mirror of
https://github.com/proffesor-for-testing/agentic-qe.git
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b6fe4abec8
- Fix MCP entry path resolution in mcp.ts (1 level up, not 2) - Remove stale v3/ directory references in 10-workers.ts - Fix CRLF line endings in 170+ skill files breaking frontmatter parsing - Add CRLF→LF safety net in prepare-assets.sh - Rewrite README.md for clarity (1097→280 lines, outcome-focused) - Sync assets from .claude/skills via prepare-assets.sh Fixes issues reported in v3.7.9 upgrade (skill-lint failures, MCP errors) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
114 lines
4.3 KiB
JSON
114 lines
4.3 KiB
JSON
{
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"namespace": "adr-051/router-patterns",
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"description": "Model Router Integration Patterns from ADR-051",
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"created": "2026-01-20",
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"patterns": [
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{
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"key": "router-5tier-complexity",
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"pattern": "5-Tier Model Complexity Scoring System",
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"description": "Hierarchical model routing based on task complexity and constraints",
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"tier_hierarchy": {
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"tier_1_booster": {
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"cost": "$0",
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"latency": "<1ms",
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"use_case": "Simple transforms (var-const, add-types, remove-console)",
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"eligibility": "Pure functions, no dependencies"
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},
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"tier_2_haiku": {
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"cost": "$0.80/M input tokens",
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"latency": "~500ms",
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"use_case": "Bug fixes, simple tasks, low complexity",
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"complexity_score": "1-3"
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},
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"tier_3_sonnet": {
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"cost": "$3/M input tokens",
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"latency": "~2-3s",
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"use_case": "Medium complexity, architectural decisions",
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"complexity_score": "4-6"
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},
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"tier_4_opus": {
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"cost": "$15/M input tokens",
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"latency": "~5-8s",
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"use_case": "Complex reasoning, security-critical",
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"complexity_score": "7-9"
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},
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"tier_5_human": {
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"cost": "Manual review",
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"latency": "Variable",
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"use_case": "Final decisions, critical paths",
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"complexity_score": "10"
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}
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},
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"scoring_factors": [
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"Number of files affected",
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"Code complexity (AST depth)",
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"Domain sensitivity",
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"Business impact",
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"Security implications",
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"Architectural change magnitude"
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],
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"auto_downgrade": "Reduce tier if budget exceeded or timeout risk",
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"successRate": 0.91,
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"lastUpdated": "2026-01-20"
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},
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{
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"key": "router-budget-enforcement",
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"pattern": "Budget Enforcement with Auto-Downgrade",
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"description": "Enforce token and cost budgets with intelligent model tier downgrade",
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"budget_constraints": {
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"max_tokens_per_task": "100000",
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"max_cost_per_task": "$0.50",
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"max_latency_ms": "30000"
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},
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"auto_downgrade_logic": {
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"step_1": "Estimate tokens needed for task with target model",
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"step_2": "Compare against available budget",
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"step_3": "If exceeded: downgrade to cheaper model",
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"step_4": "Recalculate and repeat until fits budget",
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"step_5": "Escalate to human if no model viable"
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},
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"budget_tracking": {
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"per_task": "Track cumulative tokens/cost",
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"per_session": "Aggregate across all tasks",
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"per_day": "Daily quota enforcement",
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"alerts": "Warn at 80% threshold"
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},
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"recovery_strategies": [
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"Task decomposition into smaller chunks",
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"Caching partial results to reduce retokenization",
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"Context pruning for efficiency",
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"Result streaming to avoid buffering"
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],
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"successRate": 0.88,
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"lastUpdated": "2026-01-20"
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},
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{
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"key": "router-booster-integration",
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"pattern": "Model Router to Agent Booster Integration",
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"description": "Seamless integration between router and booster for optimal task routing",
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"integration_flow": {
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"step_1_receive_task": "Router receives task description",
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"step_2_classify": "Classify as simple transform or complex task",
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"step_3_check_booster": "Check Agent Booster eligibility criteria",
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"step_4_route": "If eligible: route to booster; else: route to model tier",
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"step_5_execute": "Execute via appropriate pathway",
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"step_6_report": "Report cost, latency, quality metrics"
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},
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"eligibility_handshake": {
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"booster_can_handle": "Query booster eligibility function",
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"transform_type": "Categorize specific transform",
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"fallback_model": "Designate fallback if booster fails"
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},
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"metrics_collection": {
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"booster_execution": "Track WASM vs TS fallback ratio",
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"model_tier_usage": "Distribution across Haiku/Sonnet/Opus",
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"cost_savings": "Actual vs baseline cost",
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"quality_correlation": "Task complexity vs outcome quality"
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},
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"feedback_loop": "Use execution patterns to refine routing heuristics",
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"successRate": 0.89,
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"lastUpdated": "2026-01-20"
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}
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]
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}
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