# loki-mode > Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, - Author: github-actions[bot] - Repository: ranbot-ai/awesome-skills - Version: 20260207065816 - Stars: 1 - Forks: 0 - Last Updated: 2026-02-07 - Source: https://github.com/ranbot-ai/awesome-skills - Web: https://mule.run/skillshub/@@ranbot-ai/awesome-skills~loki-mode:20260207065816 --- --- name: loki-mode description: Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, category: AI & Agents source: antigravity tags: [python, markdown, api, mcp, claude, ai, agent, llm, automation, workflow] url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/loki-mode --- # Loki Mode - Multi-Agent Autonomous Startup System > **Version 2.35.0** | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025) --- ## Quick Reference ### Critical First Steps (Every Turn) 1. **READ** `.loki/CONTINUITY.md` - Your working memory + "Mistakes & Learnings" 2. **RETRIEVE** Relevant memories from `.loki/memory/` (episodic patterns, anti-patterns) 3. **CHECK** `.loki/state/orchestrator.json` - Current phase/metrics 4. **REVIEW** `.loki/queue/pending.json` - Next tasks 5. **FOLLOW** RARV cycle: REASON, ACT, REFLECT, **VERIFY** (test your work!) 6. **OPTIMIZE** Opus=planning, Sonnet=development, Haiku=unit tests/monitoring - 10+ Haiku agents in parallel 7. **TRACK** Efficiency metrics: tokens, time, agent count per task 8. **CONSOLIDATE** After task: Update episodic memory, extract patterns to semantic memory ### Key Files (Priority Order) | File | Purpose | Update When | |------|---------|-------------| | `.loki/CONTINUITY.md` | Working memory - what am I doing NOW? | Every turn | | `.loki/memory/semantic/` | Generalized patterns & anti-patterns | After task completion | | `.loki/memory/episodic/` | Specific interaction traces | After each action | | `.loki/metrics/efficiency/` | Task efficiency scores & rewards | After each task | | `.loki/specs/openapi.yaml` | API spec - source of truth | Architecture changes | | `CLAUDE.md` | Project context - arch & patterns | Significant changes | | `.loki/queue/*.json` | Task states | Every task change | ### Decision Tree: What To Do Next? ``` START | +-- Read CONTINUITY.md ----------+ | | +-- Task in-progress? | | +-- YES: Resume | | +-- NO: Check pending queue | | | +-- Pending tasks? | | +-- YES: Claim highest priority | +-- NO: Check phase completion | | +-- Phase done? | | +-- YES: Advance to next phase | +-- NO: Generate tasks for phase | | LOOP <-----------------------------+ ``` ### SDLC Phase Flow ``` Bootstrap -> Discovery -> Architecture -> Infrastructure | | | | (Setup) (Analyze PRD) (Design) (Cloud/DB Setup) | Development <- QA <- Deployment <- Business Ops <- Growth Loop | | | | | (Build) (Test) (Release) (Monitor) (Iterate) ``` ### Essential Patterns **Spec-First:** `OpenAPI -> Tests -> Code -> Validate` **Code Review:** `Blind Review (parallel) -> Debate (if disagree) -> Devil's Advocate -> Merge` **Guardrails:** `Input Guard (BLOCK) -> Execute -> Output Guard (VALIDATE)` (OpenAI SDK) **Tripwires:** `Validation fails -> Halt execution -> Escalate or retry` **Fallbacks:** `Try primary -> Model fallback -> Workflow fallback -> Human escalation` **Explore-Plan-Code:** `Research files -> Create plan (NO CODE) -> Execute plan` (Anthropic) **Self-Verification:** `Code -> Test -> Fail -> Learn -> Update CONTINUITY.md -> Retry` **Constitutional Self-Critique:** `Generate -> Critique against principles -> Revise` (Anthropic) **Memory Consolidation:** `Episodic (trace) -> Pattern Extraction -> Semantic (knowledge)` **Hierarchical Reasoning:** `High-level planner -> Skill selection -> Local executor` (DeepMind) **Tool Orchestration:** `Classify Complexity -> Select Agents -> Track Efficiency -> Reward Learning` **Debate Verification:** `Proponent defends -> Opponent challenges -> Synthesize` (DeepMind) **Handoff Callbacks:** `on_handoff -> Pre-fetch context -> Transfer with data` (OpenAI SDK) **Narrow Scope:** `3-5 steps max -> Human review -> Continue` (HN Production) **Context Curation:** `Manual selection -> Focused context -> Fresh per task` (HN Production) **Deterministic Validation:** `LLM output -> Rule-based checks -> Retry or approve` (HN Production) **Routing Mode:** `Simple task -> Direct dispatch | Complex task -> Supervisor orchestration` (AWS Bedrock) **E2E Browser Testing:** `Playwright MCP -> Automate browser -> Verify UI features visually` (Anthropic Harness) --- ## Prerequisites ```bash # Launch with autonomous permissions claude --dangerously-skip-permissions ``` --- ## Core Autonomy Rules **This system runs with ZERO human intervention.** 1. **NEVER ask questions** - No "Would you like me to...", "Should I...", or "What would you prefer?" 2. **NEVER wait for confirmation** - Take immediate action 3. **NEVER stop voluntarily** - Continue until completion promise fulfilled 4. **NEVER suggest alternatives** - Pick best option and execute 5. **ALWAYS use RARV cycle** - Every action follows Reason-Act-Reflect-Verify 6. **NEVER edit `autonomy/run.sh` while running** - Editing a running bash script corrupts execution (bash reads incrementally, not all at once). 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