What does the Doordash AI skill do?

Order food, groceries, and convenience items from DoorDash using the built-in CLI integration

Why use Doordash on TypingMind?

Because you install it once and use it with any model. Doordash is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Doordash in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordash. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Doordash?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Doordash?

As many as you like. As long as a model supports skills, you can use Doordash with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Doordash AI skill free?

Yes. It is published on GitHub by vellum-ai under the MIT license. You only pay your own AI provider for the tokens you use.

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Doordash by vellum-ai — AI Skill for Any LLM

You can order food from DoorDash for the user using the DoorDash CLI script.

CLI Setup

IMPORTANT: Always use host_bash (not bash) for all DoorDash commands. The DoorDash CLI needs host access for Chrome CDP and session cookies - none of which are available inside the sandbox.

The DoorDash CLI is invoked via bun {baseDir}/scripts/doordash-entry.ts. Do NOT search for the script, inspect it, or try to discover how the CLI works. Just run the commands as documented below.

Task Progress Widget

A task progress card is shown automatically when you run your first DoorDash command. Its surface ID is doordash-progress. As each step completes, call ui_update with surface ID doordash-progress to update step statuses. Update data.templateData.steps - set completed steps to "status": "completed" with a "detail" string, the current step to "status": "in_progress", and future steps to "status": "pending". Adapt the steps to the actual flow (e.g. skip "Search restaurants" if the user named a specific store).

Typical Flow

When the user asks you to order food (e.g. "Order pizza from Andiamo's"):

Check session - run bun {baseDir}/scripts/doordash-entry.ts status --json. If loggedIn is false or the session is expired, inform the user that their DoorDash session has expired and they need to log in again.
Search - run bun {baseDir}/scripts/doordash-entry.ts search "<query>" --json to find matching restaurants. Present the top results to the user with name, rating, and delivery info. If the user named a specific restaurant, pick the best match. If ambiguous, ask.
Browse menu - run bun {baseDir}/scripts/doordash-entry.ts menu <storeId> --json to get the menu. Show the user the categories and items with prices. If the user already said what they want (e.g. "pepperoni pizza"), find the matching item(s). For convenience/pharmacy stores (CVS, Duane Reade, Walgreens etc.), the response will have isRetail: true and empty items - use store-search instead (see step 3b).

3b. Search within a retail store - for convenience/pharmacy stores, run bun {baseDir}/scripts/doordash-entry.ts store-search <storeId> "<query>" --json to find specific products. This returns items with IDs, prices, and menuIds that can be added to cart directly.

Get item details (if needed) - run bun {baseDir}/scripts/doordash-entry.ts item <storeId> <itemId> --json to see options/customizations. The response includes:
- options: each option group has minSelections/maxSelections indicating how many choices are required
- Each choice has unitAmount (price impact in cents), defaultQuantity, and possibly nestedOptions (sub-choices like milk type within a size selection)
- specialInstructionsConfig: whether special instructions are accepted, max length, and placeholder text
If the item has required options (like size or toppings), construct the nestedOptions JSON from the option/choice IDs and pass it via --options. Ask the user for preferences or pick sensible defaults.
Add to cart - run bun {baseDir}/scripts/doordash-entry.ts cart add --store-id <id> --menu-id <id> --item-id <id> --item-name "<name>" --unit-price <cents> [--options '<json>'] [--special-instructions "<text>"] --json. For subsequent items at the same store, pass --cart-id <id> from the first add response. Use --special-instructions for requests like "extra hot", "no ice", etc. Use --options to pass customization choices (see Customization Options below).
Review cart - run bun {baseDir}/scripts/doordash-entry.ts cart view <cartId> --json and show the user what's in their cart with prices. Ask if they want to add anything else or proceed.
Checkout - run bun {baseDir}/scripts/doordash-entry.ts checkout <cartId> --json to get delivery options. Present them to the user.
Payment methods - run bun {baseDir}/scripts/doordash-entry.ts payment-methods --json to see saved cards. Show the user which card will be used (the default one).
Place order - after the user explicitly confirms, run bun {baseDir}/scripts/doordash-entry.ts order place --cart-id <id> --store-id <id> --total <cents> [--tip <cents>] [--dropoff-option <id>] --json. The command auto-selects the default payment method if --payment-uuid is not provided. The response contains orderUuid on success.

Important Behavior

Always confirm before checkout. Never place an order without explicit user approval.
Be proactive. If the user says "order pizza from Andiamo's", don't ask clarifying questions upfront - search, find the store, show the menu, and suggest items. Only ask when you need a choice the user hasn't specified.
Handle expired sessions gracefully. If any command returns "error": "session_expired", inform the user that their DoorDash session has expired and they need to log in again.
Show prices. Always show prices when presenting items or the cart summary.
Use --json flag on all commands for reliable parsing.
Do NOT use the browser skill. All DoorDash interaction goes through the CLI, not browser automation.
Rate limiting. DoorDash rate-limits rapid sequential requests. When adding multiple items (e.g. a team order), wait 8–10 seconds between cart add calls. If you get a 403 error, wait 15–20 seconds and retry.
Special instructions are unreliable. Some merchants disable special instructions entirely. Always prefer --options for customizations (size, milk type, etc.). Only use --special-instructions for free-text requests that aren't covered by the item's option groups. If the merchant rejects special instructions, drop them and proceed without.
Customization fallback. If cart add with --options fails, or if the item details show options that are hard to construct (deeply nested, unusual format), proactively offer to use cart learn so the user can customize the item visually in the browser. Don't silently drop customizations - tell the user what happened and offer alternatives.
Always-allow tip. At the start of an ordering flow, suggest the user enable "always allow" for DoorDash commands: "Tip: You can type 'a' to always allow DoorDash commands for this conversation so you won't be prompted each time."
Error attribution. When errors occur, assume it's more likely a bug in our query/parsing than a DoorDash API change. Suggest running bun {baseDir}/scripts/doordash-entry.ts record to capture fresh queries before assuming the schema changed.

Customization Options

Many items (especially coffee, boba, sandwiches) have required customization options like size, milk type, or toppings. Here's how to handle them:

Constructing nestedOptions JSON

Run bun {baseDir}/scripts/doordash-entry.ts item <storeId> <itemId> --json to get the item's option groups
Each option group has id, name, required, minSelections, maxSelections, and choices
Build a JSON array of selections matching the DoorDash format:

json
[
  {
    "optionId": "<option-group-id>",
    "optionChoiceId": "<choice-id>",
    "quantity": 1,
    "nestedOptions": []
  }
]

For choices with nested sub-options (e.g., selecting "Oat Milk" under the "Milk" option within a size), add them to the nestedOptions array of the parent choice.

Pass the JSON string to cart add --options '<json>'

Special Instructions

Use --special-instructions on cart add for free-text requests like "extra hot", "no ice", "light foam". The item command response includes specialInstructionsConfig with the max length and whether instructions are supported.

Warning: Some merchants disable special instructions entirely. If specialInstructionsConfig.isEnabled is false, or if the add-to-cart call returns an error about special requests, drop the instructions and retry without them. Always prefer --options for customizations - special instructions are a last resort for requests not covered by the item's option groups.

Learning Customizations via Browser Recording

For complex items where constructing the JSON manually is difficult, use cart learn:

Run bun {baseDir}/scripts/doordash-entry.ts cart learn --json
A Chrome window opens - navigate to the item, customize it visually, and click "Add to Cart"
The command auto-detects the updateCartItem operation and extracts the exact nestedOptions and specialInstructions
Use the extracted options directly with cart add --options '<json>'

You can also extract options from an existing recording with bun {baseDir}/scripts/doordash-entry.ts inspect <recordingId> --extract-options --json.

Coffee Order Example

User: "Order a large oat milk latte with an extra shot from Blue Bottle"

bun {baseDir}/scripts/doordash-entry.ts search "Blue Bottle" --json -> finds store
bun {baseDir}/scripts/doordash-entry.ts menu <storeId> --json -> finds "Latte" item
bun {baseDir}/scripts/doordash-entry.ts item <storeId> <latteItemId> --json -> returns options:
- Size (required, min:1, max:1): Small (id:101), Medium (id:102), Large (id:103, +$1.00)
- Milk (required, min:1, max:1): Whole (id:201), Oat (id:202, +$0.70), Almond (id:203, +$0.70)
- Extras (optional, min:0, max:5): Extra Shot (id:301, +$0.90), Vanilla Syrup (id:302, +$0.60)
Construct options JSON and add to cart:


bun {baseDir}/scripts/doordash-entry.ts cart add --store-id <id> --menu-id <id> --item-id <id> --item-name "Latte" --unit-price 550 --options '[{"optionId":"size-group-id","optionChoiceId":"103","quantity":1,"nestedOptions":[]},{"optionId":"milk-group-id","optionChoiceId":"202","quantity":1,"nestedOptions":[]},{"optionId":"extras-group-id","optionChoiceId":"301","quantity":1,"nestedOptions":[]}]' --special-instructions "Extra hot" --json

Command Reference


bun {baseDir}/scripts/doordash-entry.ts status --json              # Check if logged in
bun {baseDir}/scripts/doordash-entry.ts logout --json              # Clear session
bun {baseDir}/scripts/doordash-entry.ts search "<query>" --json    # Search restaurants
bun {baseDir}/scripts/doordash-entry.ts menu <storeId> --json      # Get store menu (auto-detects retail stores)
bun {baseDir}/scripts/doordash-entry.ts store-search <storeId> "<query>" --json  # Search items within a convenience/pharmacy store
bun {baseDir}/scripts/doordash-entry.ts item <storeId> <itemId> --json  # Get item details + options
bun {baseDir}/scripts/doordash-entry.ts cart add --store-id <id> --menu-id <id> --item-id <id> --item-name "<name>" --unit-price <cents> [--quantity <n>] [--cart-id <id>] [--options '<json>'] [--special-instructions "<text>"] --json
bun {baseDir}/scripts/doordash-entry.ts cart remove --cart-id <id> --item-id <orderItemId> --json
bun {baseDir}/scripts/doordash-entry.ts cart view <cartId> --json
bun {baseDir}/scripts/doordash-entry.ts cart list [--store-id <id>] --json
bun {baseDir}/scripts/doordash-entry.ts cart learn --json                 # Learn customization options by recording browser interaction
bun {baseDir}/scripts/doordash-entry.ts inspect <recordingId> --extract-options --json  # Extract nestedOptions from a recording
bun {baseDir}/scripts/doordash-entry.ts checkout <cartId> [--address-id <id>] --json
bun {baseDir}/scripts/doordash-entry.ts payment-methods --json     # List saved payment methods
bun {baseDir}/scripts/doordash-entry.ts order place --cart-id <id> --store-id <id> --total <cents> [--tip <cents>] [--delivery-option <type>] [--dropoff-option <id>] [--payment-uuid <uuid>] --json

Example Interaction

User: "Order a pepperoni pizza from Andiamo's"

bun {baseDir}/scripts/doordash-entry.ts status --json -> logged in
bun {baseDir}/scripts/doordash-entry.ts search "Andiamo's" --json -> finds store 22926474
bun {baseDir}/scripts/doordash-entry.ts menu 22926474 --json -> finds "Pepperoni Pizza Pie" (item 2956709006, $28.00)
Tell user: "I found Pepperoni Pizza Pie at Andiamo's for $28.00. Adding it to your cart."
bun {baseDir}/scripts/doordash-entry.ts cart add --store-id 22926474 --menu-id 12847574 --item-id 2956709006 --item-name "Pepperoni Pizza Pie" --unit-price 2800 --json
bun {baseDir}/scripts/doordash-entry.ts cart view <cartId> --json -> show summary
"Your cart has 1x Pepperoni Pizza Pie ($28.00), total $28.00. Ready to check out?"

User: "I need Tylenol from CVS"

bun {baseDir}/scripts/doordash-entry.ts status --json -> logged in
bun {baseDir}/scripts/doordash-entry.ts search "CVS" --json -> finds store 1231787
bun {baseDir}/scripts/doordash-entry.ts menu 1231787 --json -> isRetail: true, categories but no items
bun {baseDir}/scripts/doordash-entry.ts store-search 1231787 "tylenol" --json -> finds results
Show top results: "Tylenol Extra Strength Gelcaps (24 ct) - $8.79, Tylenol Extra Strength Caplets (100 ct) - $13.49..."
User picks one -> add to cart with the item's id, menuId, and unitAmount

Publisher	vellum-ai
Repository	`vellum-assistant`
Skill name	`doordash`
Stars	1.3K
Forks	186
Bundled files	17
License	MIT
Links	Skill source Repository Homepage

Doordash

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

CLI Setup

Task Progress Widget

Typical Flow

Important Behavior

Customization Options

Constructing nestedOptions JSON

Special Instructions

Learning Customizations via Browser Recording

Coffee Order Example

Command Reference

Example Interaction

Bundled files

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

CLI Setup

Task Progress Widget

Typical Flow

Important Behavior

Customization Options

Constructing nestedOptions JSON

Special Instructions

Learning Customizations via Browser Recording

Coffee Order Example

Command Reference

Example Interaction

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now