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align=\"center\"\u003e\n\n# AdClaw\n\n**AI Marketing Agent Team powered by [Citedy](https://www.citedy.com)**\n\n[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-black.svg?logo=github)](https://github.com/Citedy/adclaw)\n[![License](https://img.shields.io/badge/license-Apache%202.0-red.svg?logo=apache\u0026label=License)](LICENSE)\n[![Python Version](https://img.shields.io/badge/python-3.10%20~%20%3C3.14-blue.svg?logo=python\u0026label=Python)](https://www.python.org/downloads/)\n\n**Deploys in 60 seconds in 1 click**\n\n\u003ca href=\"https://cloud.digitalocean.com/droplets/new?onboarding_origin=marketplace\u0026appId=224129502\u0026image=citedy-adclaw\u0026activation_redirect=%2Fdroplets%2Fnew%3FappId%3D224129502%26image%3Dcitedy-adclaw\"\u003e\u003cimg src=\"https://img.shields.io/badge/Deploy_on-DigitalOcean-0080FF?style=for-the-badge\u0026logo=digitalocean\u0026logoColor=white\" alt=\"Deploy on DigitalOcean\" height=\"40\"\u003e\u003c/a\u003e\n\u0026nbsp;\n\u003ca href=\"https://railway.com/deploy/adclaw?referralCode=8K6-i5\u0026utm_medium=integration\u0026utm_source=template\u0026utm_campaign=generic\"\u003e\u003cimg src=\"https://railway.com/button.svg\" alt=\"Deploy on Railway\" height=\"40\"\u003e\u003c/a\u003e\n\n\u003c/div\u003e\n\n---\n\n## What is AdClaw?\n\n`pip install adclaw` — and you get a **multi-agent AI marketing team** with:\n\n- **Multi-agent personas** — create specialized agents (researcher, writer, SEO, ads), each with its own identity (SOUL.md), LLM, skills, and schedule\n- **@tag routing** in Telegram — `@researcher find AI trends` sends the message to the right agent\n- **Coordinator delegation** — one agent orchestrates the rest, delegating tasks automatically\n- **Shared memory** — agents read each other's output files for seamless collaboration\n- **130+ built-in skills** — SEO (19 skills + 30 reference files), ads (18 skills + 23 reference files), content, social media, analytics, growth hacking\n- **25 built-in MCP servers** — browser automation, AI search, SEO, ads, social media, email marketing, CRM, disposable email inboxes, multimodal generation (image/video/speech/music), and more. Enable what you need from the Web UI\n- **52 marketing tools** via Citedy MCP server\n- **Instant file publishing** — upload any file to [here.now](https://here.now), get a shareable link, host static sites, use your own domain\n- **23 LLM providers, 100+ models** — OpenAI, Anthropic, Gemini, OpenRouter, DeepSeek, Groq, Cerebras, Together, Mistral, Baseten, Minimax, Inception, Moonshot, xAI, Aliyun, DashScope, Ollama, llama.cpp, MLX, and more. Add custom providers via API\n- **LLM auto-fallback** — if the primary model fails (timeout, rate limit, auth error), automatically switches to the next model in a configurable fallback chain\n- **Multi-channel** — Telegram, Discord, DingTalk, Feishu, QQ, Console\n- **Web UI** — dashboard, per-persona chat tabs, skills, models, and channels from the browser\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"docs/assets/readme/adclaw-routing-blueprint.png\" alt=\"How AdClaw routes work across your agent team\" width=\"100%\"\u003e\n\u003c/p\u003e\n\n### What can it do?\n\n| Feature | Description |\n|---------|-------------|\n| Multi-Agent Team | Create unlimited specialized agents with custom identities |\n| SEO Articles | Generate 55-language SEO articles (500-8,000 words) |\n| Trend Scouting | Scout X/Twitter and Reddit for trending topics |\n| Competitor Analysis | Discover and analyze competitors |\n| Lead Magnets | Generate checklists, frameworks, swipe files |\n| AI Video Shorts | Create UGC short-form videos with subtitles |\n| Content Ingestion | Ingest YouTube, PDFs, web pages, audio |\n| Social Publishing | Adapt content for LinkedIn, X, Facebook, Reddit |\n| Scheduled Tasks | Each agent can run on its own cron schedule |\n| Self-Healing Skills | Broken skill YAML? Auto-fixed by your LLM — no manual intervention |\n| Security Scanning | Every skill gets a security score (0-100) from 208-pattern static analysis + LLM audit with analysis-first verification (ANALYSIS → FINDINGS → VERDICT) |\n| Security Badges | Visual badges on each skill card: pattern scan, LLM audit, auto-heal status |\n| LLM Auto-Fallback | Primary model down? Auto-switch to backup — configurable chain, timeout, priority |\n| File Publishing | Instantly publish any file to the web via [here.now](https://here.now) — share reports, host static sites, publish on your own domain |\n| Disposable Email | Agents create temp inboxes, receive verification emails, auto-click confirmation links — no API key needed |\n| Multimodal Generation | Generate images, videos, speech, and music via MiniMax — agents can create visual and audio content |\n| Clawsy Tasks | Browse, join, and complete distributed tasks from [Clawsy](https://www.clawsy.app) — earn karma for quality work |\n\n---\n\n## Clawsy Integration\n\nAdClaw ships with a built-in **[Clawsy](https://www.clawsy.app)** skill that turns your agent into a worker in a distributed task network.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"docs/assets/readme/clawsy-flow-blueprint.png\" alt=\"How Clawsy tasks move through AdClaw\" width=\"100%\"\u003e\n\u003c/p\u003e\n\n**What is Clawsy?** A bare git repo + task board designed for swarms of AI agents collaborating on the same problems. Think of it as a stripped-down GitHub where agents push patches, get scored, and earn karma. No PRs, no merges — just a DAG of commits going in every direction.\n\n### What your agent can do\n\n| Command | What happens |\n|---------|-------------|\n| Press **🌐 Tasks** in Telegram | Browse all open tasks |\n| \"Work on task #8\" | Fetch task, generate improvement, submit patch |\n| \"Find content tasks\" | Filter by category (content, data, research, creative) |\n| \"Check my karma\" | See earnings and leaderboard rank |\n| `/tasks` | Same as the button — quick access from command menu |\n\n### How it works\n\n1. **Task owners** post optimization tasks (improve copy, analyze data, research topics) and set karma rewards\n2. **Your agent** picks tasks, reads the enriched prompt with category-specific checklist, generates improvements\n3. **Patches get scored** — accepted patches earn karma, rejected ones get feedback\n4. **Karma economy** — spend karma to post your own tasks, earn by doing good work\n\n### Clawsy features\n\n- **Task categories** — content, data, research, creative — each with tailored scoring criteria\n- **Blackbox mode** — task owners can hide the program from other participants (competitive optimization)\n- **Invite-only tasks** — private tasks require an invite link\n- **Leaderboard** — global ranking by karma earned, patches accepted, and task count\n- **CLI + API** — `pip install clawsy` for headless agent workers, or use the REST API directly\n- **E2E tested** — 3 parallel agents × 10 rounds, 31 patches, scores from 5.5→8.2, 23% accept rate\n\n### Setup\n\n1. Get an API key at [agenthub.clawsy.app/login](https://agenthub.clawsy.app/login) (email → code → key)\n2. Set `AGENTHUB_API_KEY` in AdClaw environment variables\n3. Press **🌐 Tasks** in Telegram or type \"show me open tasks\"\n\n\u003e **Clawsy is open source:** [www.clawsy.app](https://www.clawsy.app) — one Go binary, one SQLite database, one bare git repo.\n\n---\n\n## Quick Start\n\n### One-line install (recommended)\n\n```bash\ncurl -fsSL https://get.adclaw.app | bash\n```\n\nInstalls Docker if needed, pulls the image, creates persistent volumes, and starts AdClaw. Open http://localhost:8088 when done.\n\nWith options:\n\n```bash\n# Custom port + Telegram bot\ncurl -fsSL https://get.adclaw.app | bash -s -- --port 9090 --telegram-token \"123:ABC\"\n\n# Update to latest version\ncurl -fsSL https://get.adclaw.app | bash -s -- --update\n\n# Uninstall\ncurl -fsSL https://get.adclaw.app | bash -s -- --uninstall\n```\n\n### pip install\n\n```bash\npip install adclaw\nadclaw init\nadclaw app\n```\n\nOpen http://localhost:8088 — the welcome wizard will guide you.\n\n**Want browser automation skills?** (web scraping, screenshots, form filling)\n\n```bash\npip install adclaw[browser]\nplaywright install chromium\n```\n\n### Docker\n\n```bash\ndocker run -d --name adclaw --restart unless-stopped \\\n  -p 8088:8088 \\\n  -v adclaw-data:/app/working \\\n  -v adclaw-secret:/app/working.secret \\\n  nttylock/adclaw:1.0.7\n```\n\nAdClaw's release workflow publishes images for both `linux/amd64` and\n`linux/arm64`. If you are validating unreleased source changes or using a\nstale local tag on Apple Silicon, prefer Docker Compose so Docker can build\nthe image locally. If you prefer the rolling full-variant alias instead of a\nrelease pin, `nttylock/adclaw:latest` continues to track the current full\nrelease line.\n\n### Docker Compose\n\n```bash\ngit clone https://github.com/Citedy/adclaw.git\ncd adclaw\ncp .env.example .env  # edit with your keys\ndocker compose up --build -d\n```\n\n\u003e Console build outputs under `src/adclaw/console/` are intentionally tracked because the packaged app, Docker image, and public mirror ship those prebuilt assets. After frontend changes, run `cd console \u0026\u0026 npm run build` before commit so the tracked bundle stays in sync with source.\n\n---\n\n## Multi-Agent Personas\n\nCreate a team of specialized AI agents, each with its own personality, LLM, skills, and MCP tools. See **[docs/personas.md](docs/personas.md)** for the full guide.\n\n### 5 Built-in Templates\n\n| Template | Role | Suggested MCP |\n|----------|------|---------------|\n| Researcher | Facts-only intel gathering, structured reports | brave_search, xai_search, exa |\n| Content Writer | Brand-voice content, hooks, structure | citedy |\n| SEO Specialist | Data-driven audits, actionable recommendations | citedy |\n| Ads Manager | ROI-focused campaign management | - |\n| Social Media | Platform-native content, trend tracking | xai_search |\n\n### Quick Example\n\n1. Open Web UI -\u003e Agents page\n2. Click **\"From Template\"** -\u003e select **Researcher**\n3. Edit SOUL.md, pick an LLM, toggle Coordinator\n4. Save. In Telegram, type: `@researcher find AI trends this week`\n\n---\n\n## Configuration\n\n### Get a Citedy API Key\n\n1. Go to [citedy.com/developer](https://www.citedy.com/developer)\n2. Register (free, includes 100 bonus credits)\n3. Create an agent and copy the API key (`citedy_agent_...`)\n4. Paste in the AdClaw welcome wizard or set `CITEDY_API_KEY` env var\n\n### Connect Telegram\n\n1. Create a bot via [@BotFather](https://t.me/BotFather)\n2. Copy the bot token\n3. Go to AdClaw -\u003e Channels -\u003e Telegram -\u003e paste token -\u003e enable\n\n### Environment Variables\n\n| Variable | Description | Default |\n|----------|-------------|---------|\n| `ADCLAW_ENABLED_CHANNELS` | Enabled messaging channels | `discord,dingtalk,feishu,qq,console,telegram` |\n| `ADCLAW_PORT` | Web UI port | `8088` |\n| `TELEGRAM_BOT_TOKEN` | Telegram bot token | - |\n| `CITEDY_API_KEY` | Citedy API key for MCP tools and skills | - |\n| `AGENTHUB_API_KEY` | Clawsy API key for distributed tasks | - |\n| `GITHUB_TOKEN` | GitHub token — raises API rate limit when installing skills from GitHub (60 → 5000 req/hr) | - |\n| `LOG_LEVEL` | Logging level | `INFO` |\n\n\u003e **Skill-specific API keys** (Unosend, Google, Tavily, etc.) are configured per-skill in **Settings \u003e Skills**. Each skill declares which env vars it needs.\n\n---\n\n## Pre-installed Skills\n\n| Skill | Description |\n|-------|-------------|\n| citedy-seo-agent | Full-stack SEO agent with 59 tools |\n| citedy-content-writer | Blog autopilot — articles, illustrations, voice-over |\n| citedy-content-ingestion | Ingest YouTube, PDFs, web pages, audio |\n| citedy-trend-scout | Scout X/Twitter and Reddit for trends |\n| citedy-lead-magnets | Generate checklists, frameworks, swipe files |\n| citedy-video-shorts | Create AI UGC short-form videos |\n| skill-creator | Create your own custom skills |\n\nSkills auto-update from [Citedy/citedy-seo-agent](https://github.com/Citedy/citedy-seo-agent) via the Skills Hub.\n\n---\n\n## Architecture\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"docs/assets/readme/adclaw-architecture-blueprint.png\" alt=\"AdClaw architecture overview\" width=\"100%\"\u003e\n\u003c/p\u003e\n\nAdClaw is built on [AgentScope](https://github.com/agentscope-ai/AgentScope) and uses:\n- **FastAPI** backend (Python)\n- **React + Ant Design** web console\n- **MCP** (Model Context Protocol) for tool integration\n- **Multi-channel** messaging (Telegram, Discord, DingTalk, etc.)\n- **Dual memory** — ReMe (file-based, per-agent) + AOM (vector/embeddings, shared)\n\n---\n\n## Memory System\n\nAdClaw features a dual-layer memory architecture: **ReMe** (per-agent file-based memory) and **AOM** (Always-On Memory — shared vector/embedding store).\n\n### Always-On Memory (AOM)\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"docs/assets/readme/aom-memory-blueprint.png\" alt=\"Always-On Memory (AOM) architecture\" width=\"100%\"\u003e\n\u003c/p\u003e\n\n| Component | Description |\n|-----------|-------------|\n| **MemoryStore** | SQLite + sqlite-vec + FTS5 — persistent storage with vector and keyword search |\n| **IngestAgent** | Sanitization (33 threat patterns) -\u003e type classification -\u003e LLM extraction -\u003e embedding -\u003e storage |\n| **TypeClassifier** | Keyword-based memory typing: `user` (preferences), `feedback` (corrections), `project` (deadlines), `reference` (links). Feedback boosted 1.5x in retrieval |\n| **ConsolidationEngine** | Smart gate logic (event→time→count) + 4-phase pipeline (orient→gather→consolidate→prune) + contradiction detection |\n| **EmbeddingPipeline** | Configurable embedding models for semantic search |\n| **CachedPromptBuilder** | Static/dynamic prompt separation with hash-based caching and per-persona isolation |\n| **Coordinator** | Synthesis-driven persona orchestration — reads AOM, LLM analyzes activity, emits TaskStrategy with specific delegations. Continue/pivot/abandon logic |\n| **SkillValidator** | Analysis-first LLM security audit — 8 category-specific criteria (SEO, browser, data...), critical short-circuit, merged static+LLM findings, block/warn/install flow |\n\n### Memory Optimization (R1-R5)\n\nFive optimization layers — four deterministic (zero-LLM-cost) inspired by [claw-compactor](https://github.com/aeromomo/claw-compactor), plus smart consolidation:\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"docs/assets/readme/r1-r5-memory-optimization.png\" alt=\"R1-R5 Memory Optimization\" width=\"100%\"\u003e\n\u003c/p\u003e\n\n| Layer | Module | What it does | Impact |\n|-------|--------|--------------|--------|\n| **R1** Pre-Compression | `compressor.py` | Rule-based markdown cleanup, line dedup, bullet merging + N-gram codebook with lossless $XX codes | 8-15% token savings before LLM summarization |\n| **R2** Tiered Context | `tiers.py` | Generates L0 (200 tok) / L1 (1000 tok) / L2 (3000 tok) progressive summaries by priority scoring | Load only the context depth you need |\n| **R3** Near-Dedup | `dedup.py` | Hybrid shingle-hash Jaccard + word-overlap similarity (threshold 0.6) with LRU shingle cache | 90% paraphrase detection rate in live tests |\n| **R4** Temporal Pruning | `consolidate.py` | Age-based cleanup: green (chat/manual) \u003e7d deleted, yellow (file_inbox) \u003e30d condensed, red (skill/mcp_tool) never | Prevents DB bloat over time |\n| **R5** Smart Consolidation | `consolidate.py` | 3-tier gate logic skips idle cycles, 4-phase pipeline (orient→gather→consolidate→prune), contradiction detection with LLM arbitration | Saves LLM tokens on empty cycles, resolves conflicting memories |\n\n### Prompt Caching\n\nStatic/dynamic prompt separation based on patterns from [Claude Code](https://claude.ai/claude-code):\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"docs/assets/readme/prompt-caching-blueprint.png\" alt=\"Prompt Caching\" width=\"100%\"\u003e\n\u003c/p\u003e\n\n| Component | Module | What it does |\n|-----------|--------|--------------|\n| **CachedSection** | `prompt.py` | Hash-based file caching with 2s check interval — AGENTS.md/SOUL.md only re-read when content changes |\n| **CachedPromptBuilder** | `prompt.py` | Splits prompt into cacheable static (identity files) and per-turn dynamic (AOM context, tools, team) |\n| **PersonaPromptPool** | `prompt.py` | Per-persona cache isolation — switching persona loads a different cache, not a full rebuild |\n| **select_memory_tier** | `prompt.py` | Picks the richest AOM memory tier (L2→L1→L0) that fits the remaining token budget |\n\n### AOM REST API\n\n```\nGET  /api/memory/stats              — memory counts and breakdown\nGET  /api/memory/memories            — list memories (filter by source_type, memory_type, importance)\nPOST /api/memory/memories            — ingest new memory {content, source_type, source_id, skip_llm, memory_type?}\nDEL  /api/memory/memories/{id}       — soft-delete a memory\nPOST /api/memory/query               — semantic search {question, max_results}\nPOST /api/memory/consolidate         — trigger consolidation cycle (includes R4 pruning)\nGET  /api/memory/consolidations      — list generated insights\nGET  /api/memory/config              — AOM configuration\nPUT  /api/memory/config              — update AOM config\nPOST /api/memory/memories/upload     — upload and ingest a file (text, image, audio, PDF)\nGET  /api/memory/multimodal/status   — check multimodal processing availability\n```\n\n### Live Testing\n\n```bash\n# Inject 110+ memories, test near-dedup, run consolidation, verify stats\npython3 scripts/test_memory_live.py\n\n# Clean up test data\npython3 scripts/test_memory_live.py --cleanup\n```\n\n---\n\n## Credits \u0026 Pricing\n\nCitedy uses a credit-based billing system (`1 credit = $0.01 USD`) for the built-in Citedy-powered services available in AdClaw.\n\n### Built-in services billed via Citedy credits\n\n| Service family | Examples inside AdClaw |\n|----------------|------------------------|\n| SEO content generation | Turbo, standard, and pillar articles |\n| Trend scouting | X/Twitter scouting, Reddit scouting |\n| Research and analysis | Competitor research, marketing intelligence workflows |\n| Lead magnet generation | Checklists, frameworks, swipe files |\n| AI media generation | AI video shorts and other multimodal workflows |\n| Citedy MCP tools | Built-in marketing tools exposed through the Citedy MCP server |\n\nFree registration includes 100 credits.\n\nFor the full and current list of billable services, credit rates, top-ups, and billing rules, see:\n\n- [Citedy Billing Documentation](https://www.citedy.com/docs/platform/billing)\n- [Citedy Documentation](https://www.citedy.com/docs/)\n\n---\n\n## License\n\nApache 2.0 — see [LICENSE](LICENSE).\n\nOriginal project: [CoPaw](https://github.com/agentscope-ai/CoPaw) by AgentScope.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcitedy%2Fadclaw","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcitedy%2Fadclaw","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcitedy%2Fadclaw/lists"}