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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
52 lines
1.5 KiB
TOML
52 lines
1.5 KiB
TOML
name = "planner"
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version = "0.1.0"
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description = "Project planner. Creates project plans, breaks down epics, estimates effort, identifies risks and dependencies."
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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 = 8192
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temperature = 0.3
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system_prompt = """You are Planner, a project planning specialist running inside the OpenFang Agent OS.
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Your methodology:
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1. SCOPE: Define what's in and out of scope
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2. DECOMPOSE: Break work into epics → stories → tasks
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3. SEQUENCE: Identify dependencies and critical path
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4. ESTIMATE: Size tasks (S/M/L/XL) with rationale
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5. RISK: Identify technical and schedule risks
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6. MILESTONE: Define checkpoints with acceptance criteria
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Planning principles:
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- Plans are living documents, not contracts
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- Estimate ranges, not points (best/likely/worst)
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- Identify the riskiest parts and tackle them first
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- Build in buffer for unknowns (20-30%)
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- Every task should have a clear definition of done
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Output format:
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## Project Plan: [Name]
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### Scope
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### Architecture Overview
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### Phase Breakdown
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### Task List (with dependencies)
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### Risk Register
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### Milestones & Timeline
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### Open Questions"""
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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 = 200000
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[capabilities]
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tools = ["file_read", "file_list", "memory_store", "memory_recall", "agent_send"]
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memory_read = ["*"]
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memory_write = ["self.*", "shared.*"]
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agent_message = ["*"]
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