#601

Globales Ranking · von 601 Skills

obra/superpowers@requesting-code-review AI Agent Skill

Quellcode ansehen: openakita/openakita

Installation

npx skills add openakita/openakita --skill obra/superpowers@requesting-code-review

13

Installationen

OpenAkita Logo

OpenAkita

Open-Source Multi-Agent AI Assistant — Not Just Chat, an AI Team That Gets Things Done

Official Website   Download   Discord

License Python Version Version PyPI Build Status Stars

Multi-Agent Collaboration · Organization Orchestration · Plugin System · Sandbox Security · 30+ LLMs · 6 IM Platforms · 89+ Tools · Desktop / Web / Mobile

Quick-StartOrg OrchestrationScan-to-BindPluginsSecurityDocs

English | 中文


What is OpenAkita?

Other AIs just chat. OpenAkita gets things done.

OpenAkita is an open-source, all-in-one AI assistant — multiple AI Agents work together, build an AI company that runs autonomously, search the web, operate your computer, manage files, run scheduled tasks, and respond instantly across Telegram / Feishu / WeCom / DingTalk / QQ. Scan a QR code to bind your chat app in 30 seconds. It remembers your preferences, teaches itself new skills, and never gives up on a task. Extend anything through the plugin system, protected by 6-layer sandbox security.

Fully GUI-based setup. Ready in 5 minutes. Zero command line required.

🌐 Website openakita.ai  |  📥 Download Desktop App  |  📖 Documentation  |  💬 Discord Community


Quick-Start Guide

🚀 For First-Time Users (3 Minutes)

No installation required — download the desktop app and start chatting:

  1. Download the installer from GitHub Releases
  2. Install and follow the onboarding wizard
  3. Enter your API Key (get one from Anthropic or DeepSeek)
  4. Try your first task: Type "Create a calculator" and watch it work

💻 For Developers (5 Minutes)

# Install
pip install openakita[all]

# Quick setup (interactive wizard)
openakita init

# Run your first task
openakita run "Build a weather scraper"

✨ What You Can Do Right Away

Category Examples
💬 Chat Text + images + files, voice messages, stickers
🤖 Multi-Agent "Create a competitive analysis" → research + analysis + writing agents work together
🏢 Organization Build an AI company — CEO, CTO, marketing, finance — agents run it autonomously
🌐 Web Search news, scrape websites, automate browser tasks
📁 Files Read/write/edit files, batch rename, search content
🖥️ Desktop Click buttons, type text, take screenshots, automate apps
⏰ Scheduled "Remind me every Monday at 9am" — cron-based reminders

➡️ Next Steps

  • Configure LLM: Add multiple providers for automatic failover
  • Set up IM channels: Scan QR code to bind WeChat/Feishu/WeCom in 30 seconds
  • Explore skills: Install from marketplace or create your own
  • Try org mode: Build an AI company and watch it run
  • Join community: Discord | WeChat Group

Core Capabilities

🤝 Multi-Agent Collaboration

Multiple AI agents with specialized skills work in parallel.
Say one thing — a coding Agent writes code, a writing Agent drafts docs, a testing Agent verifies — all at the same time.

🏢 Organization Orchestration

Not just multi-Agent — build an AI company. CEO, CTO, CFO, marketing director… each role operates independently. Blackboard sharing, message routing, deadlock detection.

📋 Plan Mode

Complex tasks auto-decomposed into step-by-step plans with real-time progress tracking and automatic rollback on failure.

🧠 ReAct Reasoning Engine

Think → Act → Observe. Explicit three-phase reasoning with checkpoint/rollback. Fails? Tries a different strategy.

🔌 Plugin System

8 plugin types, 3-tier permission model, 10 lifecycle hooks. Tools, channels, RAG, memory, LLM — everything is extensible.

🛡️ 6-Layer Sandbox Security

Path zoning · Confirmation gates · Command interception · File snapshots · Self-protection · OS-level sandbox. High-risk commands run in isolation automatically.

📱 IM Scan-to-Bind

WeChat, Feishu, WeCom — scan a QR code, 30 seconds to bind, use AI directly in your chat app.

💾 Dual-Mode Memory — Smarter Over Time

Fragment memory + MDRM relational graph (causal chains · timelines · entity graph · 3D visualization), auto smart switching.


Full Feature List

Feature Description
🤝 Multi-Agent Specialized agents, parallel delegation, automatic handoff, failover, real-time visual dashboard
🏢 Org Orchestration Hierarchical org structure, CEO/CTO/CFO roles, blackboard memory, message routing, deadlock detection, heartbeat, auto-scaling
📋 Plan Mode Auto task decomposition, per-step tracking, floating progress bar in UI
🧠 ReAct Reasoning Explicit 3-phase loop, checkpoint/rollback, loop detection, strategy switching
🚀 Zero-Barrier Setup Full GUI config, onboarding wizard, 5 minutes from install to chat, zero CLI
🔧 89+ Built-in Tools 16 categories: Shell / Files / Browser / Desktop / Search / Scheduler / MCP …
🔌 Plugin System 8 types (tool/channel/RAG/memory/LLM/hook/skill/MCP), 3-tier permissions, 10 lifecycle hooks, fault isolation
🛡️ 6-Layer Security Path zoning, confirmation gates, command blocklist, file snapshots, self-protection, OS sandbox (Linux bwrap / macOS seatbelt / Windows MIC)
📱 IM Scan-to-Bind WeChat/Feishu/WeCom scan-to-bind, 30-second setup, no developer configuration needed
🛒 Skill Marketplace Search & one-click install, GitHub direct install, AI-generated skills on the fly
🌐 30+ LLM Providers Anthropic / OpenAI / DeepSeek / Qwen / Kimi / MiniMax / Gemini … smart failover
💬 6 IM Platforms Telegram / Feishu / WeCom / DingTalk / QQ / OneBot, voice recognition, smart group chat
🔗 MCP Integration Standard MCP client, stdio / HTTP / SSE transports, multi-directory scan, dynamic server management
💾 Dual-Mode Memory Mode 1 fragments (3 layers + 7 types + multi-path recall) + Mode 2 MDRM relational graph (5 dimensions + multi-hop traversal + 3D visualization), auto smart switching
🎭 8 Personas Default / Tech Expert / Boyfriend / Girlfriend / Jarvis / Butler / Business / Family
🤖 Proactive Engine Greetings, task follow-ups, idle chat, goodnight — adapts frequency to your feedback
🧬 Self-Evolution Daily self-check & repair, failure root cause analysis, auto skill generation
🔍 Deep Thinking Controllable thinking mode, real-time chain-of-thought display, IM streaming
🖥️ Multi-Platform Desktop (Win/Mac/Linux) · Web (PC & mobile browser) · Mobile App (Android/iOS), 11 panels, dark theme
📊 Observability 12 trace span types, full-chain token statistics panel
😄 Stickers 5700+ stickers, mood-aware, persona-matched

5-Minute Setup

Option 1: Desktop App (Recommended)

Fully GUI-based, no command line — this is what sets OpenAkita apart from other open-source AI assistants:

OpenAkita Quick Setup

Step What You Do Time
1 Download installer, double-click to install 1 min
2 Follow the onboarding wizard, enter API Key 2 min
3 Start chatting Now
  • No Python installation, no git clone, no config file editing
  • Isolated runtime — won't mess with your existing system
  • Chinese users get automatic mirror switching
  • Models, IM channels, skills, schedules — all configured in the GUI

Download: GitHub Releases — Windows (.exe) / macOS (.dmg) / Linux (.deb)

Learn more at openakita.ai

Option 2: pip Install

pip install openakita[all]    # Install with all optional features
openakita init                # Run setup wizard
openakita                     # Launch interactive CLI

Option 3: Source Install

git clone https://github.com/openakita/openakita.git
cd openakita
python -m venv venv && source venv/bin/activate
pip install -e ".[all]"
openakita init

Commands

openakita                              # Interactive chat
openakita run "Build a calculator"     # Execute a single task
openakita serve                        # Service mode (IM channels)
openakita serve --dev                  # Dev mode with hot reload
openakita daemon start                 # Background daemon
openakita status                       # Check status

Multi-Platform Access

OpenAkita supports Desktop, Web, and Mobile — use it anywhere, on any device:

Platform Details
🖥️ Desktop App Windows / macOS / Linux — native app built with Tauri 2.x
🌐 Web Access PC & mobile browser — enable remote access, open in any browser
📱 Mobile App Android (APK) / iOS (TestFlight) — native wrapper via Capacitor

Desktop App

OpenAkita Desktop App

Cross-platform desktop app built with Tauri 2.x + React + TypeScript:

Panel Function
Chat AI chat, streaming output, Thinking display, drag & drop upload, image lightbox
Agent Dashboard Neural network visualization, real-time multi-Agent status tracking
Agent Manager Create, manage, and configure multiple Agents
IM Channels One-stop setup for all 6 platforms, scan-to-bind
Skills Marketplace search, install, enable/disable
MCP MCP server management
Memory Memory management + LLM-powered review
Scheduler Scheduled task management
Token Stats Token usage statistics
Config LLM endpoints, system settings, advanced options
Feedback Bug reports + feature requests

Dark/light theme · Onboarding wizard · Auto-update · Bilingual (EN/CN) · Start on boot

Mobile App

▶ Watch Mobile App Demo
▶ Click to watch the Mobile App demo on Bilibili

  • Connect your phone to the desktop backend over local network
  • Full-featured: chat, multi-Agent collaboration, memory, skills, MCP — all on mobile
  • Supports real-time streaming and Thinking chain display
  • Preview mode available without connecting to a server

Organization Orchestration

▶ Watch Organization Orchestration Demo
▶ Click to watch: Built a company on OpenAkita, and it runs autonomously (Bilibili)

Beyond multi-Agent collaboration — build an entire AI company. OpenAkita includes a full organization orchestration engine (AgentOrg) that lets you visually design company structures in the GUI, where AI agents operate like a real company:

┌───────────────────────────────────────────────┐
│                CEO / Executive                 │
│       Sets company strategy, coordinates all   │
└───┬───────────┬───────────┬───────────┬───────┘
    ▼           ▼           ▼           ▼
  CTO        Product     Marketing     CFO
 Tech arch   Planning    Strategy    Budget ctrl
    │           │           │           │
    ▼           ▼           ▼           ▼
 Dev team    Design      Content      Analytics

Key Features

Feature Description
Visual Org Chart Drag-and-drop org builder in the GUI — nodes, edges, hierarchies
Autonomous Roles Each node is an independent Agent with its own identity, skills, policies, and memory
Blackboard Sharing 3-level blackboard memory (org / department / node) for secure cross-team info sharing
Message Routing Priority message queues with edge bandwidth control and deadlock detection
Heartbeat Checks Periodic health monitoring of all nodes, auto-remediation on anomalies
Auto-Scaling Automatically recruits new Agents under heavy load, dismisses when idle
External Tools Nodes can request research / browser / code tools on demand with approval workflow
Org Templates Pre-built templates (tech company, content team, etc.) — deploy with one click
Projects & Tasks Tree-structured task decomposition, timeline tracking, org-wide coordination

Multi-Agent Collaboration

▶ Watch Multi-Agent Collaboration Demo
▶ Click to watch the Multi-Agent collaboration demo on Bilibili

OpenAkita has a built-in multi-Agent orchestration system — not just one AI, but an AI team:

You: "Create a competitive analysis report"


┌──────────────────────────────────────┐
│      AgentOrchestrator (Director)     │
│   Decomposes task → Assigns to Agents │
└───┬────────────┬──────────────┬──────┘
    ▼            ▼              ▼
 Search Agent  Analysis Agent  Writing Agent
 (web research) (data crunching) (report drafting)
    │            │              │
    └────────────┴──────────────┘

         Results merged, delivered to you
  • Specialization: Different Agents for different domains, auto-matched to tasks
  • Parallel Processing: Multiple Agents work simultaneously
  • Auto Handoff: If one Agent gets stuck, it hands off to a better-suited one
  • Failover: Agent failure triggers automatic switch to backup
  • Depth Control: Max 5 delegation levels to prevent runaway recursion
  • Visual Tracking: Agent Dashboard shows real-time status of every Agent
  • Instance Pooling: Agent instance pool with LRU eviction for efficient resource use

IM Scan-to-Bind

▶ Watch Scan-to-Bind Tutorial
▶ Click to watch: OpenAkita scan-to-bind for WeChat, Feishu, WeCom (Bilibili)

No developer account needed. No callback URL configuration. No technical knowledge required — scan a QR code, 30 seconds to bind:

Platform How to Bind Time
WeChat Open IM Channels → Click WeChat → Scan QR code 30 sec
Feishu Open IM Channels → Click Feishu → Scan to authorize 30 sec
WeCom Open IM Channels → Click WeCom → Scan to bind 30 sec

Once bound, just @AI in your chat app — send messages, images, files, voice — AI handles it all.


6 IM Platforms

Talk to your AI right inside the chat tools you already use:

Platform Connection Highlights
WeChat Scan-to-bind (iLink) Personal account, no official account needed, 30-second setup
Feishu WebSocket / Webhook Card messages, event subscriptions, scan-to-bind
WeCom Smart Robot callback / WebSocket Streaming replies, proactive push, scan-to-bind
DingTalk Stream WebSocket No public IP needed
Telegram Webhook / Long Polling Pairing verification, Markdown, proxy support
QQ Official WebSocket / Webhook Groups, DMs, channels
OneBot WebSocket Compatible with NapCat / Lagrange / go-cqhttp
  • 📷 Vision: Send screenshots/photos — AI understands them
  • 🎤 Voice: Send voice messages — auto-transcribed and processed
  • 📎 File Delivery: AI-generated files pushed directly to chat
  • 👥 Group Chat: Replies when @mentioned, stays quiet otherwise
  • 💭 Chain-of-Thought: Real-time reasoning process streamed to IM
  • 🔄 Message Interrupts: Insert new instructions between tool calls without waiting

Plugin System

OpenAkita provides a complete plugin architecture with plugin.json manifest declarations, a 3-tier permission model for security, and 10 lifecycle hooks for deep integration:

8 Plugin Types

Type Description Example
🔧 Tool Register custom tools for LLM to call Database queries, API calls
💬 Channel Add new IM channel adapters Slack, Discord adapters
📚 RAG Add external knowledge retrieval sources Notion, Confluence retrieval
🧠 Memory Extend memory storage backends Redis, PostgreSQL storage
🤖 LLM Connect new LLM providers Private model deployments
🪝 Hook Inject logic into the lifecycle Message auditing, content filtering
Skill Wrap Skills as plugins Package skills for distribution
🔗 MCP Wrap MCP Servers as plugins Simplify MCP deployment

3-Tier Permission Model

Tier Description Example
Basic Auto-granted on install Read config, register tools
Advanced Requires user confirmation on install File I/O, network requests
System Must be manually granted per-permission Shell execution, system config

Lifecycle Hooks

on_initon_message_receivedon_tool_resulton_prompt_buildon_retrieveon_session_starton_session_endon_scheduleon_shutdown

Plugins have automatic fault isolation: error count exceeding threshold triggers auto-disable, preventing a single plugin from crashing the system.

Developer docs: Plugin System Overview


Sandbox Security

OpenAkita implements a 6-layer defense-in-depth security model, from path management to OS-level isolation:

L1  Path Zoning         workspace / controlled / protected / forbidden
L2  Confirmation Gate   Dangerous ops (delete files, system commands) require user approval
L3  Command Intercept   regedit, format, rm -rf — blocked outright
L4  File Snapshots      Auto-checkpoint before writes, rollback available
L5  Self-Protection     data/, src/, identity/ — core dirs locked from modification
L6  OS-Level Sandbox    Linux bwrap / macOS seatbelt / Windows MIC

Sandbox Execution

When the policy engine classifies a shell command as HIGH risk, it automatically runs in an OS-level sandbox:

Platform Sandbox Backend Description
Linux bubblewrap (bwrap) User-space container isolation, restricted filesystem and network
macOS sandbox-exec (seatbelt) System-level sandbox policies
Windows Low Integrity (MIC) Mandatory Integrity Control, low-privilege process isolation

Additional Security Mechanisms

  • Policy Engine: POLICIES.yaml for tool permissions, shell command blocklist, path restrictions
  • Resource Budgets: Token / cost / duration / iteration / tool call limits per task
  • Runtime Supervision: Auto-detection of tool thrashing, reasoning loops, token anomalies
  • Local Data: Memory, config, and chat history stored on your machine only
  • Open Source: Apache 2.0, fully transparent codebase

30+ LLM Providers

No vendor lock-in. Mix and match freely:

Category Providers
International Anthropic · OpenAI · Google Gemini · xAI (Grok) · Mistral · OpenRouter · NVIDIA NIM · Groq · Together AI · Fireworks · Cohere
China Alibaba DashScope · Kimi (Moonshot) · Xiaomi MiMo · MiniMax · DeepSeek · SiliconFlow · Volcengine · Zhipu AI · Baidu Qianfan · Tencent Hunyuan · Yunwu · Meituan LongCat · iFlow
Local Ollama · LM Studio (⚠️ Small models have limited tool-calling ability — not recommended yet, pending optimization)

7 capability dimensions: Text · Vision · Video · Tool use · Thinking · Audio · PDF

Smart failover: One model goes down, the next picks up seamlessly.

Recommended Models

International Models (in order of recommendation):

Model Provider Notes
claude-opus-4-6 Anthropic One of the best — top-tier coding & long-task capability, 1M context
gpt-5.4 OpenAI Flagship — native computer-use, 1M context, strong reasoning
claude-sonnet-4-6 Anthropic Best value — fully upgraded default model, 1M context
gpt-5.3-instant OpenAI Best for everyday chat — significantly fewer hallucinations, natural flow
claude-opus-4-5 Anthropic Previous flagship, still extremely capable
claude-sonnet-4-5 Anthropic Stable and reliable for everyday use

Chinese Models (recommended):

Model Provider Notes
kimi-k2.5 Moonshot 1T MoE, Agent Swarm with up to 100 parallel sub-agents, 256K context, open-source
qwen3.5-plus Alibaba 397B MoE, 1M context, 201 languages, extremely cost-effective
mimo-v2-pro Xiaomi 1T MoE, 1M context, global Top 8 ranking, affordable pricing
deepseek-v3 DeepSeek Cost-effective benchmark, strong Chinese support

For complex reasoning, enable Thinking mode — add -thinking suffix to the model name.

⚠️ Local small models not recommended (e.g. 7B/14B quantized): Small models have limited tool-calling and agent collaboration capabilities, prone to hallucinations and format errors. Use API-hosted flagship models for the best experience.


Memory System

Not just a "context window" — true long-term memory. Supports dual modes with automatic switching:

Mode 1: Fragment Memory (Classic)

  • Three layers: Working memory (current task) + Core memory (user profile) + Dynamic retrieval (past experience)
  • 7 memory types: Fact / Preference / Skill / Error / Rule / Persona trait / Experience
  • Multi-path recall: Semantic + full-text + temporal + attachment search
  • Gets smarter over time: Preferences you mentioned two months ago? Still remembered.

Mode 2: MDRM Relational Graph Memory (New)

On top of fragment memory, builds causal chains, timelines, and entity relationship graphs — letting AI truly understand connections between events:

Dimension Description Example
Temporal Event chronology and timelines "What did I do last week?" → auto-constructs timeline
Causal Cause-and-effect chains "What caused this bug?" → traces causal chain
Entity Relationships between people/projects/concepts "Which projects did Alice work on?" → entity graph
Action Dependencies, prerequisites, compositions "What else is needed to finish X?" → dependency analysis
Context Project/session attribution "All discussions about this project" → cross-session aggregation
  • 4 node types: Event / Fact / Decision / Goal
  • Multi-hop graph traversal: Starting from seed nodes, expands along relationship edges to find deep connections
  • 3-layer encoding: Fast rule-based encoding → summary backfill → session-end batch LLM encoding
  • 3D visualization: Frontend supports 3D visualization of the memory graph

Smart Mode Switching

Set memory_mode to auto (default) and the system auto-routes based on query characteristics: causal/timeline/cross-session questions use Mode 2 graph traversal, preference/fact queries use Mode 1 semantic retrieval.

  • AI-driven extraction: Automatically distills valuable information after each conversation, dual-track writes to both modes
  • 3D memory graph: Visualize memory nodes and relationships, intuitively understand AI's memory structure

MCP Integration

OpenAkita includes a full MCP (Model Context Protocol) client, enabling AI to connect with any external service:

Feature Description
3 Transports stdio (default), Streamable HTTP, SSE (legacy compatible)
Multi-Dir Scan Auto-discovers MCP configs from built-in mcps/, .mcp, data/mcp/servers/ directories
Dynamic Management Add/remove MCP servers at runtime, no restart needed
Tool Suite call_mcp_tool, list_mcp_servers, add_mcp_server, connect_mcp_server, and more
Progressive Disclosure MCP tool catalog + prompt templates, shown on demand
GUI Management Desktop MCP panel for one-stop configuration

Connect to GitHub, databases, Playwright browser, filesystem, or any MCP Server.


Self-Evolution

OpenAkita keeps getting stronger:

Daily 04:00   →  Self-check: analyze error logs → AI diagnosis → auto-fix → push report
After failure →  Root cause analysis (context loss / tool limitation / loop / budget) → suggestions
Missing skill →  Auto-search GitHub for skills, or AI generates one on the spot
Missing dep   →  Auto pip install, auto mirror switching for China
Every chat    →  Extract preferences and experience → long-term memory

Architecture

Desktop App (Tauri + React)

Identity ─── SOUL.md · AGENT.md · POLICIES.yaml · 8 Persona Presets

Core     ─── ReasoningEngine(ReAct) · Brain(LLM) · ContextManager
    │        PromptAssembler · RuntimeSupervisor · ResourceBudget

Agents   ─── AgentOrchestrator(Coordination) · AgentInstancePool(Pooling)
    │        AgentFactory · FallbackResolver(Failover)

Org      ─── OrgRuntime(Runtime) · OrgManager(CRUD)
    │        OrgMessenger(Routing) · Blackboard(Shared Memory)
    │        OrgIdentity(Inheritance) · OrgPolicies(Policies)

Plugins  ─── PluginManager(Discovery/Loading) · PluginAPI(Host Interface)
    │        HookRegistry(10 Hooks) · PluginSandbox(Fault Isolation)

Memory   ─── Mode1: UnifiedStore(SQLite+Vector) · RetrievalEngine(Multi-path)
    │        Mode2: RelationalStore(MDRM Graph) · GraphEngine(Multi-hop)
    │        MemoryModeRouter(Auto Switch) · MemoryEncoder(3-Layer)

Tools    ─── Shell · File · Browser · Desktop · Web · MCP · Skills
    │        Plan · Scheduler · Sticker · Persona · Agent Delegation

Security ─── PolicyEngine(6-Layer) · SandboxExecutor(OS Sandbox)
    │        ConfirmationGate · CommandFilter · Checkpoint

Evolution ── SelfCheck · FailureAnalyzer · SkillGenerator · Installer

Channels ─── CLI · Telegram · Feishu · WeCom · WeChat · DingTalk · QQ · OneBot

Tracing  ─── AgentTracer(12 SpanTypes) · DecisionTrace · TokenStats

Documentation

Document Content
Configuration Guide Desktop Quick Setup & Full Setup walkthrough
LLM Provider Setup API Key registration + endpoint config + Failover
IM Channel Setup Telegram / Feishu / DingTalk / WeCom / QQ / OneBot tutorial
Plugin System Overview Plugin types, permissions, developer guide
Org Orchestration Design AgentOrg technical architecture and design
Org Orchestration Guide Organization orchestration user guide
Quick Start Installation and basics
Architecture System design and components
Configuration All config options
Deployment Production deployment
MCP Integration Connecting external services
Skill System Creating and using skills

Community

WeChat Official Account
WeChat Official
Follow for updates
Personal WeChat
WeChat (Personal)
Note "OpenAkita" to join group
WeChat Group
WeChat Group
Scan to join (⚠️ refreshed weekly)
QQ Group
QQ Group: 854429727
Scan or search to join

🌐 Website · 💬 Discord · 🐦 X (Twitter) · 📧 Email

Issues · Discussions · ⭐ Star


Acknowledgments

Community Contributors

License

Apache License 2.0 — See LICENSE

Third-party licenses: THIRD_PARTY_NOTICES.md

Star History

Star History Chart

OpenAkita — Open-Source Multi-Agent AI Assistant That Gets Things Done
openakita.ai

Installationen

Installationen 13
Globales Ranking #601 von 601

Sicherheitsprüfung

Keine Sicherheitsdaten für diesen Skill verfügbar.

EU EU-Hosted Inference API

Power your AI Agents with the best open-source models.

Drop-in OpenAI-compatible API. No data leaves Europe.

Explore Inference API

GLM

GLM 5

$1.00 / $3.20

per M tokens

Kimi

Kimi K2.5

$0.60 / $2.80

per M tokens

MiniMax

MiniMax M2.5

$0.30 / $1.20

per M tokens

Qwen

Qwen3.5 122B

$0.40 / $3.00

per M tokens

So verwenden Sie diesen Skill

1

Install obra/superpowers@requesting-code-review by running npx skills add openakita/openakita --skill obra/superpowers@requesting-code-review in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für obra/superpowers@requesting-code-review, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.

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