ai-driven-development
CodeAlive-AI · CodeAlive-AI/ai-driven-development
Offers a collection of 23 agent skills and safety hooks for AI-driven software development across multiple coding agents.
Practices, protocols, and skills for AI-driven software development. Skills and safety hooks for Claude Code, Codex, OpenCode, Cursor, Antigravity, and any agent supporting the Agent Skills standard.
Preview
What you can do with it
- Enhance your agent's ability to reflect and configure itself.
- Apply best practices for AI-driven development directly in your agent.
- Implement safety protocols and bash guards for agent execution.
Safety check
Usable, but read the notes first.
- ●Installer downloads a remote script and pipes it to the shell.
README.md
Automated scan of the repo files. Always review code you run.
From the README
AI-Driven Development
Practices, protocols, and skills for AI-driven software development
An umbrella collection of 23 skills + 1 hook that work across Claude Code, Codex CLI, OpenCode, Cursor, Gemini CLI, Antigravity, and any other agent that supports the Agent Skills standard.
Related Projects
- Apple App Store Reviewer — moved to Vibe Stack in full; install this skill from
CodeAlive-AI/vibe-stack. - Vibe Stack — an opinionated AI-native development stack with one verified default per layer, covering web apps, agent apps, deployment, persistence, error tracking, and observability.
Installation
Via Skills CLI (recommended — works in 12+ agents):
# Install all 23 skills
npx skills add CodeAlive-AI/ai-driven-development
# Or pick a single skill
npx skills add CodeAlive-AI/ai-driven-development --skill prompt-engineering
Via Claude Code plugin marketplace:
/plugin marketplace add CodeAlive-AI/ai-driven-development
/plugin install ai-driven-development@ai-driven-development
# Restart Claude Code for changes to take effect
The Bash safety hook (bash-guard) ships separately — see hooks/balanced-safety-hooks/ for its install one-liner.
What's Included
Agent reflection & meta (7)
Meta-skills that let AI coding agents configure themselves. No more editing config files — just tell your agent what you need.
| Skill | What It Does |
|---|---|
| mcp-management | Install and manage MCP servers across 10+ coding agents (Claude Code, Cursor, VS Code, Gemini CLI, Codex, Goose, Copilot CLI, OpenCode, Zed, Devin) — single command, handles JSON/YAML/TOML config differences |
| hooks-management | Manage hooks and automation for Claude Code, Codex CLI, OpenCode, and Devin CLI/Desktop |
| settings-management | Configure settings for Claude Code (JSON), Codex CLI (TOML), OpenCode (JSON/JSONC), and Devin CLI/Desktop (JSON) |
| skills-management | Organise, discover, share, and train skills for coding agents — SkillOpt-style optimisation loop with bounded edits, held-out validation gate, rejected-edit buffer, epoch-wise slow/meta update, plus trigger / transfer / diff / edit-log tooling |
| plugins-management | Package and publish plugins for Claude Code, OpenCode, and Devin CLI/Desktop (validate, scaffold, submit to Anthropic's directory) |
| agentic-readiness | Audit and improve repositories for Codex/Codex App, Claude Code, and OpenCode, including AGENTS.md/CLAUDE.md discovery and routing |
| installing-cli-tools | Install, upgrade, authenticate, verify, and roll back developer CLIs while keeping tokens and API keys out of chat, logs, shell history, startup files, and repositories |
Engineering practices (8)
Disciplined approaches that improve how agents and humans collaborate on code.
| Skill | What It Does |
|---|---|
| code-that-fits-in-your-head | Keep agent-authored systems understandable and maintainable by resisting accidental complexity, Big Balls of Mud, and technical-debt accumulation. Supports large changes when architecture, acceptance criteria, verification, and recovery are explicit; uses structural heuristics without universal formatting or task-size limits |
| prompt-engineering | Universal prompt-engineering toolkit. 14 reference docs covering Claude / GPT / Gemini family-specific guidance, prompting techniques, evaluation & red-teaming, common failure modes (hallucinations, security, structure, debt) |
| fpf-problem-solving | First Principles Framework — a transdisciplinary "operating system for thought". Decompose cross-domain problems, audit conclusions, and reason rigorously about complex systems. Based on Anatoly Levenchuk's FPF |
| bug-fix-protocol | 8-step bug-fix protocol. Treats every production bug as two failures (the code defect + the testing system that allowed it through) and enforces a step-8 audit that closes the gap |
| plan-mode | Planning gate for any project change. Investigate context → analyse the task → surface ambiguities, contradictions, risks, and blockers → ask focused questions → produce an evidence-based, step-by-step plan → implement only after explicit approval, then validate. Compact always-on SKILL.md + full PROTOCOL.md |
| investigating-repository-history | Reconstruct historical intent before risky edits. Local git blame/log + GitHub PR/review evidence (via gh, never direct API), with squash/rebase/cherry-pick/rename/revert anomaly handling, decision-atom extraction, and confidence-scored output — produces a cited history note instead of guessing |
| refactoring-csharp | One-shot Roslyn contract for renaming C# symbols from file + 1-based line + oldName, with dry-run preview, safe file moves for supported named types, and explicit error codes |
| repo-activity-summary | Summarize what a repository has been doing from local git log — technologies, work types, churn hotspots, contributor patterns, velocity, and health signals. Stdlib-only Python, no network or API keys. Benchmarked at −42% cost / −37% wall clock versus the same agent answering the same question unaided, at equal factual accuracy; flags its own low-confidence classification instead of asserting it |
AI infrastructure (1)
| Skill | What It Does |
|---|