BrainForge AI gives you GSD-like workflow discipline, but simplified for students, juniors, and developers who need to understand and defend their code.
Whether you are writing a school project, working as a junior developer, or building a personal app — BrainForge keeps your AI tool focused, structured, and produces code you can explain.
BrainForge AI is a CLI that installs a structured workflow into any project directory. It gives your AI coding tool (Claude, Cursor, Copilot, Gemini, Codex…) everything it needs to plan before coding, respect your level, and stay focused on one task at a time.
It is not a clone of GSD. GSD is powerful and professional. BrainForge AI takes the same workflow discipline and applies it for students, juniors, and builders who need to understand and explain every line.
BrainForge AI = GSD-level discipline + student control + professor check + oral defense prep − the complexity
AI tools often cause the same recurring problems:
BrainForge solves this with a simple workflow: discuss → map → plan → build → verify → professor-check → defend.
| GSD | BrainForge AI | |
|---|---|---|
| Target audience | Professional teams | Students, juniors, solo builders |
| Setup complexity | Advanced | Simple — one init command |
| Code level control | Not the focus | Core feature — enforced at every step |
| Academic integrity check | No | Yes — professor-check and defend |
| Oral defense prep | No | Yes — defend generates DEFENSE.md |
| Agent infrastructure | Heavy | Minimal — slash commands + prompt templates |
| State files | Rich structured system | Simple Markdown files |
| Learning curve | Steep | Gentle |
npx brainforge-ai init
npm install -g brainforge-ai
brainforge init
brainforge-aiis the npm package name.brainforgeis the CLI command.
Requirements: Node.js >= 16
npx brainforge-ai init
brainforge discuss
brainforge map
brainforge plan "add authentication"
brainforge build
brainforge verify
brainforge professor-check
brainforge defend
brainforge dashboard
This is the main workflow for academic projects.
# 1. Initialize BrainForge
brainforge init
# 2. Answer questions about your project and professor requirements
brainforge discuss
# 3. Scan your existing codebase (if you have one)
brainforge map
# 4. Plan a specific task
brainforge plan "add appointment management"
# 5. Get a ready-to-paste coding prompt for your AI tool
brainforge build
# → Paste the prompt into Claude, Cursor, Gemini, etc.
# → Implement the task
# → Come back to BrainForge when done
# 6. Check the implementation
brainforge verify
# 7. Run a professor-style review
brainforge professor-check
# 8. Prepare your oral defense
brainforge defend
# 9. Open the dashboard to see your project status
brainforge dashboard
If you are adding BrainForge to a project that already has code:
# 1. Initialize BrainForge (non-destructive, will not touch your code)
brainforge init
# 2. Set up your project context
brainforge discuss
# 3. Scan the codebase and generate CODEBASE_MAP.md
brainforge map
# 4. Plan your next task
brainforge plan "refactor the user module"
# 5. Get the coding prompt and paste into your AI tool
brainforge build
# 6. Verify the changes
brainforge verify
| Command | Description |
|---|---|
init |
Initialize BrainForge — creates all workflow files and directories |
discuss |
Answer questions to set up project context (PROJECT.md, STUDENT_LEVEL.md, PROFESSOR_RULES.md, STATE.md) |
map |
Scan and map the codebase — generates CODEBASE_MAP.md and a /map-project AI prompt |
plan <task> |
Create a focused implementation plan. Reads real file paths from CODEBASE_MAP.md first, uses semantic aliases (login→auth, register→user) before falling back to generic suggestions |
build |
Generate a ready-to-paste coding prompt from the current task plan |
verify |
Check your implementation: imports, complexity, violations, and undeclared package deps. Outputs SAFE_TO_CONTINUE, REVIEW_BEFORE_SUBMISSION, or MUST_FIX_BEFORE_SUBMISSION |
professor-check |
Scan the codebase locally for advanced patterns (language-specific: Python, Java, PHP, Ruby, C#), suspicious style, large files. Writes .brainforge/PROFESSOR_CHECK.md |
defend |
Generate an oral defense pack (DEFENSE.md) with questions, answers, and a checklist |
dashboard |
Open the interactive project dashboard in the browser |
serve |
Start a live dashboard server with auto-reload on localhost:3000 |
status |
Show a compact summary of the current project state |
study |
Initialize Study Mode files for understanding the project |
difficulty |
Generate a difficulty analysis workflow |
defense-pack |
Generate a full oral defense preparation workflow (extended version) |
simplify |
Generate a prompt to simplify code to match the project level |
doctor |
Check BrainForge health and project status |
update |
Update agents, commands, and templates without touching your data |
guide |
Show all CLI and slash commands with project status |
When you run brainforge init, BrainForge creates:
my-project/
.brainforge/
PROJECT.md ← project name, type, stack, features, constraints
STATE.md ← current phase, task, last verification, next action
STUDENT_LEVEL.md ← selected code level, rules, forbidden complexity
PROFESSOR_RULES.md ← what professor/client asked, allowed/forbidden tech
CURRENT_TASK.md ← goal, plan, what not to do (updated by brainforge plan)
CODEBASE_MAP.md ← codebase scan output (updated by brainforge map)
VERIFY_REPORT.md ← verification results (updated by brainforge verify)
DEFENSE.md ← oral defense pack (updated by brainforge defend)
CHECKPOINTS/ ← checkpoint artifacts
PROMPTS/ ← generated AI coding prompts
brain.md ← master context file for AI tools
project.md ← project spec (legacy format)
roadmap.md ← phase roadmap
memory/ ← architecture, coding style, bugs, glossary…
phases/ ← phase files
agents/ ← AI agent instruction files
commands/ ← slash command templates
dashboard/ ← local HTML dashboard files
reports/ ← generated reports
.claude/
skills/ ← 95+ expert skill files for Claude Code
AGENTS.md
CLAUDE.md
GEMINI.md
OPENAI.md
| File | Written by | Purpose |
|---|---|---|
PROJECT.md |
init, discuss |
Project name, type, stack, features, status |
STATE.md |
init, discuss, verify |
Current phase, task, next action |
STUDENT_LEVEL.md |
init, discuss |
Code level rules, forbidden patterns |
PROFESSOR_RULES.md |
init, discuss |
Professor/client requirements and constraints |
CODEBASE_MAP.md |
map |
Scanned structure, entry points, models, routes |
CURRENT_TASK.md |
plan |
Task goal, implementation plan, what not to do |
PROMPTS/build-current-task.md |
plan, build |
Ready-to-paste AI coding prompt |
VERIFY_REPORT.md |
verify |
Errors, warnings, violations, final recommendation |
PROFESSOR_CHECK.md |
professor-check |
Local scan report: risk level, score, suspicious patterns |
DEFENSE.md |
defend |
Defense pack, questions, answers, checklist |
PROMPTS/defend.md |
defend |
AI prompt for a richer file-by-file defense pack |
BrainForge v2 uses these files as the primary source of truth:
.brainforge/
PROJECT.md ← project context
STATE.md ← current phase, task, last verification, next action
STUDENT_LEVEL.md ← code level rules
PROFESSOR_RULES.md ← professor/client constraints
CURRENT_TASK.md ← active task plan (updated by brainforge plan)
CODEBASE_MAP.md ← scanned file tree (updated by brainforge map)
VERIFY_REPORT.md ← verification results (updated by brainforge verify)
PROFESSOR_CHECK.md ← local scan report (updated by brainforge professor-check)
DEFENSE.md ← oral defense pack (updated by brainforge defend)
PROMPTS/ ← generated AI coding prompts
Legacy folders are kept for compatibility with older BrainForge workflows and AI tool prompts:
brain.md, project.md, roadmap.md ← legacy context files
memory/ ← legacy memory files
phases/ ← legacy phase files
agents/ ← AI agent instruction files
commands/ ← slash command templates
reports/ ← legacy report files
New commands write to v2 files. Legacy files are not deleted or modified by v2 commands.
Scenario: second-year university project, Spring Boot + MySQL, oral defense in two weeks.
brainforge init
brainforge discuss
# → Project type: Academic
# → Stack: Java, Spring Boot, MySQL
# → Code level: academic-realistic
# → Comments: French
# → Professor asked: REST API with authentication, MVC pattern required
# → Forbidden: Spring Security (too advanced)
# → Report required: Yes
# → Oral defense: Yes
brainforge map
# → Scans the project, generates CODEBASE_MAP.md with MVC structure detected
brainforge plan "add patient management CRUD"
# → Detects likely files: PatientController, PatientService, Patient.java
# → Writes CURRENT_TASK.md with MVC implementation steps
brainforge build
# → Outputs prompt that tells the AI to respect the academic-realistic level,
# add French comments, stay in MVC, and not rewrite unrelated files
# → Paste the prompt into Claude or Cursor → implement the feature
brainforge verify
# → Checks for broken imports, enterprise patterns (Singleton, Factory, DI containers),
# forbidden technologies, large files
brainforge professor-check
# → Generates audit prompt: checks for AI-generated style, too-perfect code,
# enterprise patterns a second-year student cannot justify
brainforge defend
# → Generates DEFENSE.md with Spring MVC explanation, possible questions
# ("What is a controller?", "Why did you use a service layer?"),
# simple answers, weak points, and a last-minute checklist
Scenario: Python web dev course, Django + SQLite, grade depends on oral questions.
brainforge init
brainforge discuss
# → Project type: Academic
# → Stack: Python, Django
# → Code level: beginner
# → Comments: French
# → Professor asked: CRUD web app with Django views and templates
# → Forbidden: Django REST Framework (not covered in course)
brainforge plan "add product catalog page"
# → Implementation plan: Model → View → Template → URL config
# → Warns not to use class-based views if declarerd beginner level
brainforge build
# → Prompt tells AI to use function-based views, Django ORM,
# add French comments, keep templates simple
brainforge verify
# → Flags any import that does not resolve, any use of DRF or advanced patterns
brainforge defend
# → Generates Django-specific explanation: MTV architecture,
# how models map to database tables, what a view does,
# possible professor questions about ORM, template tags, migrations
Scenario: building a side project with Node.js and React, intermediate level.
brainforge init
brainforge discuss
# → Project type: Personal
# → Stack: Node.js, Express, React, PostgreSQL
# → Code level: intermediate
# → No professor constraints
brainforge map
brainforge plan "add user authentication with JWT"
brainforge build
# → Paste prompt into Cursor or Claude Code
# → Implement authentication
brainforge verify
# → Checks auth route imports, flags suspiciously enterprise-level patterns,
# counts TODO markers
brainforge dashboard
# → Visual overview of project state, phase progress, recent commits
BrainForge generates context files and prompts that work with any AI coding tool:
BrainForge installs 95+ expert skill files to .claude/skills/ for Claude Code users. These guide AI behavior for specific stacks, frameworks, and tasks.
.brainforge/ structure)discuss — interactive project context setupplan — focused task planning with CURRENT_TASK.mdbuild — paste-ready AI coding prompt generationverify — import checking, complexity detection, student-level validationdefend — oral defense pack with stack-aware questions and answersCODEBASE_MAP.md — enriched map with entry points, models, routesprofessor-check — real local codebase scan (no AI needed for the scan)verify — SAFE_TO_CONTINUE / REVIEW_BEFORE_SUBMISSION / MUST_FIX recommendationplan — uses real files from CODEBASE_MAP.md before falling back to generic suggestionsplan — semantic aliases (login→auth, register→user, payment→billing, refresh→jwt…)professor-check — language-specific pattern detection (Python metaclasses, Java Spring, PHP traits, Ruby metaprogramming, C# async/LINQ)verify — undeclared package import check against package.jsondata.json for offline file:// viewingbrainforge check-imports — stricter cross-file import resolutionMIT — see LICENSE.