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Agent First Engineering

mcp-codyamaughan-agent-first-engineering · by CodyAMaughan

A curriculum + an agent-agnostic scaffolder for agent-first software engineering: design your codebase so AI coding agents (Claude Code, Codex, Cursor) succeed.

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Install

$ agentstack add mcp-codyamaughan-agent-first-engineering

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No 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.

View the full security report →

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Reliability & compatibility

Security review passed
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1mo ago

Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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 →
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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:

  1. Open Standards FirstAGENTS.md + SKILL.md are the source of truth; vendor formats

are optional adapters.

  1. Agent-Agnostic by Construction — author once, render per-agent. Claude Code is the

reference, not the requirement.

  1. Teach and Generate in Lockstep — A and B stay in sync, by rule.
  2. Guardrails Over Vibes — correctness is enforced by hooks/tests/CI, not prose.
  3. Minimal Context, Progressive Disclosure — short, command-first, machine-parseable.
  4. Adopt, Don't Reinvent — build alongside mature, permissive tools (esp. GitHub

Spec Kit), don't fork them.

  1. 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.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.