EduOrchestrate

Turn any AI coding agent into a daily learning command center.

One command turns a target job role into an adaptive plan, trend-aware research, daily emails, and a skill progression card — running locally inside the agent you already use. Your data, your machine.

Quickstart · Features · Agents · CLI · How it works · FAQ

Why EduOrchestrate?

Most learning tools are SaaS dashboards that collect courses you never finish. EduOrchestrate is the opposite: a vendor-neutral learning coach that lives in your CLI. It turns "I want to become an Agentic AI Engineer" into a concrete daily loop — one core topic, one build artifact, one review — with sourced research and proof of progress.

Job boards use AI to filter candidates. EduOrchestrate gives the learner AI to build a daily, sourced path to the job — one artifact at a time.

•  Role → plan in one command. Pick a target role and a first skill; get an adaptive plan with a fixed 30-day minimum.
•  AI-native & agnostic. The same /eduorchestrate skill works across Claude Code, Codex, Gemini, OpenClaw, Antigravity, Hermas, and any MCP agent.
•  Local-first & private. Learning state stays in data/; SMTP secrets live in .env.local or GitHub Actions — never committed.
•  Zero dependencies. A dependency-free Node CLI. Audit it in an afternoon.
•  Open source, MIT. No account, no paywall, no telemetry.

Quickstart

From an agent terminal in your project:

npx eduorchestrate

That's it. The interactive setup captures your profile (name, email, target role, current topic, first-skill focus, stage, plan length, daily email time, timezone, SMTP), writes the agent adapters, and generates your first 30-day plan.

What it does

	Feature	Description
	Adaptive role plans	Learner-chosen length with a fixed 30-day minimum. One topic, one build artifact, one review loop per day.
	Trend-aware research	Daily digests of dated, sourced updates from official docs, YouTube search, and GitHub sample code — and only reshapes the roadmap when a trend improves employability.
	Daily email delivery	Preview with --dry-run, then send the day's plan over your own SMTP.
	Autonomous runner	A generated GitHub Actions workflow delivers your daily plan hands-free — no browser or agent session needs to stay open.
	Skill progression cards	Prebuilt, GitHub-style SVG terminal cards showing role, skill, momentum, and next action.
	Course source packs	Role-specific official catalogs, free-course discovery links from major vendors, and newsletter feeds.
	Token-conscious harness	Tells the agent what to load first, when to research, and what not to paste into chat.
	Progress & reviews	Evidence logging, weekly summaries, and a recommend-next that suggests your next skill after the plan window.

Built-in role blueprints

Agentic AI & LLM Engineer RAG, evals, agent workflows

Full-Stack Developer Web, cloud, CI/CD

Cybersecurity Analyst SOC, SIEM, cloud security

Data Scientist Data eng, analytics, ML

For other roles, EduOrchestrate infers the closest blueprint and keeps the plan artifact-driven.

Supported agents

The same /eduorchestrate command is honored across runtimes — setup writes the right adapter for each. Where a runtime can't register slash commands, it treats use EduOrchestrate as equivalent to /eduorchestrate.

The CLI

Everything runs from one dependency-free CLI. State writes to data/ and is git-ignored by default.

# Plan
npx eduorchestrate plan --role "Agentic AI and LLM Engineer"
npx eduorchestrate plan --role "Agentic AI and LLM Engineer" --skill "RAG evaluation" --days 45

# Daily loop
npx eduorchestrate harness                     # load the token-conscious harness
npx eduorchestrate courses                      # role-specific course + newsletter packs
npx eduorchestrate research --day 1             # dated, sourced trend digest
npx eduorchestrate send-today --dry-run         # preview the daily email
npx eduorchestrate send-today                   # send for real (your SMTP)
npx eduorchestrate log-progress --day 1 --completed "Built setup" --evidence "Repo link"

# Review & cards
npx eduorchestrate status                       # current role, skill, day, next action
npx eduorchestrate weekly-summary --week 1
npx eduorchestrate progress-card                # GitHub-style skill card (md + json)
npx eduorchestrate terminal-card                # terminal-style SVG card
npx eduorchestrate recommend-next               # next skill after the plan window

# Setup helpers
npx eduorchestrate setup-secrets                # prints `gh secret set` commands for Actions email
npx eduorchestrate doctor                       # verifies skill, adapters, config, env files

How it works

EduOrchestrate models the system as a typed multi-agent workflow — even when a single model executes it:

flowchart LR
    R["Target role<br/>+ stage"] --> GM[GoalMapper]
    GM --> CP[CurriculumPlanner]
    CP --> RS[Researcher]
    RS --> BM[BuildMentor]
    BM --> FC[FocusCoach]
    FC --> EV[Evaluator]
    EV -->|next action| CP

Each day becomes one build action with visible proof — research current references, practice one focused skill, preview or send the email, log evidence, keep the next action visible.

Autonomous daily delivery

EduOrchestrate doesn't need a browser window or an open agent session to deliver. On setup it writes .github/workflows/eduorchestrate-daily.yml, which runs in GitHub Actions at your configured time:

• Runs node bin/eduorchestrate.js send-today on schedule.
• Pulls SMTP credentials from GitHub Actions secrets (setup-secrets prints the exact gh secret set commands).
• Advances the day from schedule.startDate and stops after the plan window instead of repeating the same day forever.

send-today --dry-run is always a safe preview. send-today sends real email. Adapters follow the same resume rule everywhere: on resume, load the harness/status, resolve today's day, and only send after SMTP setup is approved.

Configuration & state

Architecture

src/
├── cli.js                 # dependency-free command router
├── planner.js             # role blueprints + adaptive plan generation
├── adapters.js            # writes per-agent adapter files
├── workflow.js            # GitHub Actions runner generator
├── research.js            # official docs / YouTube / GitHub-sample digests
├── courses.js             # role-specific course + newsletter source packs
├── harness.js             # token-conscious execution harness
├── progress.js            # progress log, status, weekly summaries
├── progression-card.js    # role/skill + terminal card generation
├── card-components.js     # compact SVG component renderer
├── email.js               # SMTP mailer
└── config.js              # config + data-dir resolution
skills/eduorchestrate/     # canonical universal skill + assets + references
tests/node/                # Node regression tests

Development

git clone https://github.com/haroontrailblazer/EduOrchestrate.git
cd EduOrchestrate
npm test            # run the Node regression suite
npx .               # run the CLI locally before publishing

The whole CLI is dependency-free and runs on Node 18+. There is no build step.

FAQ

Yes — MIT-licensed and open source, with zero runtime dependencies. No account, no paywall, no telemetry. The only thing you pay for is whichever AI coding CLI you already use.

Local. Plans, research digests, progress logs, and cards write to data/, which is git-ignored. SMTP credentials live in .env.local or GitHub Actions secrets — never in committed config.

A month is the floor for building real, demonstrable momentum on a job role. You can request a longer plan, but if you ask for fewer than 30 days it still generates 30.

Claude Code, Codex and generic coding agents (AGENTS.md), Gemini, OpenClaw, Antigravity, Hermas, and any MCP-capable agent. See Supported agents.

A generated GitHub Actions workflow runs send-today on schedule using your stored secrets. Run setup-secrets to print the commands that store SMTP credentials as Actions secrets.

Contributing

Contributions are welcome! Whether it's a new role blueprint, an agent adapter, better course sources, or docs — open an issue or PR.

1. Fork & branch from main
2. Keep it dependency-free and add/adjust tests in tests/node/
3. Run npm test
4. Open a PR with a clear description

Star history

License

MIT © EduOrchestrate — your data, your machine.