ai-first-engineering

ai-first-engineering is a skill for Claude Code, Codex from sifxprime/kodelyth-ecc. It costs 21 tokens per session (249 once invoked), scanned A, a copy of ai-first-engineering, MIT.

An engineering process for teams where AI agents produce much of the code. It emphasizes clear plans, measurable checks, explicit system boundaries, and review of real behavior.

In plain words
What is it for?
Use it to design agent-friendly systems, define acceptance checks, review generated changes, and require regression and integration tests.
Why use it?
AI-generated code can appear correct while containing regressions, unsafe assumptions, or data-handling errors.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/sifxprime/kodelyth-ecc/ai-first-engineering
Any agent
npx skills add sifxprime/kodelyth-ecc --skill ai-first-engineering
Clone the repo
git clone --depth 1 https://github.com/sifxprime/kodelyth-ecc

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ai-first-engineering

README.md
[![agentmods](https://agentmods.dev/badge/skills/sifxprime/kodelyth-ecc/ai-first-engineering.svg)](https://agentmods.dev/skills/sifxprime/kodelyth-ecc/ai-first-engineering)
Your own site
<a href="https://agentmods.dev/skills/sifxprime/kodelyth-ecc/ai-first-engineering"><img src="https://agentmods.dev/badge/skills/sifxprime/kodelyth-ecc/ai-first-engineering.svg" alt="Measured on agentmods" height="20"></a>
Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 249 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00021 $0.00249
Opus 5 $0.00010 $0.00125
Sonnet 5 $0.00004 $0.00050
Haiku 4.5 $0.00002 $0.00025

Measured yesterday against content hash 41239a1d15ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-first-engineering scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to ai-first-engineering — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/ai-first-engineering/SKILL.md · 52 lines

What it actually says

AI-First Engineering

Use this skill when designing process, reviews, and architecture for teams shipping with AI-assisted code generation.

Process Shifts

  1. Planning quality matters more than typing speed.
  2. Eval coverage matters more than anecdotal confidence.
  3. Review focus shifts from syntax to system behavior.

Architecture Requirements

Prefer architectures that are agent-friendly:

  • explicit boundaries
  • stable contracts
  • typed interfaces
  • deterministic tests

Avoid implicit behavior spread across hidden conventions.

Code Review in AI-First Teams

Review for:

  • behavior regressions
  • security assumptions
  • data integrity
  • failure handling
  • rollout safety

Minimize time spent on style issues already covered by automation.

Hiring and Evaluation Signals

Strong AI-first engineers:

  • decompose ambiguous work cleanly
  • define measurable acceptance criteria
  • produce high-signal prompts and evals
  • enforce risk controls under delivery pressure

Testing Standard

Raise testing bar for generated code:

  • required regression coverage for touched domains
  • explicit edge-case assertions
  • integration checks for interface boundaries
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 52 lines · 21 tokens per session scan A 41239a1d15ef

Subscribe to this mod's changes

ai-first-engineering is a skill published in the GitHub repository sifxprime/kodelyth-ecc (11 stars, last pushed 3d ago), licensed MIT. It adds 21 tokens to every session and 249 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ai-first-engineering, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

foolproof-product

Use this skill on ANY code change in codevira's product surface (mcpserver/, indexer/). Triggers on Edit/Write to product code, on phrases like "fix bug", "add feature", "handle error", or any modification to commands the end-user runs. Enforces 10 product- reliability principles: no silent failures, atomic state…

sachinshelke/codevira · 124 tokens

open-source-quality

Use this skill before committing, pushing, or opening a PR. Triggers on phrases like "commit", "git commit", "push", "open PR", "create pull request", "finalize this change". Enforces conventional commit messages, atomic commits, code style (ruff/mypy), public-API docstrings, actionable error messages, changelog…

sachinshelke/codevira · 101 tokens

release-readiness

Use this skill whenever the conversation mentions releasing, shipping, publishing, promoting to PyPI, "ship it", "release X.Y.Z", "ready to release", "let's publish", or any phrase suggesting moving codevira to production. Walks the 5-gate release gauntlet (G1-G5) and refuses to proceed without evidence at every gate.…

sachinshelke/codevira · 96 tokens

epistemic-honesty

Use this skill whenever you're about to (1) make a definitive claim like "this works", "tests pass", "ready to ship", "fixed", "done"; or (2) propose a solution to a problem; or (3) diagnose a bug or issue. Forces explicit confidence calibration with inline evidence, surfaces what you don't know, and demands a…

sachinshelke/codevira · 106 tokens

development-discipline

Use this skill before ANY code-writing tool call (Edit, Write, NotebookEdit) on this project. Triggers on phrases like "implement", "fix bug", "add feature", "refactor", "create function", "modify file", or whenever the user asks for a code change. Forces a 4-step CONTEXT → PURPOSE → REASON → CODE sequence with…

sachinshelke/codevira · 129 tokens

practical-coding

Use for implementing, fixing, refactoring, or reviewing code with the smallest correct change; routes only unresolved debugging, architecture/choice, or risk-boundary blockers, while code retrieval uses the cheapest sufficient available capability.

Hubujiu/practical-coding · 48 tokens