Agent skill

Snowflake

by adobe in adobe/skills

Use this when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived, etc.) into an Edge Delivery Services page while preserving the original design and…

Apache-2.0Auto-check passedDatabases

Install Snowflake

skills CLI
$ npx skills add adobe/skills --skill snowflake -a claude-code

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

GitHub CLI
$ gh skill install adobe/skills snowflake --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/adobe/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/aem/edge-delivery-services/skills/snowflake .claude/skills/snowflake && 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
snowflake
GitHub stars
195
Token cost
~3.7k tokens
SKILL.md length
1,254 words
Files
55 (incl. scripts, assets)
Skills in repo
105
Repo updated
First seen
Licence
Apache-2.0

At a glance

Use this when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived, etc.) into an Edge Delivery Services page while preserving the original design and…

  • Works in 4 steps: Target EDS repo — detected via gh repo… → DA root path — read from… → Conversion level — inferred from… → …
  • Include convert this page to EDS
  • SKILL.md covers When to use, What this skill does NOT do, Parameters and Skill dependencies, plus 6 more sections
  • Runs JavaScript scripts from its folder; calls git, node and curl; reaches admin.da.live and admin.hlx.page; needs DA_TOKEN

What it does

Snowflake is an agent skill from adobe/skills. Use this when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived, etc.) into an Edge Delivery Services page while preserving the original design and making content authorable in Document Authoring — triggers include "convert this page to EDS", "static-to-EDS overlay", "convert to EDS blocks", "next experimentation", "next run", "start run", or providing a source URL to make editable in DA. Covers two modes — page-level (overlay template with slot markers) and…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 61 other files, including scripts and assets (for example `.releaserc.json`, `CHANGELOG.md` and `HOST-NOTES.md`).

It sits in Databases, covering Data warehousing, HTML artifacts and A/B testing. It works with Adobe Experience Manager, Snowflake and Figma. The repository describes itself as: Adobe Skills for Agents. The licence is Apache-2.0.

When your agent uses it

  • Include convert this page to EDS
  • Static-to-EDS overlay
  • Convert to EDS blocks
  • Next experimentation

Example prompts

  • “convert this page to EDS”
  • “static-to-EDS overlay”
  • “convert to EDS blocks”
  • “/snowflake”

Requirements

  • Node.js

Workflow steps

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

  1. Target EDS repo — detected via gh repo view --json nameWithOwner,
  2. DA root path — read from .snowflake/config.json daRoot key
  3. Conversion level — inferred from phrasing (see Parameters), else
  4. Slug / template name — derived from the source URL (kebab-case,

What it can do on your machine

Read from SKILL.md and the folder at commit cbc9952. 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 1 file in scripts/ (JavaScript, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • git
    • node
    • curl
    • npx
    • jq
    • gh

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • admin.da.live
    • admin.hlx.page

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • DA_TOKEN

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

Context cost

Snowflake loads about 3.7k tokens when it runs. Until then it costs about 163 tokens; SKILL.md has 1,254 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~163
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

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 passed

The automated check found no risky patterns in SKILL.md.

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 adobe/skills at commit cbc9952, republished under its Apache-2.0 licence (© adobe). 1,254 words, ~3,701 tokens.

Download SKILL.mdSave it as .claude/skills/snowflake/SKILL.md (or your agent's skills folder). This skill also uses 54 other files; get the full folder from GitHub.
name
snowflake
description
Use this when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived, etc.) into an Edge Delivery Services page while preserving the original design and making content authorable in Document Authoring — triggers include "convert this page to EDS", "static-to-EDS overlay", "convert to EDS blocks", "next experimentation", "next run", "start run", or providing a source URL to make editable in DA. Covers two modes — page-level (overlay template with slot markers) and block-level (each section becomes an independent EDS block). For canonical EDS block-rewrite migrations use page-import instead.
license
Apache-2.0
metadata.version
1.2.0

Snowflake — Static-to-EDS Conversion

Convert a static HTML page into an EDS page while preserving the original design and making content authorable in Document Authoring. Two conversion levels are supported:

  • Page-level (overlay) — the original DOM is preserved byte-for-byte via a template with [data-slot] markers. One template, one CSS file, one DA doc with slot-keyed rows.
  • Block-level — each content section becomes an independent EDS block with its own decorate() function and CSS. Content is authored in DA block tables. Header and footer stay as static fragments.

Both levels keep the original visual design intact. Page-level is the safer default; block-level produces more standard EDS output but requires section independence in the source page.

When to use

The user has an AI-generated polished static HTML page and wants to launch it on Edge Delivery Services without losing the original design while still making content editable in DA. Typical phrasing:

  • "Convert https://example.com/static-page to EDS"
  • "Make this page editable in DA but keep the original markup"
  • "Convert this page to EDS blocks" (signals level=block)
  • "Start the next experimentation for URL …"
  • "Static-to-EDS overlay for …" (signals level=page)

What this skill does NOT do

Not for canonical EDS block-rewrite migrations — that's page-import. Snowflake preserves the source design; page-import rewrites to standard EDS block patterns with no visual fidelity target. Three asset strategies are supported (see knowledge/methodology.md §3): absolute, vendor, da-media.

Parameters

ParameterValuesDefaultDescription
levelpage, auto, check, blockpageConversion level — see below
level values
ValueBehavior
autoRun the feasibility analysis in Phase 2, present the recommendation, ask the user to confirm before Phase 3
checkRun the feasibility analysis only — produce the report in decisions.json, stop before Phase 3. Useful for batch scanning
blockBlock-level conversion. Analysis still runs as validation (written to decisions.json) but does not gate the conversion
pagePage-level conversion (standard overlay). Analysis still runs as validation but does not gate the conversion

When level is not provided and the user's phrasing signals intent, infer it:

  • "convert to EDS blocks", "block-level" → level=block
  • "overlay", "preserve the DOM", "snowflake overlay" → level=page
  • Neutral phrasing → level=page
Usage examples
/snowflake https://example.com/promo              → page-level; infer repo, daRoot, slug
/snowflake https://example.com/promo level=block  → block-level, infer the rest
/snowflake https://example.com/promo level=auto   → feasibility analysis decides
/snowflake level=check                            → feasibility scan only (asks for URL)
/snowflake                                        → page-level, fully interactive

The Source URL is the leading positional input and the only required argument. Everything else is resolved automatically and presented in a single confirmation summary before any work begins.

Skill dependencies

Snowflake cites DA HTML rules and the DA admin API contract from the da-content skill. Load da-content alongside Snowflake. Phases 3 (Generate) and 5 (Round-trip) reference it directly.

Prerequisites

Required — the only input the skill cannot resolve on its own:

  1. Source URL — the static page to convert. Must be reachable (publicly hosted or local dev server).

Resolved automatically — shown in the init summary for one-shot confirmation before any work begins:

  1. Target EDS repo — detected via gh repo view --json nameWithOwner, falling back to parsing git remote get-url origin. Must already have the overlay engine wired (see knowledge/architecture.md §"Solution shape"). Phase 0 installs it if absent.
  2. DA root path — read from .snowflake/config.json daRoot key if set, otherwise defaults to the current git branch name (the same branch the skill uses for code). Shown in summary; override inline.
  3. Conversion level — inferred from phrasing (see Parameters), else page. Shown in summary; override inline.
  4. Slug / template name — derived from the source URL (kebab-case, ≤30 chars). Shown in summary; override inline.

Auth check (non-blocking) — DA token resolved from $DA_TOKEN → ~/.aem/da-token.json. Its status appears in the init summary. Phases 1–4 do not need it; if absent at invocation time, invoke the da-auth skill before Phase 5 (Round-trip) runs.

Initialization

On every invocation the agent performs these steps before entering Phase 0:

  1. Resolve inputs — apply the fast-path rules from the Prerequisites section above.

  2. Probe substrate —

    bash
    node <SKILL_DIR>/scripts/install-substrate.mjs --dry-run

    Captures the outcome (no-op / clean-install / drift / custom-code-detected).

  3. Check DA token —

    bash
    DA_TOKEN=$(node -e "
      const fs = require('fs');
      const p = process.env.HOME + '/.aem/da-token.json';
      try {
        const t = JSON.parse(fs.readFileSync(p, 'utf8'));
        if (t.expires_at > Date.now() + 60000) process.stdout.write(t.access_token);
      } catch {}
    ")

    Non-blocking — records status for the summary only.

  4. Always display the run parameters before any phase begins. Show this summary unconditionally — even when all values were provided upfront or inferred without ambiguity — then proceed immediately without waiting for confirmation:

    Source URL : https://example.com/promo   ← required (provided)
    Target repo: acme/my-site                ← detected from git
    DA root    : /main                        ← from current branch
    Level      : page                        ← default
    Slug       : promo                       ← derived from URL
    Substrate  : clean install — 9 files     ← (or: already current ✓)
    DA token   : cached ✓                    ← (or: not found — needed at Phase 5)

    Proceed without pausing for the common case (fresh install — no snowflake substrate yet; replaced files are backed up). Only pause for drift (a prior snowflake substrate that diverged), where overwriting could lose intentional customization — Phase 0 handles that case.

  5. Proceed — Phase 0 → 1 → … → 6 in order.

Show full SKILL.md (548 more words)Show less

Quick start — end-to-end example

From the target EDS repository root, here's the full seven-phase conversion in compressed form. Each phase file under phases/ holds the complete prompt; this is the shape of the actual commands the agent emits.

bash
# Inputs (resolved during init, confirmed in the summary)
SOURCE_URL="https://example.com/promo"
PAGE_SLUG="promo"
DA_ROOT="/main"                       # defaults to current branch name
NNN=001                           # next run number
PROJECT=".snowflake/projects/${NNN}-${PAGE_SLUG}"
TEMPLATE_NAME="promo"
LEVEL="page"                      # page | auto | check | block

# Phase 0 — install (or verify) the overlay substrate (once per repo)
node "<SKILL_DIR>/scripts/install-substrate.mjs"

# Phase 1 — capture: fetch source + assets into the project folder
mkdir -p "$PROJECT/input"
curl -fsS "$SOURCE_URL" -o "$PROJECT/input/index.html"
# For JS-rendered pages, use a browser to get the fully rendered HTML instead

# Phase 2 — analyze: produce decisions.json (sections, slots, asset
# strategy, head-links, conversionLevel). Includes block-level
# feasibility assessment. If LEVEL=check, stop here.
# Driven by phases/2-analyze.md.

# Phase 3 — generate: produce 5 artifacts + DA-source body
# (templates/<tpl>.html, fragments/<tpl>/{header,footer}.html,
# styles/<tpl>.css, scripts/<tpl>-animations.js, da/<slug>.html).
# Driven by phases/3-generate.md.

# Phase 4 — wire: copy artifacts to EDS-served paths and build the
# drafts file. Driven by phases/4-wire.md.

# Phase 5 — round-trip: local dev server + production preview
npx -y @adobe/aem-cli up --html-folder drafts &
TOKEN="${DA_TOKEN:-$(jq -r .access_token ~/.aem/da-token.json)}"
git checkout -b "snowflake-${NNN}" && git add . && git commit -m "snowflake #${NNN}"
git push -u origin "snowflake-${NNN}"
curl -X PUT -H "Authorization: Bearer $TOKEN" \
  -F "data=@${PROJECT}/output/da/${PAGE_SLUG}.html;type=text/html" \
  "https://admin.da.live/source/${OWNER}/${REPO}${DA_ROOT}/${PAGE_SLUG}.html"
curl -X POST -H "Authorization: Bearer $TOKEN" \
  "https://admin.hlx.page/preview/${OWNER}/${REPO}/snowflake-${NNN}${DA_ROOT}/${PAGE_SLUG}"
# Verify at https://snowflake-${NNN}--${REPO}--${OWNER}.aem.page/${DA_ROOT}/${PAGE_SLUG}

# Phase 6 — reflect: append findings to $PROJECT/learnings.md;
# promote cross-project rules to knowledge/learnings.md.

<SKILL_DIR> is the absolute path to the directory containing this SKILL.md. The agent substitutes it before invoking — see HOST-NOTES.md for per-host resolution rules.

The seven phases (sequential)

Each phase is a self-contained markdown file with executable bash + Node. The agent reads the phase prompt, runs its steps, updates state.json at the project root (<projectsDir>/<NNN>-<slug>/state.json), and proceeds. Reruns are safe — phases skip work already done.

  1. Prerequisites — install/verify the overlay substrate; stamp .snowflake/config.json. Runs once per repo. See phases/0-prereq.md.

  2. Capture — fetch source HTML and referenced external assets; create the project folder. See phases/1-capture.md.

  3. Analyze — structural map: header/footer boundaries, section list, slot opportunities, head-level links to lift, asset strategy. Also runs the block-level feasibility assessment — see knowledge/block-level-feasibility.md. Includes a page complexity gate: pages with >8 sections or >100 slottable elements auto-switch from page-level to block-level to avoid incomplete content extraction (see phases/2-analyze.md). Produces notes.md + decisions.json (including conversionLevel). See phases/2-analyze.md.

  4. Generate — branches by conversionLevel from Phase 2:

    • page: produce the 5 overlay artifacts (template HTML, header fragment, footer fragment, page CSS, animations JS) plus the DA-source body with slot-keyed rows.
    • block: produce per-section block JS/CSS, header/footer fragments, global styles/tokens, and the DA-source body with standard block tables.
    • hybrid: block-level for passing sections, page-level fragments for failing sections. Both page and block are supported under either substrate flavor (eds or milo). All Milo-specific deltas — chrome metadata, page-level/block-level generation, the --pa-* animation sidecars, and wiring — live in assets/substrate-milo/FLAVOR.md; the phase docs carry a gated pointer to it. The core skill stays substrate-neutral. See phases/3-generate.md.
  5. Wire — copy artifacts to EDS-served paths, build the local-test drafts file, run lint. See phases/4-wire.md.

  6. Round-trip — local (dev server) then production (branch + push + DA PUT + preview API). Enforces a browser health gate on both: the page must render (not blank), apply the overlay, match the source structure, be free of console/network errors, and pass the 1:1 DOM-equality check before the run may continue. See phases/5-roundtrip.md.

  7. Reflect — append run findings; promote cross-project learnings to knowledge/learnings.md. Does not close the iteration — that's a user decision. See phases/6-reflect.md.

Knowledge resolution per phase: each phase tries .snowflake/knowledge/<file>.md (project-specific override) first, then <SKILL_DIR>/knowledge/<file>.md (bundled, canonical). Project overrides win on conflict.

Reading order

Load knowledge just-in-time — only when the phase that needs it begins.

On invocation (before Phase 0):

  1. This file.
  2. knowledge/methodology.md — canonical phase rules.
  3. Confirm the da-content skill is loadable (needed by phases 3 and 5).

At Phase 2 (Analyze): 4. knowledge/block-level-feasibility.md — criteria for block-level vs page-level conversion.

At Phase 3 (Generate): 5. knowledge/architecture.md — overlay engine and slot writer semantics. 6. knowledge/block-level-conversion.md — architecture and patterns for block-level conversion. 7. knowledge/learnings.md — cross-project findings relevant to generation.

At Phase 5 (Round-trip): 8. knowledge/eds-da-mechanics.md — EDS pipeline overlay-runtime lore. 9. knowledge/learnings.md — entries on media handling, CORS, scroll-animation quirks (if not already loaded).

Then start at Phase 0.

Further reading (not loaded by the agent)

  • README.md — human-readable overview, install commands, contribution guidelines.
  • HOST-NOTES.md — per-host adapter notes (Slicc, Claude Code, generic shell), <SKILL_DIR> path resolution rules, .snowflake/ directory convention, and forbidden cross-host primitives (for maintainers).
  • examples/README.md — pointers to worked examples from closed iterations.

© adobe, Apache-2.0. 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 54 other files (scripts, assets) in plugins/aem/edge-delivery-services/skills/snowflake of adobe/skills.

  • SKILL.md
  • .releaserc.json
  • CHANGELOG.md
  • HOST-NOTES.md
  • README.md
  • assets/substrate-milo/FLAVOR.md
  • assets/substrate-milo/MANIFEST.json
  • assets/substrate-milo/VERSION
  • assets/substrate-milo/animation-sidecars.md
  • assets/substrate-milo/blocks/animation/animation.css
  • assets/substrate-milo/blocks/animation/animation.js
  • assets/substrate-milo/blocks/snowflake/snowflake.css
  • assets/substrate-milo/blocks/snowflake/snowflake.js
  • assets/substrate-milo/tools/page-animator/controls.js
  • … and 41 more

Open the folder on GitHubat commit cbc9952

Compare with similar skills

Snowflake 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.

Snowflake compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Snowflake this skilladobe/skills195—~3.7kAutomated safety check: PassApache-2.0
Data Warehouse Experimentationrampstackco/claude-skills935—~7.3kAutomated safety check: PassMIT
Caspian DiscordTryCaspian/caspian-sdk971—~323Automated safety check: PassApache-2.0
Write Script Snowflakewindmill-labs/windmill18k—~2.2kAutomated safety check: PassCustom licence
Pure Lsp Execute Parallelfinos/legend-engine112—~927Automated safety check: PassApache-2.0
Schema Design InterviewerPrepLabsAI/InterviewMentor112—~8.2kAutomated safety check: PassMIT

Similar skills

  • Data Warehouse Experimentation

    rampstackco/claude-skills

    Running experiments out of the data warehouse instead of via dedicated experiment platforms.

    935 GitHub stars~7.3k tokensUpdated today
    DatabasesAuto-check passed
  • Caspian Discord

    TryCaspian/caspian-sdk

    Post a Discord message via Caspian to a channel snowflake id.

    971 GitHub stars~323 tokensUpdated 1 mo ago
    DatabasesAuto-check passed
  • Write Script Snowflake

    windmill-labs/windmill

    MUST use when writing Snowflake queries. An agent skill from windmill-labs/windmill.

    18k GitHub stars~2.2k tokensUpdated today
    DatabasesAuto-check passed
  • Pure Lsp Execute Parallel

    finos/legend-engine

    Runs 2 to 30 Pure functions or tests concurrently on the warm LSP daemon via pure-lsp execute-parallel, or every test in a package or .pure file with --package/--source.

    112 GitHub stars~927 tokensUpdated today
    DatabasesAuto-check passed
  • Schema Design Interviewer

    PrepLabsAI/InterviewMentor

    A Data Warehouse and Lakehouse Schema Design Expert interviewer focused on dimensional modeling, star/snowflake schemas, analytics optimization, and modern lakehouse architectures.

    112 GitHub stars~8.2k tokensUpdated today
    DatabasesAuto-check passed
  • Data Modeler

    FerroxLabs/wayland

    Expert data modeling covering star schema, snowflake schema, Data Vault 2.0, dimensional modeling, slowly changing dimensions, bridge tables, fact table types, conformed dimensions, ERD creation…

    608 GitHub stars~5.2k tokensUpdated yesterday
    DatabasesAuto-check passed

More from adobe/skills

All 105 skills in this repo
  • Scaffolds, implements, deploys and debugs Adobe Runtime actions in App Builder projects, with templates for webhooks, events, database CRUD, sequences and Asset Compute workers.

    195 GitHub stars~3.1k tokensUpdated today
    Auto-check passed
  • Launches Chrome with an unpacked extension over CDP, opens its sidepanel, popup or options page, and hands over to cdp-connect for clicks, typing and screenshots.

    195 GitHub stars~952 tokensUpdated today
    Auto-check passed
  • Extracts icons, metadata, text, forms, videos and social links from any web page with playwright-cli, with SVG icon classification and cleanup.

    195 GitHub stars~1k tokensUpdated today
    Auto-check passed
  • Page Langs

    adobe/skills

    Detect all languages used on a webpage — both declared (html@lang, hreflang alternate links, nested lang= attributes, meta content-language) and actually present in the body text (Google CLD3 via…

    195 GitHub stars~1.1k tokensUpdated today
    Auto-check passed
  • Page Prep

    adobe/skills

    Prepare any webpage for clean interaction by detecting and removing disruptive overlays (cookie banners, GDPR consent, modals, popups, newsletter signups, paywalls, login walls).

    195 GitHub stars~2.1k tokensUpdated today
    Auto-check passed
  • Page Reduce

    adobe/skills

    Reduce a webpage to a structural skeleton with semantic tokens.

    195 GitHub stars~1.9k tokensUpdated today
    Auto-check passed

Categories

Questions about Snowflake

What does Snowflake do?

Use this when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived, etc.) into an Edge Delivery Services page while preserving the original design and…. Snowflake is an agent skill from adobe/skills.) into an Edge Delivery Services page while preserving the original design and making content authorable in Document Authoring — triggers include "convert this page to EDS", "static-to-EDS overlay", "convert to EDS blocks", "next experimentation", "next run", "start run", or providing a source URL to make editable in DA.

When should I use Snowflake?

Snowflake fits situations like: include convert this page to EDS; static-to-EDS overlay; convert to EDS blocks; Next experimentation.

How do I install Snowflake in Claude Code?

Run `npx skills add adobe/skills --skill snowflake -a claude-code`. Or copy the skill folder (plugins/aem/edge-delivery-services/skills/snowflake in adobe/skills) into .claude/skills/snowflake in your project. Claude Code loads it when a task matches its description.

How do I install Snowflake in Codex?

Run `npx skills add adobe/skills --skill snowflake -a codex`. Or copy the skill folder (plugins/aem/edge-delivery-services/skills/snowflake in adobe/skills) into .agents/skills/snowflake in your project. Codex loads it when a task matches its description.

Can I use Snowflake 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 adobe/skills --skill snowflake -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/snowflake, .gemini/skills/snowflake, .github/skills/snowflake and .opencode/skills/snowflake in your project.

What does Snowflake need to run?

Going by SKILL.md and its folder, Snowflake needs JavaScript for the scripts in its folder, the command-line tools its instructions call (git, node, curl, npx, jq and gh) and credentials named DA_TOKEN. Our summary lists: Node.js.

Does Snowflake access the network?

SKILL.md names 2 domains. In commands or code: admin.da.live and admin.hlx.page; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Snowflake safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Snowflake use?

Snowflake is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Snowflake use?

About 3.7k tokens (SKILL.md is roughly 15k 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 Snowflake?

Skills that share tags, products or a category with Snowflake: Data Warehouse Experimentation (rampstackco/claude-skills, 935 stars), Caspian Discord (TryCaspian/caspian-sdk, 971 stars), Write Script Snowflake (windmill-labs/windmill, 18k stars) and Pure Lsp Execute Parallel (finos/legend-engine, 112 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Snowflake?

adobe (a GitHub organization) maintains it in adobe/skills, which has 195 GitHub stars. The repository holds 105 skills in this directory. The repository was last updated on October 6, 2026.

Source: adobe/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.