Agent skill · software engineering · davila7
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, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
Why this skill is useful
Adds a comprehensive multi-agent orchestration framework with executable workflows and specialized task management scripts that enhance AI capabilities in autonomous product development.
What it needs
Requires aws, deepmind, openai installed locally. Requires aws, deepmind, openai account access. About 11k tokens when loaded. Last updated 2026-08-06. 30,138 stars on the source repository.
What this skill does
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? SDLC Phase Flow 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 …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills davila7/loki-mode