Turn tables faster without rushing anyone: 10 AI skills for the waitlist

peak-hour-pacing

feed the kitchen in waves so service doesn't collapse at 8pm

How the two work together

Claude thinks it through. Paste the Claude prompt into Claude Code, or drop the folder into your skills folder. Claude does the judgement: what to look for, what is worth doing, what is right.

Codex gets it done. At the hand-off point Claude runs Codex on your machine with one command and passes it the Codex prompt. Codex does the mechanical part and hands the result back. Claude checks it before you see it.

No API key to set up: Claude calls the Codex you already have installed. If Codex is not installed, Claude does that half itself and tells you.

Prompt for Claude

---
name: peak-hour-pacing
description: Sets how many covers the booking system releases into the kitchen in each 15 or 30 minute interval during a rush, so the kitchen receives a steady wave of orders instead of everything the room can seat arriving at once. Derives the cap from the kitchen's own measured ticket times rather than the number of seats, and tracks the gap between peak and quiet-period speed as the signal something is wrong before guests start waiting for a first course. Use when setting how many parties can be seated per interval, or working out why peak service keeps falling behind.
---

# Feed the kitchen in waves, not a flood

Give it the kitchen's measured ticket times and the room's seat count. Get back a seating cap per interval built from kitchen throughput, and a tracked peak-versus-quiet gap that flags when the cap needs revisiting.

## What it does

1. **Understand what pacing caps.** "Pacing is the limit a restaurant sets on how many covers can be seated in each interval, usually fifteen or thirty minutes." Its purpose: the cap "determines kitchen load, quoted wait times, and how much attention each party gets on arrival."

2. **Base the cap on real throughput, not seats.** Guidance advises basing the cap "on the kitchen's real throughput rather than seat count." An 80-seat room with a kitchen that fires 40 covers per half hour needs a cap of roughly 40, not 80.

3. **Match the interval length to typical dining time.** "A 30-minute grid can leave capacity unused when parties stay about 80 minutes."

4. **Track ticket time as the kitchen's own core measure**, separately from the seating cap: the span "from order entry to the dish leaving the pass."

5. **Watch the peak-versus-quiet gap**, the early-warning signal: "a large gap often signals prep or mise en place trouble" rather than volume alone.

6. **Watch stations running long-cook items**, which can choke regardless of the cap set at the door.

7. **Revisit the cap when the gap grows**, rather than leaving it fixed once service has proven it is not holding.

## Then it checks

1. The cap states the kitchen throughput figure it was derived from.
2. The interval length is checked against typical dining duration.
3. Ticket time is logged separately from the cap, by course where possible.
4. The peak-quiet gap is tracked across services.
5. Any long-cook station has its own throughput note.

Any check fails: redo that step once. Failed twice: say what is wrong and stop.

## Rules
- Public information only. Never invent a fact, number or quote. Anything sent in someone's name says whose name it is.
- Never set a cap from seat count alone; it must derive from a stated kitchen throughput figure.
- Never report a ticket time without the peak-quiet gap alongside it.
- Working document for the owner to check against their own kitchen's real measured times.

## Built from
- Eat Loyalist, "Pacing", eatloyalist.com/glossary/pacing, updated 23 Aug 2026, read 4 Nov 2026: steps 1, 2 and 3.
- Nine Guides, "Speed of service benchmarks", nineguides.pages.dev, 7 Mar 2026, read 4 Nov 2026: steps 4 and 5.

Prompt for Codex

# peak-hour-pacing

## You are given
The kitchen's measured throughput: how many covers it can fire within a stated interval (for example, 40 covers per 30 minutes), already measured by the venue. The room's total seat count. The venue's own average dining duration in minutes. A log of ticket times by service, with timestamps, covering at least one peak and one quiet period. Any station known to run long-cook items, named by the owner.

## Produce
Write into a `./peak-hour-pacing-output/` folder:

1. `pacing-cap.csv` with columns: `interval_minutes`, `kitchen_throughput_covers`, `seat_count`, `cap_used`, `cap_source`. `cap_used` is `kitchen_throughput_covers`, never `seat_count`, unless `kitchen_throughput_covers` is blank, in which case `cap_source` records `no kitchen throughput supplied, seat count used as placeholder` and this is listed first in `gaps.md`.
2. `interval-check.csv` with columns: `interval_minutes`, `average_dining_duration_minutes`, `intervals_per_dining_duration`, `fit_flag`. `intervals_per_dining_duration` is `average_dining_duration_minutes` divided by `interval_minutes`. `fit_flag` is `good fit` where that value is 2 or more, and `may leave capacity unused` where it is below 2.
3. `ticket-times.csv` with columns: `service_date`, `period`, `course`, `ticket_time_minutes`. `period` is `peak` or `quiet`.
4. `peak-quiet-gap.csv` with columns: `service_date`, `course`, `peak_average_minutes`, `quiet_average_minutes`, `gap_minutes`, `gap_flag`. `gap_minutes` is `peak_average_minutes` minus `quiet_average_minutes`. `gap_flag` is `normal` below a gap of 3 minutes and `review prep/mise en place` at 3 minutes or above.
5. `station-watch.csv` with columns: `station_name`, `long_cook_item_named`, `note`.
6. `gaps.md` - a numbered list of: any `cap_used` drawn from seat count rather than kitchen throughput; any interval marked `may leave capacity unused`; any `gap_flag` of `review prep/mise en place`; any station named with no throughput note recorded.

## Rules
- Codex calculates, checks and records. It never sets the kitchen throughput figure, the interval length, or which stations to watch - those are supplied by the venue.
- Never substitute seat count for kitchen throughput in `cap_used` without flagging it.
- Averages and gaps are calculated exactly from the supplied ticket times, never estimated.
- Use British English and DD Month YYYY dates. No em dashes in any file you write; flag any supplied text containing one in `gaps.md`.
- Every file ends with this line: this is a working document prepared for the owner to check against their own kitchen's real measured times, and is not a guarantee that a given cap will hold on any specific night.

## Return
The absolute path of each file written and the row count of each CSV. The pacing cap used and its source for each interval. The interval-fit verdict against the venue's average dining duration. The peak-versus-quiet gap by course, and any course flagged for review. Any station named with a long-cook item and its note. The `gaps.md` item count.

Built from the best public work on this

Sources for peak-hour-pacing

Everything below was opened and read on 4 November 2026.

1. Eat Loyalist, "Pacing"

https://www.eatloyalist.com/glossary/pacing/, glossary entry, last updated 23 August 2026, read 4 November 2026.

Defines the term directly: "Pacing is the limit a restaurant sets on how many covers can be seated in each interval, usually fifteen or thirty minutes." On how reservation platforms apply it: "Reservation platforms enforce it by closing slots once the cap is reached." On what it is for: the cap "determines kitchen load, quoted wait times, and how much attention each party gets on arrival," so that an overly loose cap can overwhelm the kitchen and floor during a rush. On how to set it, the page advises basing the cap "on the kitchen's real throughput rather than seat count," and warns that "a 30-minute grid can leave capacity unused when parties stay about 80 minutes."

Used in steps 1, 2 and 3: the definition of pacing, the rule that throughput rather than seats should set the cap, and the warning that interval length must be checked against typical dining duration.

Where the skill departs: the page is a short glossary entry and does not give worked numeric examples beyond the 80-minute case; the skill requires the venue to supply its own throughput and dining-duration figures rather than borrowing an example number as a standard.

2. Nine Guides, "Speed of service benchmarks"

https://nineguides.pages.dev/operations/speed-of-service-benchmarks, operations guide, dated 7 March 2026, read 4 November 2026.

Defines ticket time as "tracked as the main kitchen performance metric," the gap from order entry to the dish leaving the pass. It recommends watching "the gap between peak and off-peak times," noting that "a large gap often signals prep or mise en place trouble" rather than volume alone.

Used in steps 4 and 5: the ticket time measure kept distinct from the pacing cap, and the peak-versus-quiet gap used as the early-warning signal that the kitchen's own prep, not just order volume, needs attention.

Where the skill departs: the guide's course-by-course benchmark figures (also used by the table-turn-timer skill in this pack) are not repeated here; this skill draws only on its ticket time and gap-tracking guidance, which applies to pacing specifically.

Best public prompt we found for this job

The closest public artefact is the `sprint-planning` skill in Anthropic's `knowledge-work-plugins` repository, raw source at https://raw.githubusercontent.com/anthropics/knowledge-work-plugins/main/product-management/skills/sprint-planning/SKILL.md. The repository has 34,655 stars, read from api.github.com on 4 November 2026. It is a software team sprint-planning skill, not a kitchen skill, but the job has the same shape: decide how much work to release into a team per fixed period, deliberately below full capacity, so the team can absorb the unplanned.

The useful part is its headline rule: "Plan to 70-80% capacity. You will get interrupts." We took the underlying principle directly into pacing: the seating cap per interval should be set from the kitchen's measured throughput with headroom for the long-cook dish or the slow table, not from a seat count that assumes every single cover arrives and cooks in textbook time.

We did not copy two things. `sprint-planning` sets one capacity figure for a two-week period that the team itself negotiates; a kitchen's pacing cap has to flex within a single evening, tightening or loosening by the half hour as the ticket-time gap moves, which a fixed sprint capacity has no mechanism for. And `sprint-planning` has no equivalent of a single station becoming the bottleneck regardless of overall team capacity; a kitchen's braise or pasta station can choke a whole pass even when every other station is comfortably inside its pacing cap, which is why this skill tracks station-level throughput separately rather than only a kitchen-wide average.

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