hidmaster: One-click AI Agent Workflow Enhancement Tool, Enabling AI Coding Assistants to Automatically Master 22 Production-Grade Skills

hidmaster is an open-source AI agent workflow enhancement tool developed and maintained by SincereMa (GitHub repository: https://github.com/SincereMa/hidmaster, release date: June 14, 2026). Addressing the 'capability dilemma' of mainstream AI coding assistants like Claude Code and Codex (lack of systematic workflows, requiring repeated manual prompts), it injects 22 production-grade skills and automatic orchestration capabilities via one-click installation, enabling AI assistants to independently complete the full development process from codebase exploration to delivery.

With the popularity of AI coding assistants like Claude Code, Codex, and OpenCode, developers have found that while these tools have strong code generation capabilities, they lack systematic workflows—they cannot independently explore codebases, design architectures, execute tests, generate documents, or collaborate. Developers need to repeatedly prompt manually (e.g., "analyze code structure", "write test cases"), and fragmented interactions significantly reduce productivity. As an "AI agent workflow operating system", hidmaster aims to solve this pain point.

hidmaster is an open-source AI agent workflow enhancement tool, with the core concept of "letting AI assistants automatically know when and how to use the right skills". Core features include:

1. One-click installation: Quick deployment via curl command;
2. Multi-agent support: Compatible with Claude Code, MiMo-Code, Codex, OpenCode;
3. 22 production-grade skills: Covering the full development lifecycle;
4. Automatic orchestration: AI automatically triggers workflows based on task types;
5. Intelligent distribution: Detects the project's AI assistant type and installs skills to the correct location.

hidmaster divides its 22 skills into six categories:

• Core Development Process: explore (codebase exploration), architect (architecture design), implement (code implementation), validate (validation), ship (delivery), iterate (iteration);
• Development Quality Assurance: debug (debugging), refactor (refactoring), optimize (performance optimization);
• Project Planning: brainstorm (brainstorming), estimate (effort estimation), roadmap (roadmap);
• Code Review: code-review (code review), security-review (security review), performance-review (performance review);
• Document Generation: generate-docs (document generation), api-docs (API documentation), changelog (changelog);
• Agent Collaboration: parallel (parallel execution), subagent (sub-agent), handoff (task handoff).

The core value of hidmaster lies in automatic orchestration—teaching AI assistants when to use skills (each skill includes trigger conditions, dependencies, steps, and outputs). The task automatic classification mechanism analyzes task complexity, parallel requirements, and scope definition. Typical workflow examples:

• Fixing a login bug: explore → debug → implement → validate;
• Adding user authentication: explore → architect → implement → validate → ship;
• Code review: code-review → security-review → performance-review.

Installation Methods:

1. One-click installation: curl -fsSL https://raw.githubusercontent.com/SincereMa/hidmaster/master/install.sh | bash (deploys to ~/.hidmaster/ and adds to PATH);
2. Manual installation: git clone https://github.com/SincereMa/hidmaster.git && cd hidmaster && bash install.sh. System Requirements: Bun runtime environment, supports mainstream AI assistants like Claude Code. Basic Usage: Enter the project directory and execute hidmaster—it automatically detects the AI assistant and installs skills. Command options: detect (lists AI assistants), --force (forces reinstallation).

hidmaster's application scenarios include:

1. New Feature Development: AI automatically completes exploration → architecture → implementation → validation → delivery;
2. Code Refactoring: After inputting the target, AI automatically analyzes code smells → formulates a plan → executes refactoring → validates quality;
3. Multi-agent Collaboration: Main agent splits tasks → sub-agents process in parallel → integrates results → consistency check.

Significance: hidmaster promotes the evolution of AI coding assistants from "code tools" to "collaborators", enabling AI to understand the full development lifecycle. Value for developers: reduces AI usage barriers, improves efficiency, ensures code quality, and promotes collaboration. Future Directions: Expand support for tools like Cursor/Copilot Chat, domain-specific skills (Web/mobile development), community skill market, and visual orchestration interface.