Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/cosmicstack-labs/mercury-agent-skillsnpx agentmods add skills/cosmicstack-labs/mercury-agent-skills/zomato-orderWrote 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/zomato-order)<a href="https://agentmods.dev/skills/cosmicstack-labs/mercury-agent-skills/zomato-order"><img src="https://agentmods.dev/badge/skills/cosmicstack-labs/mercury-agent-skills/zomato-order/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cosmicstack-labs/mercury-agent-skills/zomato-order"><img src="https://agentmods.dev/badge/skills/cosmicstack-labs/mercury-agent-skills/zomato-order.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 143 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00059 | $0.01265 |
| Opus 5 | $0.00030 | $0.00633 |
| Sonnet 5 | $0.00012 | $0.00253 |
| Haiku 4.5 | $0.00006 | $0.00127 |
Grade A, and why
zomato-order 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 8d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Zomato Order Skill 🛵
Core Principles
Ordering food through Zomato programmatically has a key constraint: Zomato has no public consumer ordering API. The only way to automate order creation is through browser automation (Playwright/Puppeteer).
The smartest approach is cookie-based session reuse:
- Phase 1 — Setup (one-time): Open a visible browser, let the user log in manually, capture session cookies
- Phase 2 — Auto-Order (reusable): Load saved cookies (auto-logged in), browse restaurants, build cart, generate payment link
This avoids OTP prompts on every order while keeping payment in the user's hands (they pay via the shared link).
How It Works
Phase 1 —Initial Setup
node scripts/zomato-order.js --setup
- Opens a visible Chromium browser to Zomato
- User logs in manually (phone + OTP)
- User confirms login is complete
- Session cookies are saved to
/tmp/zomato-cookies.json - Done — no further OTP needed for weeks/months
Phase 2 — Auto-Order
node scripts/zomato-order.js
- Loads saved cookies (auto-logged in)
- Navigates to Zomato, restores session
- Searches for restaurants in user's default location
- Waits for user to browse, select items, and add to cart
- Once at the payment page, captures the URL
- Shares the payment link with the user to complete payment
- Order is placed once user pays
When To Use This Skill
Trigger Phrases
| User says | Action |
|---|---|
| "Order food from Zomato" | Run Phase 2 (auto-order). If no cookies, run Phase 1 first |
| "Let's order lunch/dinner" | Same as above |
| "Setup Zomato ordering" | Run Phase 1 (setup) |
| "I need to set up Zomato first" | Run Phase 1 (setup) |
| "Order something for the office" | Run auto-order flow |
| "Can we do Zomato automation?" | Explain the two-phase approach, offer to set up |
When NOT to use
| Scenario | Reason |
|---|---|
| User wants to place order without any interaction | Payment requires user action (UPI/Card OTP) |
| Cookies expired (> 2 months old) | Run Phase 1 setup again |
| User on a different device | Works on the machine where the script runs |
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.
- 8d ago First seen · 167 lines · 59 tokens per session scan A f6c44da5df38
zomato-order is a skill published in the GitHub repository cosmicstack-labs/mercury-agent-skills (471 stars, last pushed 17d ago), licensed MIT. It adds 59 tokens to every session and 1,265 once invoked, about $0.0003 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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