Turn a minimal prompt — even one line — into a complete, WOW-grade deliverable bundle, right-sized to the domain and scope: grounded research, a project vision, a reusable meta-prompt, an execution plan, a grounded data model, and the production-quality artifacts that fit the work (interactive dashboards for a data/pitch/ops product, a report or doc site, an API/spec, a prototype — whatever the domain needs), plus an optional animated explainer with custom SVG. Research-grounded, mobile-ready, and adapts on call to different business/domain needs. Use when the user says meta-mvp, build an MVP or vision or prototype for something, go from this one-liner to something I can show, make me the full pitch, or spin up a new project for a client. Resolves its own scoping by default (never interrogates you — it studies the task's structure and, for high-stakes ambiguity, cross-checks with a small agent panel) and asks only if you opt in. Optionally composes meta-prompting, meta-planning, research-synthesis, user-resea
Installation
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Turn a minimal prompt — even one line — into a complete, WOW-grade deliverable bundle, right-sized to the domain and scope: grounded research, a project vision, a reusable meta-prompt, an execution plan, a grounded data model, and the production-quality artifacts that fit the work (interactive dashboards for a data/pitch/ops product, a report or doc site, an API/spec, a prototype — whatever the domain needs), plus an optional animated explainer with custom SVG. Research-grounded, mobile-ready, and adapts on call to different business/domain needs. Use when the user says meta-mvp, build an MVP or vision or prototype for something, go from this one-liner to something I can show, make me the full pitch, or spin up a new project for a client. Resolves its own scoping by default (never interrogates you — it studies the task's structure and, for high-stakes ambiguity, cross-checks with a small agent panel) and asks only if you opt in. Optionally composes meta-prompting, meta-planning, research-synthesis, user-research, dict-color (bundled), bertin, editorial-dashboard, docs-dashboard, ceti-explainer, frontend-design, and motion-media-l2 — and degrades gracefully without them. Do not use for a single fully-specified one-off file, or pure question answering.
Meta-Suite doctrine (overrides anything below). Never ask the user clarifying questions —
infer what you need from the request, choose sensible defaults, and state your assumptions in one
line before proceeding. Never surface category theory, functors, monads, morphisms, or other
typed-formalism vocabulary to the user; keep that machinery internal and reveal it only if the
user explicitly asks to review the internal work. Keep all user-facing output in plain language.
meta-mvp
Take a minimal prompt — even one line — and ship a complete, stakeholder-ready bundle that produces a
WOW effect from the first glance.
This skill is SELF-CONTAINED. It does not assume any sibling skill is installed. The procedures,
the spec layer, and the copy-paste templates it needs are in references/ and templates/ here.
If sibling skills happen to be loaded you may also use them, but the bundled kits are the source of
truth — the result must be identical with or without them. Read the kits; don't wing it from the
description. Thin runs that skip the kits regress to generic output. A bundled palette tool ships
at bin/dict_color.py (stdlib-only) so the palette gate runs with no external install.
The core move (do it, then hide it)
A minimal prompt is an object; the bundle is its image under a structure-preserving map. Expand the
prompt into a typed domain (entities, relationships, invariants), then map that structure onto
deliverables: entities→data-model types, relationships→contracts and intros, independence→parallel
build lanes. Category theory is the engine, not the output — every customer-facing artifact hides
the abstraction. (Optional APPENDIX_how-we-thought.md is the only place it may appear.)
What it ships — a right-sized bundle (depth is constant; surface adapts)
Two layers. The depth spine is always produced — it is what separates a real MVP from a generic
page. The surface artifacts adapt to the domain and scope tier: don't force two dashboards onto
work that isn't a dashboard, and don't ship the full bundle for a prototype. A run that skips the SPEC
layer, the meta-prompt, or the plan has regressed — but the surface is chosen, not fixed.
The depth spine — always, every domain
00_INTAKE.md — the four resolved unknowns, each with confidence + deciding signal
(references/intake.md). Derived by default; never a wall of questions.
02_VISION.md — vision + scope in the stakeholder's language.
03_META_PROMPT.md — the reusable system meta-prompt (references/meta-prompt-kit.md Part A).
03b_COMPONENT_SPEC_META_PROMPT.md + SPEC_01..NN_*.md — the SPEC LAYER: decompose into 3–6
modules and spec each (concept brief + build spec) via sub-agents (references/spec-layer.md). The
depth most often dropped — never skip it in any domain (a prototype may run 1–2 modules).
04_PLAN.md — the typed execution plan (references/meta-plan-kit.md).
05_DATA_MODEL.md + seed_data.json — the grounded common data model (when the domain has data).
The surface artifacts — pick what fits the domain
Map the domain to its natural WOW artifact(s). Build the ONE that carries the outcome first; add a
second only if the scope tier calls for it. Every surface still earns WOW: custom inline SVG, real
palette, purposeful motion, mobile-ready.
Data / pitch / ops product → the two-dashboard pattern (Motion editorial daily tool + Aceternity
showcase) — templates/dashboard-skeleton.md. Default for this domain, not for all work.
Explainer / concept / teaching → the ceti animated explainer (templates/ceti-engine.md) as lead.
Document / report / strategy → a typeset long-form artifact or doc site; dashboards optional/dropped.
API / system / technical spec → the spec bundle + a reference doc or interactive schema viewer.
Anything else → derive the artifact from the data model + outcome. The rule is "one glance tells
the story", not "there must be a dashboard".
Offer an animated explainer on top when it sharpens the story.
Prototype → light spine (intake + lean vision + one surface artifact); SPEC fan-out may be 1–2
modules; skip the second dashboard. Say it's a prototype.
Full bundle → the whole spine + the domain's full surface set + a verify pass.
Visuals only / strategy only → just that slice, still grounded and gated.
When torn between tiers, choose the smaller and say so — "this needs less" is a passing answer.
The protocol (run in order; gate between stages)
Full contracts in references/pipeline.md. The stages:
INTAKE — resolve audience, outcome, aesthetic, and scope from the prompt + research. Derive by default (never interrogate); panel-review high-stakes ambiguity; ask only on explicit opt-in. See references/intake.md.
GROUND — research before building: web search/fetch for public facts; connected MCPs for the
stakeholder's real world (voice transcripts, mail, docs). Brand: pull real colors or derive + flag.
EXPAND (internal) — references/category-expansion.md. Decompose; name modules + invariants.
META-PROMPT — references/meta-prompt-kit.md Part A.
SPEC LAYER — references/meta-prompt-kit.md Part B + references/spec-layer.md. Sub-agents,
one per module, concurrently. This is the depth most often dropped — never skip it.
PLAN — references/meta-plan-kit.md (typed units, gates, parallel lanes, sub-agent protocol).
BUILD — build the domain's surface artifact(s) (see "What it ships" + dashboard-playbook.md):
dashboards via templates/dashboard-skeleton.md, explainer via templates/ceti-engine.md, or the
domain-appropriate artifact. Palette via bundled bin/dict_color.py; custom SVG; mobile.
VERIFY — every gate in references/quality-gates.md passes. For high stakes, a verify sub-agent.
SHIP — present in order; offer the appendix; offer a Vercel deploy only on explicit approval.
Hard completion gate (check before you say "done")
Intake resolved (derived by default, or asked only on opt-in); vision in the stakeholder's language.
Research grounded + cited; palette real or flagged.
Meta-prompt typed + example-agnostic (tested vs 2–3 sibling instances).
SPEC LAYER present: component-spec meta-prompt + module specs (≥3 for a full bundle, ≥1 for a
prototype), each with both layers, typed entities, no dead states, ≥3 edge cases, ≥1 spike, linking one canonical entity.
Plan: typed units + done-criteria + gates + parallel lanes.
Data model grounded; seed_data.json valid; sensitive facts gated out (when the domain has data).
Every surface artifact chosen for the domain: custom SVG, load-bearing motion where used,
mobile-ready, palette-coherent (dict-color gate PASS or hand-checked), JS parses.
If an explainer ships: 8 beats, ~35–45s, deterministic, scrubbable.
Right-sized to the scope tier — no artifact built that the tier didn't call for.
No category-theory vocabulary in any client artifact; appendix offered.
Files numbered; presented; deploy offered (not executed) on approval.
Missing any box = not done. See references/worked-example.md for the target depth.
Non-negotiables
WOW from glance one (custom SVG, real palette, purposeful motion) · research first, no invented facts
· abstraction hidden in outputs · mobile-ready · right-sized to the domain + scope (never overkill) ·
honest flags on anything unverified · never publish/send without approval · gate personal/sensitive
data out of client artifacts · verify before ship.
References & templates
references/pipeline.md — the 9 stage contracts.
references/intake.md — the short-intake questions.
references/category-expansion.md — minimal prompt → typed domain (the hidden engine).
references/meta-prompt-kit.md — meta-prompt (Part A) + the component-spec generator (Part B).
references/spec-layer.md — per-module specs via sub-agents (the missing piece).
references/meta-plan-kit.md — the typed planning scaffold + sub-agent protocol.