antigravity-skills-reference/skills/loki-mode/CLAUDE.md

Loki Mode - Claude Code Skill

Multi-agent autonomous startup system for Claude Code. Takes PRD to fully deployed, revenue-generating product with zero human intervention.

Quick Start

# Launch Claude Code with autonomous permissions
claude --dangerously-skip-permissions

# Then invoke:
# "Loki Mode" or "Loki Mode with PRD at path/to/prd"

Project Structure

SKILL.md                    # Main skill definition (read this first)
references/                 # Detailed documentation (loaded progressively)
  openai-patterns.md        # OpenAI Agents SDK: guardrails, tripwires, handoffs
  lab-research-patterns.md  # DeepMind + Anthropic: Constitutional AI, debate
  production-patterns.md    # HN 2025: What actually works in production
  advanced-patterns.md      # 2025 research patterns (MAR, Iter-VF, GoalAct)
  tool-orchestration.md     # ToolOrchestra-inspired efficiency & rewards
  memory-system.md          # Episodic/semantic memory architecture
  quality-control.md        # Code review, anti-sycophancy, guardrails
  agent-types.md            # 37 specialized agent definitions
  sdlc-phases.md            # Full SDLC workflow
  task-queue.md             # Queue system, circuit breakers
  spec-driven-dev.md        # OpenAPI-first development
  architecture.md           # Directory structure, state schemas
  core-workflow.md          # RARV cycle, autonomy rules
  claude-best-practices.md  # Boris Cherny patterns
  deployment.md             # Cloud deployment instructions
  business-ops.md           # Business operation workflows
  mcp-integration.md        # MCP server capabilities
autonomy/                   # Runtime state and constitution
benchmarks/                 # SWE-bench and HumanEval benchmarks

Key Concepts

RARV Cycle

Every iteration follows: Reason -> Act -> Reflect -> Verify

Model Selection

• Opus: Planning and architecture ONLY (system design, high-level decisions)
• Sonnet: Development and functional testing (implementation, integration tests)
• Haiku: Unit tests, monitoring, and simple tasks - use extensively for parallelization

Quality Gates

1. Static analysis (CodeQL, ESLint)
2. 3-reviewer parallel system (blind review)
3. Anti-sycophancy checks (devil's advocate on unanimous approval)
4. Severity-based blocking (Critical/High/Medium = BLOCK)
5. Test coverage gates (>80% unit, 100% pass)

Memory System

• Episodic: Specific interaction traces (.loki/memory/episodic/)
• Semantic: Generalized patterns (.loki/memory/semantic/)
• Procedural: Learned skills (.loki/memory/skills/)

Metrics System (ToolOrchestra-inspired)

• Efficiency: Task cost tracking (.loki/metrics/efficiency/)
• Rewards: Outcome/efficiency/preference signals (.loki/metrics/rewards/)

Development Guidelines

When Modifying SKILL.md

• Keep under 500 lines (currently ~370)
• Reference detailed docs in references/ instead of inlining
• Update version in header AND footer
• Update CHANGELOG.md with new version entry

Version Numbering

Follows semantic versioning: MAJOR.MINOR.PATCH

• Current: v2.35.0
• MINOR bump for new features
• PATCH bump for fixes

Code Style

• No emojis in code or documentation
• Clear, concise comments only when necessary
• Follow existing patterns in codebase

Testing

# Run benchmarks
./benchmarks/run-benchmarks.sh humaneval --execute --loki
./benchmarks/run-benchmarks.sh swebench --execute --loki

Research Foundation

Built on 2025 research from three major AI labs:

OpenAI:

• Agents SDK (guardrails, tripwires, handoffs, tracing)
• AGENTS.md / Agentic AI Foundation (AAIF) standards

Google DeepMind:

• SIMA 2 (self-improvement, hierarchical reasoning)
• Gemini Robotics (VLA models, planning)
• Dreamer 4 (world model training)
• Scalable Oversight via Debate

Anthropic:

• Constitutional AI (principles-based self-critique)
• Alignment Faking Detection (sleeper agent probes)
• Claude Code Best Practices (Explore-Plan-Code)

Academic:

• CONSENSAGENT (anti-sycophancy)
• GoalAct (hierarchical planning)
• A-Mem/MIRIX (memory systems)
• Multi-Agent Reflexion (MAR)
• NVIDIA ToolOrchestra (efficiency metrics)

See references/openai-patterns.md, references/lab-research-patterns.md, and references/advanced-patterns.md.