plugins/aem/edge-delivery-services/skills/snowflake/SKILL.md
Static-to-EDS conversion that preserves the original design while making content authorable in Document Authoring. Two modes — page-level (overlay template with slot markers) and block-level (each section becomes an independent EDS block). Use when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived hand-coded, etc.) into an Edge Delivery Services page. Triggers on "convert this page to EDS", "static-to-EDS overlay", "convert to EDS blocks", "next experimentation", "next run", "start run", or when a user provides a source URL and asks to make it editable in DA while keeping the original design intact. Do NOT use for canonical EDS block-rewrite migrations — that's the page-import skill.
npx skillsauth add adobe/skills snowflakeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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:
[data-slot] markers. One
template, one CSS file, one DA doc with slot-keyed rows.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.
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:
level=block)level=page)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.
| Parameter | Values | Default | Description |
|-----------|--------|---------|-------------|
| level | page, auto, check, block | page | Conversion level — see below |
level values| Value | Behavior |
|-------|----------|
| auto | Run the feasibility analysis in Phase 2, present the recommendation, ask the user to confirm before Phase 3 |
| check | Run the feasibility analysis only — produce the report in decisions.json, stop before Phase 3. Useful for batch scanning |
| block | Block-level conversion. Analysis still runs as validation (written to decisions.json) but does not gate the conversion |
| page | Page-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:
level=blocklevel=pagelevel=page/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.
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.
Required — the only input the skill cannot resolve on its own:
Resolved automatically — shown in the init summary for one-shot confirmation before any work begins:
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..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.page. Shown in summary; override inline.Auth check (non-blocking) — DA token resolved from $DA_TOKEN →
~/.aem/da-token.json. Its status appears in the init summary. Phases
1–4 do not need it; if absent at invocation time, invoke the da-auth
skill before Phase 5 (Round-trip) runs.
On every invocation the agent performs these steps before entering Phase 0:
Resolve inputs — apply the fast-path rules from the Prerequisites section above.
Probe substrate —
node <SKILL_DIR>/scripts/install-substrate.mjs --dry-run
Captures the outcome (no-op / clean-install / drift / custom-code-detected).
Check DA token —
DA_TOKEN=$(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.
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.
Proceed — Phase 0 → 1 → … → 6 in order.
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.
# 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.
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.
Prerequisites — install/verify the overlay substrate; stamp
.snowflake/config.json. Runs once per repo.
See phases/0-prereq.md.
Capture — fetch source HTML and referenced external assets; create the project folder. See phases/1-capture.md.
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.
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.
See phases/3-generate.md.Wire — copy artifacts to EDS-served paths, build the local-test drafts file, run lint. See phases/4-wire.md.
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.
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.
Load knowledge just-in-time — only when the phase that needs it begins.
On invocation (before Phase 0):
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.
<SKILL_DIR> path resolution rules,
.snowflake/ directory convention, and forbidden cross-host
primitives (for maintainers).development
Start AEM Workflows on AEM as a Cloud Service using all available triggering mechanisms. Use when starting workflows manually via the Timeline UI, programmatically via WorkflowSession.startWorkflow(), via the HTTP Workflow API, through Manage Publication, or passing initial metadata and payload to a workflow instance.
development
Single entry point for all AEM as a Cloud Service Workflow skills. Covers workflow model design, custom process step and participant chooser development, launcher configuration, workflow triggering, and production support including debugging stuck/failed workflows, triaging incidents with Cloud Manager logs, thread pool analysis, and Sling Job diagnostics for the Granite Workflow Engine.
development
[BETA] Implement custom AEM Workflow Java components on AEM as a Cloud Service. This skill is in beta. Verify all outputs before applying them to production projects. Use when writing WorkflowProcess steps, ParticipantStepChooser implementations, registering services via OSGi DS R6 annotations, reading step arguments from MetaDataMap, accessing JCR payload via WorkflowSession adapter, reading and writing workflow metadata and variables, and handling errors with WorkflowException for retry behavior.
development
Start AEM Workflows on AEM 6.5 LTS using all available triggering mechanisms. Use when starting workflows manually via the Timeline UI, programmatically via WorkflowSession.startWorkflow(), via the HTTP Workflow API, through Manage Publication, through replication triggers, or passing initial metadata and payload to a workflow instance.