By Sudeeparyan
Autonomous /loop-driven task completion with learning, prediction, and progress tracking — wraps 10 autopilot_* MCP tools (status/enable/disable/config/reset/log/progress/learn/history/predict)
Uses power tools
Uses Bash, Write, or Edit tools
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AI safety scanning, PII detection, prompt injection defense, and adaptive threat learning
Security review, dependency scanning, policy gates, and CVE monitoring
Token usage tracking, model cost attribution per agent, budget alerts, and optimization recommendations — uses memory_* (namespace-routed) for cost-tracking and cost-patterns; pairs with federation budget circuit breaker (ADR-097)
RuVector memory with HNSW search, AgentDB, and semantic retrieval
Session-as-skill browser automation: Playwright + RVF cognitive containers + ruvector trajectories + AgentDB selector memory + AIDefence PII/injection gates
npx claudepluginhub p/sudeeparyan-ruflo-autopilot-plugins-ruflo-autopilotHarness-native ECC operator layer - 67 agents, 277 skills, 93 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
v9.52.0 - Reliability wave: tangle contextual review correction loop with hard round ceiling, progress-supervised review rounds (per-agent stall watch, descendant-tree kills), council diversity and agy pin fixes, marketplace generator source-of-truth fix, provider troubleshooting runbook and cost-expectations docs. Run /octo:setup.
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
The Claude Code knowledge system — 380+ skills, 182+ agents, 100+ commands, 40 hooks, 32 rules, and workflows.
Comprehensive C4 architecture documentation workflow with bottom-up code analysis, component synthesis, container mapping, and context diagram generation
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review