help

name	help
description	Use when the user asks what MasterMind can do or how to drive it — "help", "what can you do", "how do I use this", "what commands are there", "list your skills", "what are my options" — or when they seem unsure how to get started.

Help — what MasterMind can do, and how to use it

Present this as a clear, friendly menu (adapt length to the ask). Open with the brand header, then lead with the one thing that matters most, then the tables. Keep it scannable. Header:

🧠  MasterMind — a genius-builder brain for your AI
    22 skills · 4 agents · Claude Code · Cursor · Codex

Lead with what fits this project

Before the full menu, name up to three skills that would earn their keep here right now, each with the reason it applies — read from what's actually in front of you (the stack, the current task, what the last few turns were about, whether a field pack exists yet):

Most useful here right now
  · init      — no field pack yet for this Django project; one-time setup, then I'm sharper on it
  · lab       — there's client data in this repo; this keeps it out of git
  · handoff   — this session is long; a handoff survives the reset

A full menu is a catalogue; three fitting picks are advice. Then give the tables below — the catalogue still matters, because the point is that the user learns what they already own.

The one rule: you don't run commands — you just talk

MasterMind works by recognizing intent. Say what you want in plain language and it applies the right skill or agent itself, then shows a short note that it did (e.g. 🧠 MasterMind ▸ building this — will verify before handoff, with └ build · design → implement → verify beneath it). The /name calls below are an optional shortcut — a way to force a specific skill — not something you need to memorize. Every skill is Auto (the model can invoke it); you can also call any of them by hand.

Skills — the workflows (all Auto-invocable)

Skill	What it does	Fires automatically when…	Call it by hand
init	set MasterMind up for this project — detect the stack (or ask what you're building), load the field pack	your first real task in a project it isn't set up for	"init" · "set up MasterMind"
build	design → implement → verify → review → capture, end to end	you ask to build/add/implement a non-trivial feature	"build a search box for the header"
debug	structured, evidence-first root-cause debugging	a bug is hard, weird, or keeps coming back	"debug why the list doesn't refresh"
perf	measure → find the real bottleneck → fix the biggest → verify	something's slow or janky ("why is this slow?")	"why is this page so slow?"
qa	prove a change works by driving it for real (+ optional tests)	you finish something / ask to test it	"qa this" · "write tests for it"
report	a shareable write-up of a cycle — changed files, decisions, verification, verdict (MD default, HTML on request)	you ask for a report; or end of build/qa if you turned it on (off by default)	"give me a report of this" · "reports on"
spec	turn a fuzzy ask into a crisp, buildable spec	the request is ambiguous or spans many files	"spec out the checkout flow first"
route	load only the files/skills a task actually needs	a task is non-trivial or you're unsure where to start	"route this"
learn	get up to speed fast on an unfamiliar stack/API, verify assumptions	the tech is new, fast-moving, or you're guessing	"learn how the Stripe API handles refunds"
spike	build a throwaway spike to learn, then rebuild properly	the right approach is genuinely unknown	"spike a quick prototype of this"
signature	capture your team's real conventions as durable rules it follows	you ask it to match your codebase / keep correcting the same thing	"make it match our patterns"
persona	write in the documented public style of a named engineer, cited	you ask for someone's style ("write like X")	"write this like Kent C. Dodds"
explain	write AI-friendly usage docs beside an internal package	an internal package has little/no docs (asks first)	"explain this package"
prompt	sharpen a vague prompt into a precise, AI-ready one	you ask to optimize/fix a prompt for an AI	"improve this prompt"
lab	set up a private, gitignored quarantine for confidential data	before capturing project/client-specific notes	"set up a lab here"
levelup	improve MasterMind's own knowledge (lessons, curriculum, new field)	after a correction/review, or to refresh standards	"levelup — remember this"
doubt	interrogate a claim before handing it over — adversarial, reviewer never sees your conclusion	you're about to say "it works", or a review came back suspiciously clean	"doubt this"
deprecate	remove/migrate/retire safely — expand → migrate → contract	deleting a feature, column, flag, or endpoint	"can we delete this?"
map	a durable decision map for multi-week work	work spanning many sessions; "why did we decide X?"	"map this project"
lint	check MasterMind's own files for bloat, repeated rules, contradictions	before a release, or the brain feels bloated	"lint the brain"
handoff	write a concise handoff so work survives a reset/teammate	before a long-task /clear, pausing, or handing off	"write a handoff"
help	show this menu — what every skill/agent does and when it fires	you ask "what can you do?" / "help" / "how do I use this"	"what can you do?"

Agents — the deep expert roles (isolated context)

Agents run in their own context for a focused job. MasterMind delegates to them inside a task; you can also summon one directly.

Agent	What it does	Used automatically when…	Call it by hand
architect	designs the solution before code (boundaries, data model, APIs)	a feature is non-trivial (inside build)	"architect this feature"
code-reviewer	reviews a diff against the rigor gate; proposes fixes, never applies	after a change, before "done"	"review this"
refactorer	restructures working code to a better design, behavior-preserving	you ask to clean up / restructure working code	"refactor this component"
tech-scout	decides adopt-vs-build for a library/tool/pattern, with a verdict	choosing a dependency or approach	"should we use Zustand or Redux here?"

Skills vs agents (one line)

Skills are inline workflows that run in the current conversation; agents are separate expert roles with their own fresh context for a heavier, focused job. You rarely pick — MasterMind reaches for the right one and tells you.

Getting set up

If MasterMind isn't set up for this project yet (no field pack for your stack), it will offer a one-time setup — say "init" or just start working and it'll ask. Verify your install anytime with ~/.mastermind/install.sh --check.

Two optional preferences (per project, both off by default, kept in .mastermind/prefs.md):

• cycle report — a written write-up at the end of a build/QA cycle. Turn on: "reports on".
• plan-first — on bigger tasks, MasterMind shows the plan and waits for your OK before editing. Turn on: "plan first from now on".

Both behave exactly as their implementations define them — skills/build/SKILL.md (plan-first gate) and skills/report/SKILL.md (report formats).