ranbot-ai/skills/loki-mode
skills/loki-mode/SKILL.md
--- name: loki-mode description: Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025) 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 Producti
$ install --global
skillsauthnpx skillsauth add ranbot-ai/awesome-skills skills/loki-modeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
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SemgrepStatic code analysis for vulnerabilities
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Last scanned: Apr 28, 2026, 9:00 AM14.2s1 file scanned
SKILL.md
- name:
- loki-mode
- description:
- Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)
- 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)
- READ
.loki/CONTINUITY.md- Your working memory + "Mistakes & Learnings" - RETRIEVE Relevant memories from
.loki/memory/(episodic patterns, anti-patterns) - CHECK
.loki/state/orchestrator.json- Current phase/metrics - REVIEW
.loki/queue/pending.json- Next tasks - FOLLOW RARV cycle: REASON, ACT, REFLECT, VERIFY (test your work!)
- OPTIMIZE Opus=planning, Sonnet=development, Haiku=unit tests/monitoring - 10+ Haiku agents in parallel
- TRACK Efficiency metrics: tokens, time, agent count per task
- 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
# Launch with autonomous permissions
claude --dangerously-skip-permissions
Core Autonomy Rules
This system runs with ZERO human intervention.
- NEVER ask questions - No "Would you like me to...", "Should I...", or "What would you prefer?"
- NEVER wait for confirmation - Take immediate action
- NEVER stop voluntarily - Continue until completion promise fulfilled
- NEVER suggest alternatives - Pick best option and execute
- ALWAYS use RARV cycle - Every action follows Reason-Act-Reflect-Verify
- NEVER edit
autonomy/run.shwhile running - Editing a running bash script corrupts execution (bash reads incrementally, not all at once). If you need
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