By afrIOkaner
v9.37.1 — Agent summaries, prompt-size preflight, research fanout, and Codex-compatible portable skills. Run /octo:setup.
Design UI/UX systems with style guides, palettes, typography, and component specs
AI Debate Hub - Structured four-way debates between Claude, Sonnet, Gemini, and Codex
Deep research with multi-source synthesis and comprehensive analysis
[advanced] Resume a previous agent by ID — continue an interrupted task where it left off
[advanced] Activate destructive command warnings for the session
Backend architect for scalable API design, microservices, and distributed systems
Cloud architect for AWS/Azure/GCP infrastructure, IaC, FinOps, and multi-cloud strategies
Code review expert for quality analysis, security vulnerabilities, and production reliability
Database architect for data modeling, technology selection, schema design, and migration planning
Debugging specialist for errors, test failures, and unexpected behavior
Multi-AI requirements scoping using Codex and Gemini CLIs (Double Diamond Define phase)
Multi-AI validation, scoring, and review using Codex and Gemini CLIs (Double Diamond Deliver phase)
Multi-AI implementation using Codex and Gemini CLIs (Double Diamond Develop phase)
Multi-AI research using Codex and Gemini CLIs (Double Diamond Discover phase)
Decompose and execute large changes, migrations, or multi-issue fixes in parallel with quality gates
Uses power tools
Uses Bash, Write, or Edit tools
Runs pre-commands
Contains inline bash commands via ! syntax
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Every AI model has blind spots. Claude Octopus puts up to eight of them on every task, so blind spots surface before you ship — not after. It orchestrates Codex, Gemini, Copilot, Qwen, Ollama, Perplexity, and OpenRouter alongside Claude Code, with consensus gates that flag any disagreements.
Claude-native first, Octopus for escalation. Use Claude-native /init, /review, and /security-review when Claude is enough. Use Octopus when you want multiple model opinions, adversarial review, or stricter multi-LLM workflows.
🐙 Research, build, review, and ship — with eight AI providers checking each other's work. Say what you need, and the right workflow runs. Claude-native handles the ordinary path; Octopus handles the escalated path. A 75% consensus gate catches disagreements before they reach production. No single model's blind spots slip through.
🧠 Remembers across sessions. Integrates with claude-mem for persistent memory — past decisions, research, and context survive session boundaries.
⚡ Spec in, software out. Dark Factory mode takes a spec and autonomously runs the full pipeline — research, define, develop, deliver. You review the output, not every step.
🔄 Four-phase methodology, not just tools. Every task moves through Discover → Define → Develop → Deliver, with quality gates between phases. Other orchestrators give you infrastructure. Octopus gives you the workflows.
🐙 32 specialized personas (role-specific AI agents like security-auditor, backend-architect), 48 commands (slash commands you type), 52 skills (reusable workflow modules). Say "audit my API" and the right expert activates. Don't know the command? The smart router figures it out.
🐙 Works with just Claude. Scales to eight. Zero providers needed to start. Add them one at a time — each activates automatically when detected.
💰 Five providers cost nothing extra. Codex and Gemini use OAuth (included with subscriptions). Qwen has 1,000-2,000 free requests/day. Copilot uses your GitHub subscription. Ollama runs locally for free.
| Version | Best Features |
|---|---|
| v9 (current) | Up to 8 providers (Codex, Gemini, Copilot, Qwen, Ollama, Perplexity, OpenRouter, OpenCode). Four-way AI debates. Smart router — just say what you need. Agent summary tables show which providers actually contributed. Provider-aware prompt preflight prevents silent oversize failures. Research breadth modes fan out light, standard, or exhaustive investigations. Setup aliases and fuzzy /octo:* corrections reduce command friction. Discipline mode with 8 auto-invoke gates. Two-stage review. Circuit breakers with automatic provider recovery. Cursor + OpenCode + Codex cross-compatibility. Token compression: bin/octo-compress pipe + auto PostToolUse hook save ~7,300 tokens/session. PostCompact context recovery. bin/octopus CLI. 170+ CC feature flags through v2.1.132. |
| v8 | Multi-LLM code review with inline PR comments. Parallel workstreams in isolated git worktrees. Reaction engine — auto-responds to CI failures. 32 specialized personas. Dark Factory autonomous pipeline. |
| v7 | Double Diamond workflow. Multi-provider dispatch. Quality gates and consensus scoring. Configurable sandbox modes. |
npx claudepluginhub afriokaner/claude-octopusComplete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
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.
Harness-native ECC operator layer - 60 agents, 232 skills, 75 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Persistent file-based planning for AI coding agents. Crash-proof markdown plans (task_plan.md, findings.md, progress.md) that survive context loss and /clear, with an opt-in completion gate and multi-agent shared state. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard. Includes Arabic, German, Spanish, and Chinese (Simplified and Traditional).
Supergraph enforces a complete, evidence-based coding pipeline — scan → plan → TDD → fix → verify → review — grounded in real codebase analysis at every step. It combines AST dependency graphs, LSP-level code intelligence, and a structured skill chain so Claude never guesses about impact before making a change.
AI-powered development tools for code review, research, design, and workflow automation.
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.