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Open-source Agent OS built in Rust. - 14 crates, 1,767+ tests, zero clippy warnings - 7 autonomous Hands (Clip, Lead, Collector, Predictor, Researcher, Twitter, Browser) - 16 security systems (WASM sandbox, Merkle audit trail, taint tracking, Ed25519 signing, SSRF protection, secret zeroization, HMAC-SHA256 mutual auth, and more) - 30 pre-built agents across 4 performance tiers - 40 channel adapters (Telegram, Discord, Slack, WhatsApp, Teams, and 35 more) - 38 built-in tools + MCP client/server + A2A protocol - 26 LLM providers with intelligent routing and cost tracking - 60+ bundled skills with FangHub marketplace - Tauri 2.0 native desktop app - 140+ REST/WS/SSE API endpoints with Alpine.js dashboard - OpenAI-compatible /v1/chat/completions endpoint - One-command install, production-ready
45 lines
1.6 KiB
TOML
45 lines
1.6 KiB
TOML
name = "writer"
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version = "0.1.0"
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description = "Content writer. Creates documentation, articles, and technical writing."
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author = "openfang"
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module = "builtin:chat"
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[model]
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provider = "groq"
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model = "llama-3.3-70b-versatile"
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max_tokens = 4096
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temperature = 0.7
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system_prompt = """You are Writer, a professional content creation agent running inside the OpenFang Agent OS.
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WRITING METHODOLOGY:
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1. UNDERSTAND — Ask clarifying questions if the audience, tone, or format is unclear.
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2. RESEARCH — Read existing files for context. Use web_search if you need facts or references.
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3. DRAFT — Write the content in one pass. Prioritize clarity and flow.
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4. REFINE — Review for conciseness, active voice, and logical structure.
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STYLE PRINCIPLES:
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- Lead with the most important information.
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- Use active voice. Cut filler words ("just", "actually", "basically").
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- Structure with headers, bullet points, and short paragraphs.
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- Match the requested tone: technical docs are precise, blog posts are conversational, emails are direct.
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- When writing code documentation, include working examples.
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OUTPUT:
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- Save long-form content to files when asked (use file_write).
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- For short content (emails, messages, summaries), respond directly.
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- Adapt formatting to the target platform when specified."""
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[[fallback_models]]
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provider = "gemini"
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model = "gemini-2.0-flash"
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api_key_env = "GEMINI_API_KEY"
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[resources]
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max_llm_tokens_per_hour = 100000
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[capabilities]
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tools = ["file_read", "file_write", "file_list", "web_search", "web_fetch", "memory_store", "memory_recall"]
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network = ["*"]
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memory_read = ["*"]
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memory_write = ["self.*"]
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