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* feat: implement three-tier model strategy with Opus 4.5 This implements a strategic model selection approach based on agent complexity and use case, addressing Issue #136. Three-Tier Strategy: - Tier 1 (opus): 17 critical agents for architecture, security, code review - Tier 2 (inherit): 21 complex agents where users choose their model - Tier 3 (sonnet): 63 routine development agents (unchanged) - Tier 4 (haiku): 47 fast operational agents (unchanged) Why Opus 4.5 for Tier 1: - 80.9% on SWE-bench (industry-leading for code) - 65% fewer tokens for long-horizon tasks - Superior reasoning for architectural decisions Changes: - Update architect-review, cloud-architect, kubernetes-architect, database-architect, security-auditor, code-reviewer to opus - Update backend-architect, performance-engineer, ai-engineer, prompt-engineer, ml-engineer, mlops-engineer, data-scientist, blockchain-developer, quant-analyst, risk-manager, sql-pro, database-optimizer to inherit - Update README with three-tier model documentation Relates to #136 * feat: comprehensive model tier redistribution for Opus 4.5 This commit implements a strategic rebalancing of agent model assignments, significantly increasing the use of Opus 4.5 for critical coding tasks while ensuring Sonnet is used more than Haiku for support tasks. Final Distribution (153 total agent files): - Tier 1 Opus: 42 agents (27.5%) - All production coding + critical architecture - Tier 2 Inherit: 42 agents (27.5%) - Complex tasks, user-choosable - Tier 3 Sonnet: 38 agents (24.8%) - Support tasks needing intelligence - Tier 4 Haiku: 31 agents (20.3%) - Simple operational tasks Key Changes: Tier 1 (Opus) - Production Coding + Critical Review: - ALL code-reviewers (6 total): Ensures highest quality code review across all contexts (comprehensive, git PR, code docs, codebase cleanup, refactoring, TDD) - All major language pros (7): python, golang, rust, typescript, cpp, java, c - Framework specialists (6): django (2), fastapi (2), graphql-architect (2) - Complex specialists (6): terraform-specialist (3), tdd-orchestrator (2), data-engineer - Blockchain: blockchain-developer (smart contracts are critical) - Game dev (2): unity-developer, minecraft-bukkit-pro - Architecture (existing): architect-review, cloud-architect, kubernetes-architect, hybrid-cloud-architect, database-architect, security-auditor Tier 2 (Inherit) - User Flexibility: - Secondary languages (6): javascript, scala, csharp, ruby, php, elixir - All frontend/mobile (8): frontend-developer (4), mobile-developer (2), flutter-expert, ios-developer - Specialized (6): observability-engineer (2), temporal-python-pro, arm-cortex-expert, context-manager (2), database-optimizer (2) - AI/ML, backend-architect, performance-engineer, quant/risk (existing) Tier 3 (Sonnet) - Intelligent Support: - Documentation (4): docs-architect (2), tutorial-engineer (2) - Testing (2): test-automator (2) - Developer experience (3): dx-optimizer (2), business-analyst - Modernization (4): legacy-modernizer (3), database-admin - Other support agents (existing) Tier 4 (Haiku) - Simple Operations: - SEO/Marketing (10): All SEO agents, content, search - Deployment (4): deployment-engineer (4 instances) - Debugging (5): debugger (2), error-detective (3) - DevOps (3): devops-troubleshooter (3) - Other simple operational tasks Rationale: - Opus 4.5 achieves 80.9% on SWE-bench with 65% fewer tokens on complex tasks - Production code deserves the best model: all language pros now on Opus - All code review uses Opus for maximum quality and security - Sonnet > Haiku (38 vs 31) ensures better intelligence for support tasks - Inherit tier gives users cost control for frontend, mobile, and specialized tasks Related: #136, #132 * feat: upgrade final 13 agents from Haiku to Sonnet Based on research into Haiku 4.5 vs Sonnet 4.5 capabilities, upgraded agents requiring deep analytical intelligence from Haiku to Sonnet. Research Findings: - Haiku 4.5: 73.3% SWE-bench, 3-5x faster, 1/3 cost, sub-200ms responses - Best for Haiku: Real-time apps, data extraction, templates, high-volume ops - Best for Sonnet: Complex reasoning, root cause analysis, strategic planning Agents Upgraded (13 total): - Debugging (5): debugger (2), error-detective (3) - Complex root cause analysis - DevOps (3): devops-troubleshooter (3) - System diagnostics & troubleshooting - Network (2): network-engineer (2) - Complex network analysis & optimization - API Documentation (2): api-documenter (2) - Deep API understanding required - Payments (1): payment-integration - Critical financial integration Final Distribution (153 total): - Tier 1 Opus: 42 agents (27.5%) - Production coding + critical architecture - Tier 2 Inherit: 42 agents (27.5%) - Complex tasks, user-choosable - Tier 3 Sonnet: 51 agents (33.3%) - Support tasks needing intelligence - Tier 4 Haiku: 18 agents (11.8%) - Fast operational tasks only Haiku Now Reserved For: - SEO/Marketing (8): Pattern matching, data extraction, content templates - Deployment (4): Operational execution tasks - Simple Docs (3): reference-builder, mermaid-expert, c4-code - Sales/Support (2): High-volume, template-based interactions - Search (1): Knowledge retrieval Sonnet > Haiku as requested (51 vs 18) Sources: - https://www.creolestudios.com/claude-haiku-4-5-vs-sonnet-4-5-comparison/ - https://www.anthropic.com/news/claude-haiku-4-5 - https://caylent.com/blog/claude-haiku-4-5-deep-dive-cost-capabilities-and-the-multi-agent-opportunity Related: #136 * docs: add cost considerations and clarify inherit behavior Addresses PR feedback: - Added comprehensive cost comparison for all model tiers - Documented how 'inherit' model works (uses session default, falls back to Sonnet) - Explained cost optimization strategies - Clarified when Opus token efficiency offsets higher rate This helps users make informed decisions about model selection and cost control.
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name, description, model
| name | description | model |
|---|---|---|
| elixir-pro | Write idiomatic Elixir code with OTP patterns, supervision trees, and Phoenix LiveView. Masters concurrency, fault tolerance, and distributed systems. Use PROACTIVELY for Elixir refactoring, OTP design, or complex BEAM optimizations. | inherit |
You are an Elixir expert specializing in concurrent, fault-tolerant, and distributed systems.
Focus Areas
- OTP patterns (GenServer, Supervisor, Application)
- Phoenix framework and LiveView real-time features
- Ecto for database interactions and changesets
- Pattern matching and guard clauses
- Concurrent programming with processes and Tasks
- Distributed systems with nodes and clustering
- Performance optimization on the BEAM VM
Approach
- Embrace "let it crash" philosophy with proper supervision
- Use pattern matching over conditional logic
- Design with processes for isolation and concurrency
- Leverage immutability for predictable state
- Test with ExUnit, focusing on property-based testing
- Profile with :observer and :recon for bottlenecks
Output
- Idiomatic Elixir following community style guide
- OTP applications with proper supervision trees
- Phoenix apps with contexts and clean boundaries
- ExUnit tests with doctests and async where possible
- Dialyzer specs for type safety
- Performance benchmarks with Benchee
- Telemetry instrumentation for observability
Follow Elixir conventions. Design for fault tolerance and horizontal scaling.