Super Board

Community

EricTechPro

super-board

GitHub-Project-driven autonomous pipeline. Five verbs — onboard, lint, status, run, stop — that take a Project board from empty to drained across Build → QA → Review → Done lanes (labels qa · bug · feature route each card), with graceful shutdown / resume. Use when the user says "super-board", "/super-board", "drain my GitHub project", "set up the autonomous loop", "kick off the headless build/QA pipeline", or "stop super-board".

Overview

Publisher	EricTechPro
Repository	`super-board`
Skill name	`super-board`
Stars	464
Forks	136
Bundled files	19
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
19 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by EricTechPro on GitHub. Read the source before you install it.

Installation

Install the Super Board AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/EricTechPro/super-board/tree/main/skills/super-board
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/EricTechPro/super-board.git /tmp/super-board
mkdir -p .claude/skills
cp -r /tmp/super-board/skills/super-board .claude/skills/super-board

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Super Board in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Super Board on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Super Board is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

super-board — autonomous GitHub Project pipeline

Five verbs

Verb	Where	What it does
`super-board onboard`	interactive	one-time setup wizard; writes `.claude/super-board/configs/<slug>.json`
`super-board lint`	interactive	walks active-pipeline issues, flags vague ACs, runs pre-flight readiness
`super-board status`	interactive (read-only)	snapshot of active config, column counts, in-flight workers
`super-board run`	in-session (default)	the autonomous loop: waves of the `super-board-wave` dynamic workflow, run from this session (`worker_backend: "claude-p"` opts into the legacy headless runner `.claude/bin/super-board-run.sh`). Also the resume command — state lives on the board, not in process memory. Accepts a model-tier flag: `--low` (haiku/sonnet/opus ladder), default = medium (sonnet/opus/session), `--high` (opus for every card). `--codex [--low
`super-board stop`	interactive	graceful shutdown: posts "stopped mid-flight" comments on every in-flight issue + PR, releases assignee mutexes, kills workers + dispatcher. Next `super-board run` resumes.

If invoked with no verb, ask which one.

In Codex the skill is not a slash command: it is $super-board <verb>, found in .agents/skills/.

Routing

If user says	Load
`super-board onboard ...`	`references/onboard.md`
`super-board lint ...`	`references/lint.md`
`super-board status ...`	`references/status.md`
`super-board run --codex[=<model>] ...`, or any `run` from a host with no Workflow tool (overrides any configured backend)	`references/run-workflow.md` → "Codex runs"
`super-board run ...` (default — `worker_backend` unset or `"workflow"`)	`references/run-workflow.md` (lane lifecycles still come from `references/run.md`)
`super-board run ...` with config `worker_backend: "claude-p"` (legacy, explicit opt-in)	`references/run.md`
`super-board stop ...` / "stop the run" / "pause the loop" / "kill super-board"	`references/stop.md`
"resume" / "pick up where I left off" / "restart after stop"	`references/stop.md` (resume = run; no separate verb)
Anything about Blocked exits, 🙋 needs you, or dropping a card	`references/block-template.md`
Optional learning after a successfully completed run	`references/calibration.md` (external installed skill; bounded receipt; explicit existing-skill edit paths)
Config structure questions	`references/config-schema.json`
Worker gh-call discipline / rate-limit recovery	`references/rate-limit-etiquette.md` (+ `scripts/super-board-gh-guard.sh`)

Orchestrator vs worker — the cardinal rule

super-board is an autonomous trader. The interactive Claude session that invokes any of the five verbs is an orchestrator, not a worker. The orchestrator:

Validates preconditions, then dispatches per the config's worker_backend: "workflow" (default) → stay in-session and run the wave loop in references/run-workflow.md (launch workflow, reconcile, repeat); "claude-p" (legacy, explicit opt-in only) → nohup .claude/bin/super-board-run.sh, report PID + log path, exit. Explicit --codex overrides either backend with headless Codex waves; so does a host with no Workflow tool, or bash .claude/bin/super-board-host.sh printing codex. The orchestrator never does product work itself.
Delegates all build / QA / review work to workers — headless claude -p (claude-p backend), workflow lane agents (workflow backend), or headless codex exec (explicit --codex).
Must NOT do product work itself, must NOT patch the dispatcher mid-run, must NOT wait for workers, must NOT hold context for multi-card progress.

If anything goes wrong during a run, the orchestrator captures the symptom and reports back — it does not silently expand the task into a fix. See references/run.md "Orchestrator delegation contract" for the full rule.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Super Board AI skill do?

Why use Super Board on TypingMind?

Because you install it once and use it with any model. Super Board is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Super Board in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/EricTechPro/super-board/tree/main/skills/super-board. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Super Board?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Super Board?

As many as you like. As long as a model supports skills, you can use Super Board with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Super Board AI skill free?

Yes. It is published on GitHub by EricTechPro under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

super-board — autonomous GitHub Project pipeline

Five verbs

Routing

Orchestrator vs worker — the cardinal rule

Bundled files

Frequently asked questions

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