Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cosmicstack-labs/mercury-agent-skills --skill table-managergit clone --depth 1 https://github.com/cosmicstack-labs/mercury-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cosmicstack-labs/mercury-agent-skills/table-manager)<a href="https://agentmods.dev/skills/cosmicstack-labs/mercury-agent-skills/table-manager"><img src="https://agentmods.dev/badge/skills/cosmicstack-labs/mercury-agent-skills/table-manager.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.02066 |
| Opus 5 | $0.00020 | $0.01033 |
| Sonnet 5 | $0.00008 | $0.00413 |
| Haiku 4.5 | $0.00004 | $0.00207 |
Grade A, and why
table-manager scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Table Manager
Core Principles
For a restaurant, every empty seat is revenue walking out the door. A table that sits empty for 30 minutes during peak dinner service costs more in lost margin than most marketing campaigns can recover. Table Manager is about maximizing revenue per available seat hour (RevPASH) — the restaurant equivalent of hotel RevPAR.
The Four Levers of Table Revenue
- Turn Time — How long a table is occupied per party. Faster turns = more covers = more revenue.
- Table Mix — Ratio of 2-tops, 4-tops, 6-tops. Wrong mix for your party sizes = wasted seats.
- Booking Yield — How well you fill the reservations book. Gaps = lost revenue.
- Waitlist Management — How you handle walk-ins during peak times. A well-managed waitlist keeps people from walking out.
Skill Workflow
Step 1 — Audit Current Table Configuration
Ask the user for:
- Floor plan: Number of tables by size (2-top, 4-top, 6-top, etc.)
- Total seats and seatable capacity (adjust for social distancing if needed)
- Average turn time per meal period (breakfast, lunch, dinner)
- Reservation system (OpenTable, Resy, SevenRooms, or manual)
- Party size distribution (average % of 2s, 4s, 6s, etc.)
If they don't know average turn times:
"Let me calculate. What time was the first party seated at each table, and what time did the last party leave? I'll compute actual turn times from your service logs."
Step 2 — Calculate RevPASH Metrics
Revenue Per Available Seat Hour (RevPASH) = Total Revenue ÷ (Total Seats × Hours Open)
Seat Utilization % = Actual Covers ÷ (Total Seats × Turns Possible)
Theoretical Max Revenue = Seats × Hours × Max Turns × Avg Check
Revenue Gap = Theoretical Max − Actual Revenue
Example:
"Your restaurant has 40 seats open for 5 dinner hours. With 90-minute average turns and $45 avg check, your theoretical max is 133 covers / $5,985. Actual was 98 covers / $4,410. Gap: $1,575 in unrealized revenue. Every 10-minute reduction in turn time recovers $350/night."
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 177 lines · 40 tokens per session scan A 6e69c97428be
table-manager is a skill published in the GitHub repository cosmicstack-labs/mercury-agent-skills (471 stars, last pushed 13d ago), licensed MIT. It adds 40 tokens to every session and 2,066 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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