specific error>',
recommendation: '<human follow-up action>',
summary: 'Force-done: partial results emitted after 5-level escalation',
}
});
| Skill | Relationship |
|---|---|
behavioral-loop-detection | Feeds escalation triggers (REPLAN at 3, EXPLORE at 5, FORCE-DONE at 8) |
judge-verification | FAIL verdict triggers escalation at appropriate level |
plan-generator | Called at Level 3 (replan) to produce new approach |
verification-before-completion | Gates completion before escalation is declared unnecessary |
debugging | Provides root cause analysis before Level 3 escalation |
Input validated against schemas/input.schema.json before execution.
Output contract defined in schemas/output.schema.json.
Pre-execution hook: hooks/pre-execute.cjs
Post-execution hook: hooks/post-execute.cjs (emits observability event)
Before starting:
Read .claude/context/memory/learnings.md for known error patterns in this codebase.
Check .claude/context/memory/issues.md for known blockers.
After completing:
.claude/context/memory/issues.md with root cause.claude/context/memory/learnings.mdASSUME INTERRUPTION: If it's not in memory, it didn't happen.
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Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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