# Plan McDonald's Meals by Nutrition and Budget

Choosing meals within nutrition and budget limits requires checking menus, serving sizes, and discounts. Chilemai combines current MCP data with local meal planning and confirmed ordering.

## Install

```bash
npx skillstore add hessianz/chilemai
```

## Metadata

- Status: approved
- Slug: hessianz-chilemai
- Skillstore revision: r1
- Version status: missing
- Tree hash: 7af97fb7d22da7af95bde66bbbe71fd30885c49fe0d828a497f0e7cb986f7471
- Author: hessianz
- GitHub username: hessianz
- License: MIT
- Repository: https://github.com/hessianz/chilemai/tree/83f46eb66036472828157002e0700c55d1d2cc65/
- Ref: 03fad901c6372b6cd8e5a832fccabbac50bc422f
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: network, filesystem, external\_commands
- Quality score: 84
- Quality tier: gold
- Public page: https://skillstore.pages.dev/skills/hessianz-chilemai
- Manifest: https://skillstore.pages.dev/api/skills/hessianz-chilemai/manifest

## Capabilities

- Guide store selection using location, distance, opening status, and the selected pickup or delivery mode.
- Parse the MCP nutrition text format and match menu names after punctuation and whitespace normalization.
- Separate exact nutrition matches from uncertain candidates and unmatched products.
- Generate meals containing one to three single-item portions and check combined nutrition against selected limits.
- Guide coupon collection, store-specific eligibility checks, and official price comparisons before budget confirmation.
- Guide confirmed order creation, return payment links, and verify order status without blindly retrying uncertain creations.

## Use Cases

- Choose lunch near work: Find an open pickup store, compare meals against a lunch budget, and review the final official price before ordering.
- Compare meals by nutrition: Check combined calories and protein using confirmed single-item matches, while excluding products with missing or ambiguous nutrition.
- Coordinate a team meal: Follow the group-order workflow using headcount, delivery details, promotions, assistance-service parameters, and explicit approval of the final order.

## Prompt Templates

### Choose a pickup meal

```
Help me choose McDonald's lunch for pickup in Hangzhou near West Lake. My budget is 40 yuan. Show a recommendation before ordering.
```

### Apply nutrition limits

```
Find a pickup meal near West Lake in Hangzhou with at most 500 kcal and at least 25 g protein. Use confirmed nutrition matches.
```

### Compare final prices

```
For my selected store, compare two nutrition-qualified meals with applicable coupons. Check official totals against 40 yuan, including fees. Wait for confirmation before ordering.
```

### Prepare a group delivery

```
Prepare McDonald's delivery for 12 colleagues within 480 yuan. Ask me to confirm the address and time. Check promotions and required group-service parameters.
```

## Limitations

- Live menus and ordering require a configured McDonald's China MCP connection, an account token, and service availability.
- The bundled script requires Python 3.8 or later; it processes local data and does not connect to MCP or pay for orders.
- Automatic planning covers one to three single-item portions, excludes bundles and uncertain matches, and estimates prices without discounts or delivery fees.
- Nutrition coverage is incomplete and lacks sugar values; recommendations are not medical advice or guarantees about blood glucose.

## Best Practices

- Confirm the ordering mode, location, serving sizes, and nutrition limits before selecting a meal.
- Verify menu price units and use official calculated totals, including applicable fees, for budget decisions.
- Approve the exact order details before creation, and check existing orders when creation results are uncertain.

## Anti Patterns

- Treating a bundle as one burger when calculating total nutrition.
- Assuming uncertain matches or missing nutrition values satisfy dietary constraints.
- Promising final prices from menu estimates or creating orders without explicit confirmation.

## Security Audit

- Audited at: 2026-10-18T14:07:57.105\+00:00
- Summary: All 58 static alerts are false positives involving documented endpoints, installation paths, formatting, variable names, offline tests, and readable Chinese documentation. No evidence found of malicious execution, credential theft, concealed payloads, or prompt injection. The workflow uses an authenticated ordering service, requires explicit order confirmation, and leaves payment to the user.

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