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sar/.claude/skills/bmad-story-automator/data/retry-fallback-strategy.md
julian 17c08e6392 chore: initial monorepo scaffold + WDS Phase 1+2 artifacts
- Nx 22.7 monorepo (pnpm 11.1, TypeScript 5.9, Node 24)
- apps/api: NestJS 11 (CJS conforme CODING-RULES.md PGD-DB-004)
- apps/web: React 19 + Vite 8 (ESM)
- libs/shared/api-interface: Zod contract base
- Docker Compose dev: Postgres 18, Valkey 8, MinIO, Mailpit
- WDS artifacts:
  - design-artifacts/A-Product-Brief/ (5 docs canônicos + 16 dialogs)
  - design-artifacts/B-Trigger-Map/ (hub + 4 personas + feature impact)
- Stack canon: STACK.md v2.2 + CODING-RULES.md v2.0 + brand.md
- AGENTS.md + README.md como entrada para devs/agentes

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-27 14:34:20 +00:00

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3.7 KiB
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# Retry & Fallback Strategy
**Purpose:** Universal retry and fallback agent pattern for all workflow steps (create, dev, auto, review).
**Version:** 2.0.0
---
## Core Principle
**NEVER escalate to user on first failure.** Exhaust all retry options first:
1. Try fallback agent (if configured for this task)
2. Retry with alternating agents up to 5 total attempts
3. Sleep between retries if network issues detected
4. Only escalate after all attempts exhausted
---
## Agent Configuration (v3.0.0)
**Deterministic agent resolution via agents file:**
```bash
# Resolve agent for a specific task (create, dev, auto, review)
# Uses agents file generated during preflight (complexity-aware)
resolve_agent_for_task() {
local task="$1"
local state_file="$2"
local story_id="$3"
result=$("$scripts" orchestrator-helper agents-resolve \
--state-file "$state_file" \
--story "$story_id" \
--task "$task")
primary_agent=$(echo "$result" | jq -r '.primary')
fallback_agent=$(echo "$result" | jq -r '.fallback')
# Handle "false"/null meaning disabled
[ "$fallback_agent" = "false" ] && fallback_agent=""
}
# Usage:
resolve_agent_for_task "review" "$state_file" "{story_id}"
echo "Review task: primary=$primary_agent, fallback=$fallback_agent"
```
**Fallback behavior:**
- If `fallback_agent` is empty, "false", or same as primary → retry with primary only
- If `fallback_agent` differs → alternate between agents on retries
- Complexity overrides win per task, then per-task overrides, then defaults
---
## Retry Sequence (5 Attempts Max)
| Attempt | Agent | Delay Before | Notes |
|---------|-------|--------------|-------|
| 1 | primary | none | Initial attempt |
| 2 | fallback | 0-60s | Switch agent; delay if network error |
| 3 | primary | 0-60s | Back to primary |
| 4 | fallback | 60s | Always delay by attempt 4 |
| 5 | primary | 60s | Final attempt |
**If no fallback configured:** All 5 attempts use primary agent.
---
## Network Error Detection
**Indicators of network/transient issues:**
- Session output contains: "connection refused", "timeout", "rate limit", "503", "502"
- Session crashed with zero output
- `story-automator monitor-session` returns `final_state: "crashed"` with empty output
- Session stuck at "never_active" state (no response from API)
**On network error detection:**
- Sleep 60 seconds before next attempt
- Log: "Network issue detected, waiting 60s before retry..."
---
## Implementation & Validation Examples
Detailed bash patterns and step-specific validation examples are moved to:
- **`retry-fallback-implementation.md`** (implementation wrapper + per-step validation)
---
## Escalation (After All Attempts)
Only after exhausting all 5 attempts:
1. Update state: `status = "AWAITING_DECISION"`
2. Log all attempt details:
```
[timestamp] ESCALATION: {step} failed after 5 attempts
- Attempt 1 (primary): {result}
- Attempt 2 (fallback): {result}
- Attempt 3 (primary): {result}
- Attempt 4 (fallback): {result}
- Attempt 5 (primary): {result}
```
3. Present options to user:
- Retry with different settings
- Skip this story
- Abort orchestration
---
## Integration with Adaptive Retry
This strategy **replaces** the simple retry logic. The adaptive-retry.md plateau detection still applies within this framework:
- If same task plateau detected across 3+ attempts → DEFER instead of escalate
- Plateau detection runs AFTER agent switching (so both agents hit same wall)
---
## Logging
All retry attempts should be logged in the action log:
```
[timestamp] {step} attempt {N}/{max} with {agent}: {result}
```
On success after retry:
```
[timestamp] {step} succeeded on attempt {N} with {agent} (after {N-1} failures)
```