Agent skill

Doordash

by vellum-ai in vellum-ai/vellum-assistant

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

MITAuto-check: warnings

Install Doordash

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add vellum-ai/vellum-assistant --skill doordash -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install vellum-ai/vellum-assistant doordash --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
doordash
GitHub stars
1.4k
Token cost
~3.3k tokens
SKILL.md length
1,440 words
Files
20 (incl. scripts, assets)
Skills in repo
108
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 3 steps: Check session - run bun… → Search - run bun… → Browse menu - run bun…
  • SKILL.md covers CLI Setup, Task Progress Widget, Typical Flow and Important Behavior, plus 3 more sections
  • Runs TypeScript scripts from its folder; calls bun

What it does

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.

Example prompts

  • “/doordash”

Requirements

  • Node.js
  • Compatibility (from SKILL.md): Designed for Vellum personal assistants

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Check session - run bun {baseDir}/scripts/doordash-entry.ts status --json. If loggedIn is false or the session is expired, inform the user…
  2. Search - run bun {baseDir}/scripts/doordash-entry.ts search "" --json to find matching restaurants. Present the top results to the user…
  3. Browse menu - run bun {baseDir}/scripts/doordash-entry.ts menu --json to get the menu. Show the user the categories and items with prices…

What it can do on your machine

Read from SKILL.md and the folder at commit 33cc983. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 14 files in scripts/ (TypeScript, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • bun

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Vellum personal assistants

    From compatibility in the SKILL.md frontmatter.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~26
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

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.

Safety

Auto-check: warnings

The automated check found patterns that need a careful read before installing.

  • WarningMentions a credentials file (SSH keys, cloud or package-manager tokens)SKILL.md:17
    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.

SKILL.md

The full file from vellum-ai/vellum-assistant at commit 33cc983, republished under its MIT licence (© vellum-ai). 1,440 words, ~3,341 tokens.

Download SKILL.mdSave it as .claude/skills/doordash/SKILL.md (or your agent's skills folder). This skill also uses 19 other files; get the full folder from GitHub.
name
doordash
description
Order food, groceries, and convenience items from DoorDash using the built-in CLI integration
compatibility
Designed for Vellum personal assistants
metadata.icon
assets/icon.svg
metadata.emoji
🍕

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"):

  1. 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.

  2. 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.

  3. 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.

  1. 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.

  2. 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).

  3. 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.

  4. Checkout - run bun {baseDir}/scripts/doordash-entry.ts checkout <cartId> --json to get delivery options. Present them to the user.

  5. 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).

  6. 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.
Show full SKILL.md (524 more words)Show less

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
  1. Run bun {baseDir}/scripts/doordash-entry.ts item <storeId> <itemId> --json to get the item's option groups
  2. Each option group has id, name, required, minSelections, maxSelections, and choices
  3. 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.

  1. 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:

  1. Run bun {baseDir}/scripts/doordash-entry.ts cart learn --json
  2. A Chrome window opens - navigate to the item, customize it visually, and click "Add to Cart"
  3. The command auto-detects the updateCartItem operation and extracts the exact nestedOptions and specialInstructions
  4. 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"

  1. bun {baseDir}/scripts/doordash-entry.ts search "Blue Bottle" --json -> finds store
  2. bun {baseDir}/scripts/doordash-entry.ts menu <storeId> --json -> finds "Latte" item
  3. 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)
  4. 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"

  1. bun {baseDir}/scripts/doordash-entry.ts status --json -> logged in
  2. bun {baseDir}/scripts/doordash-entry.ts search "Andiamo's" --json -> finds store 22926474
  3. bun {baseDir}/scripts/doordash-entry.ts menu 22926474 --json -> finds "Pepperoni Pizza Pie" (item 2956709006, $28.00)
  4. Tell user: "I found Pepperoni Pizza Pie at Andiamo's for $28.00. Adding it to your cart."
  5. 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
  6. bun {baseDir}/scripts/doordash-entry.ts cart view <cartId> --json -> show summary
  7. "Your cart has 1x Pepperoni Pizza Pie ($28.00), total $28.00. Ready to check out?"

User: "I need Tylenol from CVS"

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

Files

SKILL.md and 19 other files (scripts, assets) in skills/doordash of vellum-ai/vellum-assistant.

  • SKILL.md
  • assets/icon.svg
  • scripts/__tests__/doordash-client.test.ts
  • scripts/__tests__/doordash-session.test.ts
  • scripts/doordash-cli.ts
  • scripts/doordash-entry.ts
  • scripts/lib/cart-queries.ts
  • scripts/lib/client.ts
  • scripts/lib/order-queries.ts
  • scripts/lib/queries.ts
  • scripts/lib/query-extractor.ts
  • scripts/lib/search-queries.ts
  • scripts/lib/session.ts
  • scripts/lib/shared/errors.ts
  • scripts/lib/shared/network-recorder.ts
  • scripts/lib/shared/recording-store.ts
  • … and 4 more

Open the folder on GitHubat commit 33cc983

Compare with similar skills

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.

Doordash compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Doordash this skillvellum-ai/vellum-assistant1.4k—~3.3kAutomated safety check: WarnMIT
Food Orderingasgeirtj/system_prompts_leaks69k—~1.4kAutomated safety check: PassCC0-1.0
Doordash Group Ordersdavila7/claude-code-templates33k—~1.3kAutomated safety check: PassMIT
Doordash Order Playbooksdavila7/claude-code-templates33k—~1.6kAutomated safety check: PassMIT
Doordash Order Ledgerdavila7/claude-code-templates33k—~918Automated safety check: PassMIT
Doordash Spend Guarddavila7/claude-code-templates33k—~1.3kAutomated safety check: PassMIT

Similar skills

  • Food Ordering

    asgeirtj/system_prompts_leaks

    Prepare restaurant food orders for delivery or pickup; use for cart, checkout and tracking.

    69k GitHub stars~1.4k tokensUpdated yesterday
    Auto-check passed
  • Doordash Group Orders

    davila7/claude-code-templates

    Group food ordering through the DoorDash CLI (dd-cli) from a persistent team roster.

    33k GitHub stars~1.3k tokensUpdated yesterday
    DevOps & CloudAuto-check passed
  • Doordash Order Playbooks

    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.

    33k GitHub stars~1.6k tokensUpdated yesterday
    Auto-check passed
  • Doordash Order Ledger

    davila7/claude-code-templates

    Accountability layer for agent-driven DoorDash ordering. An agent skill from davila7/claude-code-templates.

    33k GitHub stars~918 tokensUpdated yesterday
    Auto-check passed
  • Doordash Spend Guard

    davila7/claude-code-templates

    Hard spending policy for agent-driven DoorDash ordering through the DoorDash CLI (dd-cli).

    33k GitHub stars~1.3k tokensUpdated yesterday
    Auto-check passed
  • CSS Order

    thedaviddias/Front-End-Checklist

    A skill your agent uses when reviewing stylesheets, component styles, and responsive behavior related to Order CSS files correctly.

    74k GitHub stars~404 tokensUpdated 5 days ago
    Frontend & DesignAuto-check passed

More from vellum-ai/vellum-assistant

All 108 skills in this repo
  • Vellum GitHub App Setup

    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.

    1.4k GitHub stars~3.1k tokensUpdated 2 days ago
    Auto-check passed
  • Discord App Setup

    vellum-ai/vellum-assistant

    Connect a Discord bot to the assistant via the Discord Gateway with guided application creation and intent configuration

    1.4k GitHub stars~4.2k tokensUpdated 2 days ago
    Auto-check passed
  • Sentry App Setup

    vellum-ai/vellum-assistant

    Create and configure a Sentry internal integration so the assistant can manage issues, alerts, and releases under its own identity

    1.4k GitHub stars~1.3k tokensUpdated 2 days ago
    Auto-check passed
  • Memory Corpus Ingest

    vellum-ai/vellum-assistant

    Ingest a large dataset into memory as a skimmed map. An agent skill from vellum-ai/vellum-assistant.

    1.4k GitHub stars~3k tokensUpdated 2 days ago
    Auto-check: notes
  • Plugin Builder

    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.

    1.4k GitHub stars~3.1k tokensUpdated 2 days ago
    Auto-check passed
  • Slack App Setup

    vellum-ai/vellum-assistant

    Connect a Slack app to the Vellum Assistant via Socket Mode.

    1.4k GitHub stars~2.5k tokensUpdated 2 days ago
    Auto-check: warnings

Questions about Doordash

What does Doordash do?

Order food, groceries, and convenience items from DoorDash using the built-in CLI integration. Doordash is an agent skill from vellum-ai/vellum-assistant.

How do I install Doordash in Claude Code?

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.

How do I install Doordash in Codex?

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.

Can I use Doordash in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Doordash need to run?

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.

Does Doordash access the network?

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.

Is Doordash safe to install?

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.

What licence does Doordash use?

Doordash is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Doordash use?

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.

What are the alternatives to Doordash?

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.

Who maintains Doordash?

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.