SKILL·0E9F0C

vertical-restaurants

avelikiy
Aktualisiert 1 month ago
6 Ansichten
86
14
86
Auf GitHub ansehen
Andereaiapi

Über

Diese Fähigkeit vermittelt essenzielles Domänenwissen für die Entwicklung von Software für Restaurants und Gastgewerbe und behandelt Schlüsselkonzepte wie Menü-Modifikatoren, Inventar und finanzielle Rahmenbedingungen. Sie wird eingesetzt, wenn Kernprodukte wie Online-Bestellung, Reservierungen, Treueprogramme oder Terminplanung entworfen werden, um naive Datenmodelle zu vermeiden. Wenden Sie sie während der Architekturplanung oder der Spezifikation restaurantspezifischer Funktionen an.

Schnellinstallation

Claude Code

Empfohlen
Primär
npx skills add avelikiy/great_cto -a claude-code
Plugin-BefehlAlternativ
/plugin add https://github.com/avelikiy/great_cto
Git CloneAlternativ
git clone https://github.com/avelikiy/great_cto.git ~/.claude/skills/vertical-restaurants

Kopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um diese Fähigkeit zu installieren

Dokumentation

Vertical: restaurants & hospitality — don't spec it naive

Restaurants run on razor-thin margins (net 3–6%) with a hostile incumbent stack. A spec that treats a menu as a flat list of {name, price} or ignores who already owns the POS will ship something no operator can use. This skill loads the domain so architect/pm sound like they've worked a shift.

The 4 products in this vertical:

ProductArchetypeOne-liner
online-orderingcontentOwn menu + checkout for dine-in/pickup/delivery — dodge aggregator fees
reservationsbookingBookings, tables, text-the-waitlist
loyaltycrmPoints, offers, win-back
shift-schedulingbookingRota, open shifts, swaps with coverage rules

Incumbents to position against: Toast (POS, ~$69–165/mo + hardware + 2.49%+ per swipe), Square (POS/SMB), SevenRooms (reservations/CRM, upmarket), ChowNow (commission-free ordering), DoorDash / Uber Eats / Grubhub (aggregators, 15–30% commission per order).

1. Domain vocabulary (use these words in the spec)

  • COGS / food cost % — cost of ingredients ÷ menu price. Target ~28–35%.
  • Prime cost — food cost + labor cost; the number operators obsess over (target ≤ ~60% of sales).
  • Menu engineering — classifying items by popularity × margin into stars (high/high), plowhorses, puzzles, dogs (low/low). Drives what gets promoted or cut.
  • 86'd — an item is out of stock / unavailable ("we're 86 on the salmon"). Must propagate instantly to every ordering channel.
  • Modifiers / mods — choices on an item (size, temp, add bacon, no onions, sub fries). Grouped, with required/optional + min/max rules.
  • Covers — number of guests served (a "200-cover night").
  • Turn time — how long a table is occupied; reservations math depends on it (a 2-top turns in ~75 min).
  • FOH / BOH — front of house (servers, host, bar) / back of house (kitchen, prep, dish). Scheduling and tips differ between them.
  • Tip pooling — pooled tips split by rule (hours, role, points). Legally constrained — see §6.
  • Comps / voids — comp = item given free (manager discretion); void = item removed before it's made. Both need audit trails.
  • Ticket times — elapsed time from order fired to served; the kitchen's core SLA.
  • Third-party aggregator commission — the 15–30% DoorDash/Uber Eats/ Grubhub take. The pain that makes owned ordering a wedge.
  • KDS (kitchen display system) — screen in the kitchen that replaces paper tickets; orders route to it by station.

2. Non-obvious domain rules

  • The POS is the sticky system of record — don't fight it. Toast/Square own the menu, payments, and floor. Our products integrate with or sit beside the POS; they don't try to replace it. Sync the menu, don't fork it.
  • Aggregator commission is the wound; owned online-ordering is the wedge. A restaurant paying 25% to DoorDash on a $40 order keeps $30. Commission- free direct ordering is the single clearest ROI pitch — lead with it.
  • Menus have deep modifier hierarchies, not flat prices. "Burger" → size group (required, choose 1) → temp group (required) → add-ons (optional, 0–5) → side (required, choose 1, sub upcharges). Price = base + mods.
  • 86'd / out-of-stock is real-time and must sync everywhere. When the kitchen 86's an item it must vanish from online ordering, KDS, and the POS simultaneously, or you sell what you can't make.
  • Tips have legal handling. Pooling rules, who can share (FLSA bars managers/owners from tip pools), tip credit, and service-charge vs tip distinction are labor-law constrained, not free-form.
  • Margins are razor-thin. A feature that adds 30¢/order of cost can erase the margin on that order. Cost-consciousness is a feature, not a nicety.
  • Reservations + waitlist are SMS-driven. "Your table's ready" is a text, not an email. Waitlist quote times and ready-pings are the product.

3. What a naive build gets wrong

  • Flat menu, no modifier hierarchy. {name, price} can't express "medium, well-done, add bacon, sub fries (+$2)". Model modifier groups with required/optional + min/max from day one.
  • Ignoring 86'd / out-of-stock. Selling a sold-out item online is a refund, an angry guest, and a chargeback. Stock state is first-class.
  • Online ordering that doesn't sync the menu. A second menu that drifts from the POS menu means wrong prices and phantom items. One source of truth, synced.
  • Tip handling that breaks labor law. Letting managers into the pool, or mislabeling a service charge as a tip, is an FLSA violation, not a bug.
  • No dine-in vs pickup vs delivery distinction. Each channel has different fulfillment, timing, fees, address/table data, and tax. One generic "order" type is wrong.
  • Loyalty that's points-only with no win-back. Points without a lapsed- guest re-engagement flow (offers, "we miss you") leaves the highest-ROI CRM lever on the table.

4. Must-model entities

  • MenuItem — base price, category, station, tax class, availability state (available / 86'd / scheduled), with one or more ModifierGroups.
  • ModifierGroup{required: bool, min, max} + ordered Modifiers (name, price delta, default, in-stock). Hierarchy, not a flat list.
  • Orderchannel (dine_in | pickup | delivery), status (placed → confirmed → preparing → ready → completed | cancelled), line items with resolved modifiers, computed total, table/address per channel.
  • Reservation — party size, time, turn-time estimate, table assignment, status; plus Waitlist entry (quoted wait, ready-ping, SMS thread).
  • Shift — role (FOH/BOH), start/end, coverage rule (min staff per role/time), open shift + swap request with approval/coverage check.
  • LoyaltyMember — identity (phone-first), points balance, earn/redeem ledger, last-visit (for win-back segmentation), consent state.

5. Per-product notes (wedge + the one domain thing)

  • online-ordering (content) — Wedge: commission-free direct ordering vs DoorDash's 15–30% and Toast Online Ordering's per-order fee. The one thing: the menu + modifier hierarchy must sync from the POS and honor 86'd state, across dine-in/pickup/delivery, or it's worse than the aggregator it replaces. Menus rank locally → see [[local-seo]].
  • reservations (booking) — Wedge: SevenRooms is upmarket/expensive; give SMBs bookings + waitlist without the price tag. The one thing: it's SMS-first — text-the-waitlist and ready-pings are the product; turn time drives table availability. SMS consent → [[lifecycle-messaging]].
  • loyalty (crm) — Wedge: most POS loyalty is points-only; we add offers + win-back. The one thing: lapsed-guest re-engagement (segment by last-visit, send an offer) is where the revenue is — design win-back, not just an earn-points counter. Sends → [[lifecycle-messaging]].
  • shift-scheduling (booking) — Wedge: rota + open shifts + swaps cheaper/simpler than the incumbents. The one thing: swaps must enforce coverage rules (min staff per role per time band) — an unconstrained swap that leaves the line uncovered is the failure mode.

6. Compliance (light — defer the heavy lifts)

  • Tip pooling / labor law (FLSA) — managers/owners may not share in tip pools; keep tip vs service-charge distinct; honor tip-credit rules. State law varies (e.g. CA). Surface as a constraint; get specifics confirmed.
  • Food-allergen disclosure — the big 9 US allergens must be declarable on menu items; some jurisdictions require menu labeling. Model allergen tags on MenuItem.
  • SMS consent for waitlist/loyalty — TCPA consent, STOP/HELP, quiet hours apply to every text. Defer the mechanics to [[lifecycle-messaging]].
  • Payment — PCI scope, SCA, refunds/chargebacks. Defer billing/payment design to the billing/PCI track; don't hand-roll card handling here.

Cross-refs: [[lifecycle-messaging]] (every SMS/email leg — consent + deliver- ability), [[local-seo]] (menus and reservations rank locally; "best tacos near me" is the funnel), [[migration-ready-schema]] (importing an existing menu / guest list from the incumbent POS without losing modifier structure).

GitHub Repository

avelikiy/great_cto
Pfad: skills/vertical-restaurants
0
agentic-codingclaude-code-pluginclaude-code-skillsclaude-code-subagentscode-reviewcto
FAQ

Häufig gestellte Fragen

Was ist der Skill vertical-restaurants?

vertical-restaurants ist ein Claude Skill von avelikiy. Skills bündeln Anweisungen und Ressourcen, die Claude bei Bedarf lädt, um Aufgaben rund um vertical-restaurants ohne zusätzliche Eingaben auszuführen.

Wie installiere ich vertical-restaurants?

Verwende die Installationsbefehle auf dieser Seite: Füge vertical-restaurants als Plugin zu Claude Code hinzu oder klone das Repository in dein Skills-Verzeichnis. Starte Claude danach neu, damit der Skill geladen wird.

Zu welcher Kategorie gehört vertical-restaurants?

vertical-restaurants gehört zur Kategorie Andere.

Kann ich vertical-restaurants kostenlos nutzen?

Ja. vertical-restaurants ist auf AIMCP gelistet und kann kostenlos installiert werden.

Verwandte Skills

llamaguard
Andere

LlamaGuard ist Metas 7-8B-Parameter-Modell zur Moderation von LLM-Eingaben und -Ausgaben in sechs Sicherheitskategorien wie Gewalt und Hassrede. Es bietet eine Genauigkeit von 94-95 % und kann mit vLLM, Hugging Face oder Amazon SageMaker eingesetzt werden. Nutzen Sie diese Skill, um Inhaltsfilterung und Sicherheitsguardrails einfach in Ihre KI-Anwendungen zu integrieren.

Skill ansehen
cost-optimization
Andere

Diese Claude Skill unterstützt Entwickler bei der Optimierung von Cloud-Kosten durch Ressourcen-Dimensionierung, Tagging-Strategien und Ausgabenanalysen. Sie bietet einen Rahmen zur Senkung von Cloud-Ausgaben und zur Implementierung von Kosten-Governance für AWS, Azure und GCP. Nutzen Sie sie, wenn Sie Infrastrukturkosten analysieren, Ressourcen richtig dimensionieren oder Budgetvorgaben einhalten müssen.

Skill ansehen
sports-betting-analyzer
Andere

Diese Claude Skill analysiert Sportwettenmärkte inklusive Handicaps, Over/Unders und Spezialwetten, indem sie historische Trends und situative Statistiken untersucht, um Wertwetten zu identifizieren. Sie liefert strukturierte Markdown-Ausgaben mit umsetzbaren Empfehlungen zu Bildungszwecken. Entwickler sollten dies für Sportwetten-Analysetools nutzen, wobei zu beachten ist, dass es nur zur Unterhaltung/Bildung konzipiert wurde.

Skill ansehen
quantizing-models-bitsandbytes
Andere

Diese Fähigkeit quantisiert LLMs auf 8-Bit- oder 4-Bit-Präzision mittels bitsandbytes und erreicht dabei eine Speicherreduzierung von 50–75 % bei minimalem Genauigkeitsverlust. Sie ist ideal für den Betrieb größerer Modelle mit begrenztem GPU-Speicher oder zur Beschleunigung von Inferenzvorgängen und unterstützt Formate wie INT8, NF4 und FP4. Die Fähigkeit integriert sich in HuggingFace Transformers und ermöglicht QLoRA-Training sowie 8-Bit-Optimierer.

Skill ansehen