by VisionForge-OU · Claude Skill · ★ 483
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
A Boris-style agentic orchestrator TUI that supervises headless Claude Code agents through a gated software-delivery pipeline — pointed at any repository.
| Stars | 483 |
| Forks | 96 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 54.4948118848624/100 |
| Open Issues | 12 |
| Last Updated | 2026-06-29 |
| Created | 2026-06-17 |
| Platforms | claude-code, python |
| Est. Tokens | ~13k |
These tools work well together with foreman for enhanced workflows:
Looking for a foreman alternative? If you're comparing foreman with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
AI coding dream team of agents for VS Code. Claude Code + openai Codex collaborate in brainstorm mode, debate
Just a Better Chatbot. Powered by Agent & MCP & Workflows.
Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and wor
Universal Claude Code workflow plugin with agents, skills, hooks, and commands
A Model Context Protocol (MCP) server that enables secure interaction with MySQL databases
A desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Mode
Explore other popular claude skill tools:
foreman is A Boris-style agentic orchestrator TUI that supervises headless Claude Code agents through a gated software-delivery pipeline — pointed at any repository.. It is categorized as a Claude Skill with 483 GitHub stars.
foreman is primarily written in Python. It covers topics such as agent, agent-loop, agent-skills.
You can find installation instructions and usage details in the foreman GitHub repository at github.com/VisionForge-OU/foreman. The project has 483 stars and 96 forks, indicating an active community.
The top alternatives to foreman on Agent Skills Hub include Mysti, better-chatbot, babysitter. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: