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agentic-skills

Automate AI agent development governance with slash-command workflows across multiple coding platforms.

40|9|Updated Jan 4, 2026
Search Tags:#tdd#spec-driven#ci-cd#ai-agent#code-review#workflow-orchestration#security-hardening
One-click install
npx skills add https://github.com/akillness/jeo-skills --skill agentic-skills-akillness
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentic-skills
Source: https://github.com/akillness/jeo-skills/tree/main/.agent-skills/agentic-skills
Command: npx skills add https://github.com/akillness/jeo-skills --skill agentic-skills-akillness

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Production-grade software engineering framework that encodes Google-proven workflows, quality gates, and best practices for AI coding agents. Use when you need structured development lifecycle guidance: spec-driven development, incremental implementation, test-driven development, security hardening, performance optimization, or disciplined git/CI/CD workflows.

Core Features & Use Cases

  • Spec-driven development and slash-command guided workflows ( /spec, /plan, /build, /test, /review, /code-simplify, /ship) to manage AI agent projects.
  • End-to-end governance for production AI agents, including risk gating, verification, and CI/CD integration.
  • Multi-LLM platform compatibility (Claude Code, Gemini CLI, Codex CLI, Cursor, Windsurf, OpenCode) to enable cross-platform workflows.
  • Guardrails and best-practices inspired by Google engineering culture (trunk-based development, TDD, shift-left testing, and code-as-liability mindset).
  • Clear collaboration roles and artifact ownership across spec authors, planners, builders, testers, and reviewers.

Quick Start

Start by defining a spec with /spec, then progressively plan, build, test, review, and ship.

Frequently Asked Questions about agentic-skills

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement spec-driven development for AI coding agents?▼

Spec-driven development for AI coding agents is implemented by defining requirements with /spec, then progressively executing /plan, /build, /test, /review, and /ship workflows to enforce production engineering governance.

Can I use this AI agent workflow framework with Cursor and Gemini CLI?▼

Yes, this AI agent workflow framework supports multi-LLM platform compatibility across Claude Code, Gemini CLI, Codex CLI, Cursor, Windsurf, and OpenCode to enable cross-platform development workflows.

What is the best way to enforce test-driven development and CI/CD workflows for AI agents?▼

The best way to enforce test-driven development and CI/CD workflows for AI agents is applying slash-command guided workflows like /test and /ship, incorporating risk gating and shift-left testing best practices.

Does this framework support security hardening and code review for AI agent projects?▼

Yes, security hardening and code review are supported for AI agent projects through dedicated /review and /code-simplify workflows, applying Google-inspired guardrails and a code-as-liability mindset.

How do I manage collaboration roles and artifact ownership in AI agent development?▼

Collaboration roles and artifact ownership in AI agent development are managed by defining clear responsibilities across spec authors, planners, builders, testers, and reviewers throughout the lifecycle.

What are the limitations of using slash commands for incremental implementation in AI agents?▼

Incremental implementation via slash commands requires strict adherence to trunk-based development and structured workflows, meaning teams must follow the /spec to /ship sequence without skipping quality gates.

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