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Agent skill

AI First Engineering

by affaan-m in affaan-m/ECC

Engineering operating model for teams where AI agents generate a large share of implementation output.

MITAuto-check passedAgent Workflows

Install AI First Engineering

skills CLI
$ npx skills add affaan-m/ECC --skill ai-first-engineering -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC ai-first-engineering --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-first-engineering .claude/skills/ai-first-engineering && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ai-first-engineering
GitHub stars
277k
Used in
4 other repos
Token cost
~364 tokens
SKILL.md length
142 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

Engineering operating model for teams where AI agents generate a large share of implementation output.

  • Works in 3 steps: Planning quality matters more than… → Eval coverage matters more than… → Review focus shifts from syntax to…
  • Setting team process
  • SKILL.md covers Process Shifts, Architecture Requirements, Code Review in AI-First Teams and Hiring and Evaluation Signals, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

AI First Engineering is an agent skill from affaan-m/ECC. Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

Its SKILL.md is about 360 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Human-in-the-loop approvals. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • Setting team process
  • Ownership rules for a codebase largely written by agents

Example prompts

  • “/ai-first-engineering”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

AI First Engineering loads about 364 tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 142 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~364

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 142 words, ~364 tokens.

Download SKILL.mdSave it as .claude/skills/ai-first-engineering/SKILL.md (or your agent's skills folder).
name
ai-first-engineering
description
Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.
metadata.origin
ECC

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

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/ai-first-engineering of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 4 other repositories

We found 10 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

AI First Engineering next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

AI First Engineering compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
AI First Engineering this skillaffaan-m/ECC277k4 repos~364Automated safety check: PassMIT
Show Me Your Work Decision Logcursor/plugins11k8 repos~1.6kAutomated safety check: PassNone
Darwin Skill Optimizeralchaincyf/darwin-skill6.2k1 repos~4.7kAutomated safety check: PassMIT
Loop Constraints Enforcercobusgreyling/loop-engineering11k1 repos~475Automated safety check: NotesMIT
Ask User QuestionMemTensor/MemOS12k—~1kAutomated safety check: PassApache-2.0
PUA High-Agency Governancetanweai/pua20k—~502Automated safety check: PassMIT

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Categories

Questions about AI First Engineering

What does AI First Engineering do?

Engineering operating model for teams where AI agents generate a large share of implementation output. AI First Engineering is an agent skill from affaan-m/ECC. Engineering operating model for teams where AI agents generate a large share of implementation output.

When should I use AI First Engineering?

AI First Engineering fits situations like: setting team process; ownership rules for a codebase largely written by agents.

How do I install AI First Engineering in Claude Code?

Run `npx skills add affaan-m/ECC --skill ai-first-engineering -a claude-code`. Or copy the skill folder (skills/ai-first-engineering in affaan-m/ECC) into .claude/skills/ai-first-engineering in your project. Claude Code loads it when a task matches its description.

How do I install AI First Engineering in Codex?

Run `npx skills add affaan-m/ECC --skill ai-first-engineering -a codex`. Or copy the skill folder (skills/ai-first-engineering in affaan-m/ECC) into .agents/skills/ai-first-engineering in your project. Codex loads it when a task matches its description.

Can I use AI First Engineering in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill ai-first-engineering -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-first-engineering, .gemini/skills/ai-first-engineering, .github/skills/ai-first-engineering and .opencode/skills/ai-first-engineering in your project.

What does AI First Engineering need to run?

SKILL.md names no scripts, command-line tools or credentials: AI First Engineering is instructions for the agent only.

Does AI First Engineering access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is AI First Engineering safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does AI First Engineering use?

AI First Engineering is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does AI First Engineering use?

About 364 tokens (SKILL.md is roughly 1.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to AI First Engineering?

Skills that share tags, products or a category with AI First Engineering: Show Me Your Work Decision Log (cursor/plugins, 11k stars), Darwin Skill Optimizer (alchaincyf/darwin-skill, 6.2k stars), Loop Constraints Enforcer (cobusgreyling/loop-engineering, 11k stars) and Ask User Question (MemTensor/MemOS, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains AI First Engineering?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.