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Generic-GenAI-Setup

A portable, language-agnostic, IDE-agnostic framework for making an AI coding agent behave like a disciplined engineer on any codebase.

It is not a prompt. It is a rule set, a process with hard caps, an artefact template for every step, a failure taxonomy with remediation playbooks, and a setup protocol that adapts all of it to whatever project and IDE it lands in.

Activate with super_saiyan_bann_jo
Anchor file MAIN.md — attach this to the chat
Payload .ai/ — copied into the target project at activation
Dependencies none. Plain Markdown and one YAML config. No runtime, no package, no API key

Why this exists

An AI agent on a large codebase fails in predictable ways: it claims a file contains something it never opened, it drifts from the original objective halfway through a long session, it retries the same broken command four times, it declares a task done with three follow-ups open, it deletes something "impact-free" that a live page depended on.

None of those are fixed by a better prompt. They are fixed by structure: an externalised state machine so completion is not held in context, a grounding rule so a search hit is never mistaken for a fact, hard round caps so planning cannot expand to fill the budget, and a classification step so a bug fix never enters the machinery built for new features.

This framework is that structure, extracted from a codebase where it was built incrementally in response to real defects, and generalised so it drops into anything.

Quickstart

In a new project, with an AI assistant that has file access:

super_saiyan_bann_jo

…and attach MAIN.md, or point the assistant at ~/Documents/Generic-GenAI-Setup/.

The assistant then runs .ai/setup/activation-protocol.md: it inspects the project, discovers how your IDE loads persistent instructions, copies .ai/ in, generates the project-specific rule layer, writes an IDE adapter, builds the index, proves fourteen behaviour checks, and runs a 69-row install audit before reporting done.

Then, to start work:

Track B. Add pagination to the customer list endpoint.

The assistant pulls in the Track B steering, fills the enhancement raw-requirement template, grounds itself with file-verified pointers, builds a do-not-break.md register, and proceeds through the capped stages.

What activation produces in your project

<your project>/
├── .ai/                          the framework payload, plus:
│   ├── config.yml                your gate commands, paths, stack profile, IDE adapter
│   ├── INDEX.md                  the central index, regenerated for your project
│   ├── rules/project/            product.md · structure.md · tech.md · conventions · design · api · data
│   └── work/                     artefacts: <slug>/** per feature, hotfixes/<slug>/** per bug
└── <IDE adapter>                 e.g. AGENTS.md, .cursor/rules/*.mdc, CLAUDE.md, .kiro/steering/*

Nothing else in your repository is touched. Source code, build config and CI are left alone unless the work you subsequently ask for changes them.

The shape of the process

        ┌──────────────┐
        │ work intake  │  classify: A / B / C / T
        └──────┬───────┘
               │
   ┌───────────┼───────────┬──────────────┐
   ▼           ▼           ▼              ▼
Track A     Track B     Track C        Track T
new         change to   reproducible   copy, token,
capability  a shipped   defect         constant
            feature
   │           │           │              │
   │           │           │              └─ state → change → gates → one-line report
   │           │           │
   │           │           └─ reproduce → written root cause → blast radius → minimal
   │           │              fix → fails-before/passes-after test → gates → harden
   │           │
   │           └─ + do-not-break register + regression sweep, caps 2/2/1
   │
   └─ frame → ground → pin → gaps (≤3) → requirement → design → design review (≤3)
      → tasks → tasks review (≤2) → execute per section → cutover → close out

Every arrow above has an artefact template. Every stage has a hard cap. Every claim inside those artefacts carries a file:line pointer marked read-and-verified.

Core guarantees

Guarantee Mechanism
Work is classified before it starts 80-work-intake.md
A pointer is never treated as evidence grounding rule in 60-workflow-and-verification.md
Four gates define done, with real output 60-workflow-and-verification.md + config.yml
Planning cannot expand indefinitely hard round caps in each track file
Irreversible actions stop and ask 00-agent-contract.md + cutover step
Failures are named, not improvised around 05-failure-detection.md84-failure-playbooks.md
Documentation self-heals during work 65-auto-healing-docs.md
Nothing ships on one look 62-3x-verification.md
The process is actually followed preflight block in 01-session-preflight.md — no file edit before it
Setup is provably installed 14 behaviour checks in .ai/manifest.md
Install gaps are found, not discovered later 69-row audit in install-audit.md

Language and IDE independence

Language. The framework never names a language. The four gates are roles, not commands: LINT, STATIC/TYPE, BUILD, TEST. .ai/setup/stack-profiles.md maps those roles onto concrete commands for JavaScript/TypeScript, Python, Java/Kotlin, Go, Rust, C#/.NET, PHP, Ruby, Swift, C/C++ and Elixir, and tells you how to add a profile for anything missing. The chosen mapping is recorded once, in .ai/config.yml.

IDE. Rule loading is abstracted into four modes — ALWAYS, AUTO, ON-DEMAND, FILE-MATCH — each with a defined fallback for IDEs that cannot do it. .ai/adapters/ide-matrix.md covers the known conventions; .ai/adapters/AGENTS.template.md is the universal fallback that most assistants read natively. Adapters reference the rule files; they never copy them.

Repository map

Path Contents
MAIN.md activation anchor, the eleven non-negotiables, the S0S9 summary
.ai/ the portable payload — see .ai/INDEX.md
docs/rationale.md why each rule exists, with the failure that produced it
docs/CHANGELOG.md framework version history

Maintaining the framework itself

The framework is versioned in docs/CHANGELOG.md, and every installation records the version it was installed from in .ai/config.yml. Improving a rule means editing it here, bumping the version, and noting in the changelog whether existing installations need to re-sync.

Universal rules (.ai/rules/0095) are copied verbatim into projects and never edited in place — that is what makes a re-sync safe. Project-specific content goes in .ai/rules/project/, which the framework never overwrites after generation.

Generic-GenAI-Setup

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