Install
$ agentstack add mcp-codyamaughan-agent-first-engineering ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
> Stop coding with AI agents "loosey-goosey." Design your codebase so agents succeed — > the way a systems engineer would.
> 📖 Read it online → codyamaughan.github.io/agent-first-engineering
This repository has two deliverables that are two views of one body of knowledge:
- A — The Curriculum (
specs/001-curriculum/) — a phased, visual course that takes you
from informal "vibe coding" to designing agent-first codebases. Modeled structurally on the well-organized [AI Engineering from Scratch] approach: one concept at a time, diagrams, ELI5, a real artifact at the end of every lesson.
- B — The Scaffolder (
specs/002-scaffolder/) — an agent-agnostic,SKILL.md-first
tool that interviews you about a project, then generates a proper agent-first setup: AGENTS.md, a SKILL.md library, and lifecycle-hook guardrails — wired to work across Claude Code, Codex, and Cursor (more agents via adapters). Think create-react-app for agent-first repos, but a conversation instead of a fixed form, and it runs inside your agent. Modes: init (new repo), adopt (clean up an existing one).
Teach and generate in lockstep: every layer the curriculum teaches, the scaffolder generates; every artifact the scaffolder generates, the curriculum explains.
Who this is for
- Developers already using AI agents who want to level up from "vibe coding" to designing repos
where agents succeed by default.
- Tech leads deciding how their team should adopt AI coding tools.
It assumes you've used an AI coding agent before. It is not an intro-to-AI course.
What you'll get
- A 6-phase course (read it free at the site)
— from prompting and context engineering through verification, memory, spec-driven development, and harness engineering.
- A scaffolder that interviews you and sets up a new (or existing) repo to be agent-ready —
AGENTS.md, a skills library, and guardrail hooks — for Claude Code, Codex, and Cursor.
Principles
The project is governed by its [Constitution](.specify/memory/constitution.md). In brief:
- Open Standards First —
AGENTS.md+SKILL.mdare the source of truth; vendor formats
are optional adapters.
- Agent-Agnostic by Construction — author once, render per-agent. Claude Code is the
reference, not the requirement.
- Teach and Generate in Lockstep — A and B stay in sync, by rule.
- Guardrails Over Vibes — correctness is enforced by hooks/tests/CI, not prose.
- Minimal Context, Progressive Disclosure — short, command-first, machine-parseable.
- Adopt, Don't Reinvent — build alongside mature, permissive tools (esp. GitHub
Spec Kit), don't fork them.
- Specs Are the Source of Truth — spec → plan → tasks → implement.
What we build on (all permissive, all current)
| Layer | Adopted standard / tool | License | |---|---|---| | Context file | AGENTS.md | Open standard | | Reusable skills | Agent Skills / SKILL.md | Apache-2.0 | | Spec workflow | GitHub Spec Kit (complement, not fork) | MIT | | Principles | 12-factor-agents | Apache-2.0 |
See [meta/prior-art.md](meta/prior-art.md) for the full landscape and why this project's niche is currently unfilled.
The Curriculum
Six phases, from vibe coding to systems engineer for agents. Full index in [docs/curriculum/](docs/curriculum/index.md). Quiz yourself with /check-understanding (the [check-understanding](.agents/skills/check-understanding/SKILL.md) skill generates an interactive quiz from each phase's lessons).
| # | Phase | # | Phase | |---|---|---|---| | 1 | [Fundamentals](docs/curriculum/01-fundamentals/index.md) | 4 | [Session & Memory](docs/curriculum/04-session-and-memory/index.md) | | 2 | [Context Engineering](docs/curriculum/02-context-engineering/index.md) ★★★ | 5 | [Spec-Driven Development](docs/curriculum/05-spec-driven-development/index.md) | | 3 | [Verification & TDD](docs/curriculum/03-verification-and-tdd/index.md) ★★★ | 6 | [Orchestration & Harness](docs/curriculum/06-orchestration-and-harness/index.md) |
Project status
Early and active. The foundations tier is complete and published; the Advanced Patterns tier is on the [Roadmap](docs/roadmap.md). Built (and dogfooded) using GitHub Spec Kit.
Repo internals (for contributors)
- [
docs/translation-matrix.md](docs/translation-matrix.md) — Claude→Codex→Cursor feature research - [
.specify/memory/constitution.md](.specify/memory/constitution.md) — governing principles - [
specs/](specs/) — Spec Kit specs/plan/tasks for the curriculum (A) and scaffolder (B) - [
meta/](meta/) — executive summary, prior-art, curriculum outline, and the authoring rubric
FAQ
Do I need Claude Code?
No. It's agent-agnostic — Claude Code is the reference implementation, not a requirement. Lessons show the open-standard form plus Codex and Cursor equivalents.
Is it free?
Yes — MIT-licensed and open source.
Did you write all of this yourself?
No, and I'm upfront about it: it's a curation and synthesis of the best blogs, posts, and documentation from the top AI labs, their contributors, and other thought leaders — cited throughout. It was drafted primarily with AI (fitting, given the topic) and reviewed by me. What's mine is the direction, the structure, and the review.
Curriculum vs. scaffolder — what's the difference?
The curriculum teaches the practice; the scaffolder generates it. Each lesson ends by showing what the scaffolder produces.
How can I help?
See [Contributing](#contributing) — fixes, diagrams, better sources, and new topics from the [Roadmap](docs/roadmap.md) are all welcome.
Contributing
Contributions are welcome — fix a lesson, add a diagram, propose a topic from the [Roadmap](docs/roadmap.md), or improve the scaffolder. Start with [CONTRIBUTING.md](CONTRIBUTING.md) and our [Code of Conduct](CODEOFCONDUCT.md).
License
[MIT](LICENSE) © 2026 CodyAMaughan. Redistributed dependencies are MIT / Apache-2.0 / BSD.
[AI Engineering from Scratch]: https://github.com/rohitg00/ai-engineering-from-scratch
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: CodyAMaughan
- Source: CodyAMaughan/agent-first-engineering
- License: MIT
- Homepage: https://codyamaughan.github.io/agent-first-engineering/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.