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🏭 Agent Mill — Feature Showcase

This document walks through every major feature of Agent Mill with screenshots and explanations.


1. Command Center — Agent Workstation

The command center provides a real-time overview of all your AI agents, their status, and quick access to conversations and tasks.

View Description
Grid View Card-based layout showing agent names, descriptions, status indicators
Station View Visual office-desk diorama with dual monitors, status LEDs, and desk accessories

Key actions: Start a conversation, create tasks, monitor agent health.


2. Multi-Tab Agent Editor

Each agent is configured through a professional 4-tab editor:

Tab 1: Basic Info

Tab 2: Role & Prompt

Tab 3: Model & Compute

Tab 4: Knowledge & Skills


3. Dual-Path Streaming Engine

Agent Mill’s core technical differentiator — two streaming paths that produce identical SSE events:

Provider Streaming Mechanism
Anthropic (Claude) Claude Agent SDK native SSE — true streaming with thinking + tool_use events
OpenAI-compatible Custom tool_calls multi-turn loop (DeepSeek, Qwen, GLM, OpenAI)

SSE Event Order: meta → thinking → text → tool_use → tool_result → file → ui → error → done

What This Enables


4. Skill System (Three Forms)

Type Description
Path ZIP upload with SKILL.md + resource files. Ideal for complex business processes.
Callable Python function direct import. Lightweight tools, rapid development.
Composite YAML DAG step orchestration with conditional branching and parallel execution.

Security


5. MCP Connector System

Three transport protocols to connect any external tool:

Protocol Use Case
stdio Local subprocess tools (CLI, scripts)
sse Server-Sent Events for long-running connections
http Streamable HTTP for REST APIs

Management: CRUD + connection test + tool list discovery + auto-generated Chinese summaries + per-agent isolation.


6. RAG Knowledge Base

Stage Technology
Upload 30+ file formats (PDF, DOCX, XLSX, images, code)
Parse MinerU engine with auto-fallback
Chunk 500-char window, 50-char overlap
Embedding OpenAI-compatible API (text-embedding-3-small)
Vector Store ZVec (Alibaba, Rust kernel, embedded — no extra containers)
Retrieval Cosine similarity, configurable top_k

Auto-injection: Every conversation turn automatically retrieves relevant knowledge and injects it into the system prompt.


7. Multi-Agent Collaboration

Mode Description
Sequential Agent1 → Agent2 → … → AgentN
Parallel All agents process simultaneously
MapReduce Individual processing → aggregation

Communication: Asynchronous message passing with priority support (normal/high), message delegation, and auto-consumption polling.


8. Workflow & Solution Pack Editor


9. Dashboard & Analytics


10. Enterprise Features

Feature Description
RBAC Three roles: admin/operator/user
SSO/LDAP LDAP bind + OIDC full callback flow
Audit Logs Dual-table: admin operations + call logs
Data Masking Auto-mask email/phone/ID card in logs
Rate Limiting Token bucket per-path
Quota Control User-level monthly token/cost limits
Alert Notifications Rule engine + DingTalk/WeChat/Feishu webhooks

11. Mobile App

Independent Vue 3 application at /m.html with:


12. File Processing

Format Engine
TXT/MD/CSV/JSON/HTML/XML/YAML Direct read
PDF MinerU → pypdf fallback
DOCX MinerU → python-docx fallback
XLSX MinerU → openpyxl fallback
Images MinerU OCR

Preview: HTML iframe, PDF native, Markdown, code, SVG, images (JWT-secured with expiring tokens).


Complete Module Checklist

# Module Status
1 Dual-path Streaming (Anthropic + OpenAI)
2 Skill System (path/callable/composite)
3 MCP Connector (stdio/sse/http)
4 RAG Knowledge Base
5 DAG Solution Pack
6 Workflow Editor (Vue Flow)
7 Template Market
8 Memory System
9 Context Compression
10 Self-Learning
11 Multi-Agent Collaboration
12 RBAC
13 SSO/LDAP
14 Audit & Compliance
15 Data Masking
16 API Rate Limiting
17 Quota Control
18 Alert Notifications
19 Dashboard & Analytics
20 File Processing
21 Security (7 layers)
22 Mobile App