Food Ordering
asgeirtj/system_prompts_leaks
Prepare restaurant food orders for delivery or pickup; use for cart, checkout and tracking.
Order food, groceries, and convenience items from DoorDash using the built-in CLI integration
The automated check flagged lines worth reading first. See the safety section below.
$ npx skills add vellum-ai/vellum-assistant --skill doordash -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install vellum-ai/vellum-assistant doordash --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/doordash .claude/skills/doordash && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "doordash" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordash into .claude/skills/doordash/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doordash", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordashType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add vellum-ai/vellum-assistant --skill doordash -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install vellum-ai/vellum-assistant doordash --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/doordash .agents/skills/doordash && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "doordash" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordash into .agents/skills/doordash/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doordash", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vellum-ai/vellum-assistant --skill doordash -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install vellum-ai/vellum-assistant doordash --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/doordash .cursor/skills/doordash && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "doordash" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordash into .cursor/skills/doordash/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doordash", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/vellum-ai/vellum-assistant.git --path skills/doordash--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add vellum-ai/vellum-assistant --skill doordash -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install vellum-ai/vellum-assistant doordash --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/doordash .gemini/skills/doordash && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "doordash" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordash into .gemini/skills/doordash/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doordash", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install vellum-ai/vellum-assistant doordashInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add vellum-ai/vellum-assistant --skill doordash -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/doordash .github/skills/doordash && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "doordash" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordash into .github/skills/doordash/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doordash", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vellum-ai/vellum-assistant --skill doordash -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install vellum-ai/vellum-assistant doordash --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/doordash .opencode/skills/doordash && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "doordash" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/doordash into .opencode/skills/doordash/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doordash", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
doordashOrder food, groceries, and convenience items from DoorDash using the built-in CLI integration
Doordash is an agent skill from vellum-ai/vellum-assistant. Order food, groceries, and convenience items from DoorDash using the built-in CLI integration
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 24 other files, including scripts and assets (for example `scripts/__tests__/doordash-client.test.ts`, `scripts/__tests__/doordash-session.test.ts` and `scripts/doordash-cli.ts`). Compatibility notes: Designed for Vellum personal assistants
The repository describes itself as: An AI Assistant that’s easy to setup, does your work 24/7, knows your preferences and gets better over time. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 33cc983. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 14 files in scripts/ (TypeScript, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
bunFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Designed for Vellum personal assistants
From compatibility in the SKILL.md frontmatter.
Doordash loads about 3.3k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 1,440 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found patterns that need a careful read before installing.
The DoorDash CLI needs host access for Chrome CDP and session cookies - none of which are available inside the sandbox.Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from vellum-ai/vellum-assistant at commit 33cc983, republished under its MIT licence (© vellum-ai). 1,440 words, ~3,341 tokens.
.claude/skills/doordash/SKILL.md (or your agent's skills folder). This skill also uses 19 other files; get the full folder from GitHub.You can order food from DoorDash for the user using the DoorDash CLI script.
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.
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).
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 requiredunitAmount (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 textIf 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.
"error": "session_expired", inform the user that their DoorDash session has expired and they need to log in again.--json flag on all commands for reliable parsing.cart add calls. If you get a 403 error, wait 15–20 seconds and retry.--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.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.bun {baseDir}/scripts/doordash-entry.ts record to capture fresh queries before assuming the schema changed.Many items (especially coffee, boba, sandwiches) have required customization options like size, milk type, or toppings. Here's how to handle them:
bun {baseDir}/scripts/doordash-entry.ts item <storeId> <itemId> --json to get the item's option groupsid, name, required, minSelections, maxSelections, and choices[
{
"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.
cart add --options '<json>'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.
For complex items where constructing the JSON manually is difficult, use cart learn:
bun {baseDir}/scripts/doordash-entry.ts cart learn --jsonupdateCartItem operation and extracts the exact nestedOptions and specialInstructionscart add --options '<json>'You can also extract options from an existing recording with bun {baseDir}/scripts/doordash-entry.ts inspect <recordingId> --extract-options --json.
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 storebun {baseDir}/scripts/doordash-entry.ts menu <storeId> --json -> finds "Latte" itembun {baseDir}/scripts/doordash-entry.ts item <storeId> <latteItemId> --json -> returns options: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" --jsonbun {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>] --jsonUser: "Order a pepperoni pizza from Andiamo's"
bun {baseDir}/scripts/doordash-entry.ts status --json -> logged inbun {baseDir}/scripts/doordash-entry.ts search "Andiamo's" --json -> finds store 22926474bun {baseDir}/scripts/doordash-entry.ts menu 22926474 --json -> finds "Pepperoni Pizza Pie" (item 2956709006, $28.00)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 --jsonbun {baseDir}/scripts/doordash-entry.ts cart view <cartId> --json -> show summaryUser: "I need Tylenol from CVS"
bun {baseDir}/scripts/doordash-entry.ts status --json -> logged inbun {baseDir}/scripts/doordash-entry.ts search "CVS" --json -> finds store 1231787bun {baseDir}/scripts/doordash-entry.ts menu 1231787 --json -> isRetail: true, categories but no itemsbun {baseDir}/scripts/doordash-entry.ts store-search 1231787 "tylenol" --json -> finds resultsid, menuId, and unitAmount© vellum-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 19 other files (scripts, assets) in skills/doordash of vellum-ai/vellum-assistant.
Open the folder on GitHubat commit 33cc983
Doordash next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Doordash this skillvellum-ai/vellum-assistant | 1.4k | — | ~3.3k | Automated safety check: Warn | MIT | |
| Food Orderingasgeirtj/system_prompts_leaks | 69k | — | ~1.4k | Automated safety check: Pass | CC0-1.0 | |
| Doordash Group Ordersdavila7/claude-code-templates | 33k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Doordash Order Playbooksdavila7/claude-code-templates | 33k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Doordash Order Ledgerdavila7/claude-code-templates | 33k | — | ~918 | Automated safety check: Pass | MIT | |
| Doordash Spend Guarddavila7/claude-code-templates | 33k | — | ~1.3k | Automated safety check: Pass | MIT |
asgeirtj/system_prompts_leaks
Prepare restaurant food orders for delivery or pickup; use for cart, checkout and tracking.
davila7/claude-code-templates
Group food ordering through the DoorDash CLI (dd-cli) from a persistent team roster.
davila7/claude-code-templates
Named, context-bound saved DoorDash orders ("post-gym", "late-night deploy") recalled through the DoorDash CLI (dd-cli) with a mandatory cart-diff before any checkout link is handed over.
davila7/claude-code-templates
Accountability layer for agent-driven DoorDash ordering. An agent skill from davila7/claude-code-templates.
davila7/claude-code-templates
Hard spending policy for agent-driven DoorDash ordering through the DoorDash CLI (dd-cli).
thedaviddias/Front-End-Checklist
A skill your agent uses when reviewing stylesheets, component styles, and responsive behavior related to Order CSS files correctly.
vellum-ai/vellum-assistant
Create and configure a GitHub App so the assistant can push commits, open PRs, and comment under its own bot identity.
vellum-ai/vellum-assistant
Connect a Discord bot to the assistant via the Discord Gateway with guided application creation and intent configuration
vellum-ai/vellum-assistant
Create and configure a Sentry internal integration so the assistant can manage issues, alerts, and releases under its own identity
vellum-ai/vellum-assistant
Ingest a large dataset into memory as a skimmed map. An agent skill from vellum-ai/vellum-assistant.
vellum-ai/vellum-assistant
A skill your agent uses when the user wants to build, scaffold, ship, or edit a Vellum plugin that bundles multiple surfaces (hooks, tools, skills, and more) into one installable package.
vellum-ai/vellum-assistant
Connect a Slack app to the Vellum Assistant via Socket Mode.
Order food, groceries, and convenience items from DoorDash using the built-in CLI integration. Doordash is an agent skill from vellum-ai/vellum-assistant.
Run `npx skills add vellum-ai/vellum-assistant --skill doordash -a claude-code`. Or copy the skill folder (skills/doordash in vellum-ai/vellum-assistant) into .claude/skills/doordash in your project. Claude Code loads it when a task matches its description.
Run `npx skills add vellum-ai/vellum-assistant --skill doordash -a codex`. Or copy the skill folder (skills/doordash in vellum-ai/vellum-assistant) into .agents/skills/doordash in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vellum-ai/vellum-assistant --skill doordash -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/doordash, .gemini/skills/doordash, .github/skills/doordash and .opencode/skills/doordash in your project.
Going by SKILL.md and its folder, Doordash needs TypeScript for the scripts in its folder and the command-line tools its instructions call (bun). Our summary lists: Node.js. Compatibility (from SKILL.md): Designed for Vellum personal assistants.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md flagged 1 warning(s): mentions a credentials file (ssh keys, cloud or package-manager tokens). Read the flagged lines before installing; the check is not a guarantee either way. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Doordash is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Doordash: Food Ordering (asgeirtj/system_prompts_leaks, 69k stars), Doordash Group Orders (davila7/claude-code-templates, 33k stars), Doordash Order Playbooks (davila7/claude-code-templates, 33k stars) and Doordash Order Ledger (davila7/claude-code-templates, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
vellum-ai (a GitHub organization) maintains it in vellum-ai/vellum-assistant, which has 1,408 GitHub stars. The repository holds 108 skills in this directory. The repository was last updated on October 9, 2026.
Source: vellum-ai/vellum-assistant on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.