Page Reduce

What it does

When your agent uses it

• Migrating pages to EDS
• Analyzing page structure
• Extracting page blueprints
• Preparing input for GenAI block generation

Example prompts

• “/page-reduce”

Requirements

• Node.js
• Compatibility (from SKILL.md): Requires playwright-cli on PATH. Run `playwright-cli --help` for usage.

Workflow steps

6 steps, taken from the step headings in SKILL.md.

1. 1Open the URL
2. 2Navigate and prepare the page
3. 3Inject the bundle and run Phase 1
4. 4Phase 2: Structural reasoning
5. 5Generate output files
6. 6Report summary

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), which the agent can run.

  Shell commands in SKILL.md call:

  • npm

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

• Network

  No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

  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

  Requires playwright-cli on PATH. Run `playwright-cli --help` for usage.

  From compatibility in the SKILL.md frontmatter.

Context cost

Page Reduce loads about 1.9k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 175 tokens; SKILL.md has 533 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~175

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~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

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). 533 words, ~1,870 tokens.

name

page-reduce

description

Reduce a webpage to a structural skeleton with semantic tokens. Two-phase pipeline: Phase 1 injects a browser script that tokenizes content ({TEXT}, {HEADING:n}, {IMAGE:WxH}, {CTA:label}, {LINK:label}, {INPUT:type}, {VIDEO}, {ICON}). Phase 2 applies LLM structural reasoning to collapse repeated patterns ({REPEAT:N}), remove decorative wrappers, strip utility classes, and produce skeleton.html + manifest.json. Use when migrating pages to EDS, analyzing page structure, extracting page blueprints, or preparing input for GenAI block generation. Triggers on: reduce page, page skeleton, page blueprint, extract structure, tokenize page, page reduction, structural skeleton, reduce URL.

compatibility

Requires playwright-cli on PATH. Run `playwright-cli --help` for usage.

license

Apache-2.0

/page-reduce <URL>

if [[ -n "${CLAUDE_SKILL_DIR:-}" ]]; then
  BUNDLE="${CLAUDE_SKILL_DIR}/scripts/page-reduce-bundle.js"
else
  BUNDLE="$(find ~/.claude \
    -path "*/page-reduce/scripts/page-reduce-bundle.js" \
    -type f 2>/dev/null | head -1)"
fi

REDUCE_CONFIG="/tmp/reduce-config-$$.json"
BOOTSTRAP="/tmp/reduce-bootstrap-$$.js"

# Bootstrap: runs async detection after page load, stores result
cat > "$BOOTSTRAP" << 'EOF'
window.addEventListener('load', async () => {
  await window.xp.detectSections(document.body, window, {
    autoDetect: true,
    highlightBoxes: false,
    highlightSections: false,
  });
  window.__reduceResult = window.__reduceForSkill(document.body, window);
});
EOF

# Config: inject bundle first (exposes window.xp + window.__reduceForSkill),
# then bootstrap (runs detection after load)
echo "{\"browser\":{\"initScript\":[\"$BUNDLE\",\"$BOOTSTRAP\"]}}" > "$REDUCE_CONFIG"

# Open page — initScripts run before any page JS
URL="<target URL from /page-reduce input>"
playwright-cli open "$URL" --config="$REDUCE_CONFIG"
sleep 3  # wait for load + async detection to complete

# Read result — pure expression, no await needed
RESULT=$(playwright-cli eval "JSON.stringify(window.__reduceResult)")

rm -f "$REDUCE_CONFIG" "$BOOTSTRAP"

{
  "url": "...", "title": "...", "viewport": { "width": 1280 }, "templateHash": "...",
  "sections": [{ "index": 0, "sectionType": "hero", "xpath": "...", "tokenizedHtml": "...",
    "layout": { "numCols": 2, "numRows": 1 }, "features": ["hasHeading", "hasCTA"] }]
}

<!-- section:0 type:hero xpath:/html/body/main/section[1] -->
<section class="hero">
  <h1>{HEADING:1}</h1>
  <p>{TEXT}</p>
  {CTA:Get Started}
  {IMAGE:1200x600}
</section>

<!-- section:1 type:cards xpath:/html/body/main/div[2] -->
<div class="cards-container">
  <div class="card">
    {IMAGE:400x300}
    <h3>{HEADING:3}</h3>
    <p>{TEXT}</p>
    <a>{LINK:Read more}</a>
  </div>
  <div class="card">
    {IMAGE:400x300}
    <h3>{HEADING:3}</h3>
    <p>{TEXT}</p>
    <a>{LINK:Read more}</a>
  </div>
  {REPEAT:4}
</div>

cd <detector-repo>
npm run build        # builds dist/detect.js
npm run build:skill  # builds dist/reduce-for-skill.js
cat dist/detect.js dist/reduce-for-skill.js > <skills-repo>/skills/page-reduce/scripts/page-reduce-bundle.js

© 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 5 other files (scripts, references) in plugins/web/skills/page-reduce of adobe/skills.

• SKILL.md
• .releaserc.json
• evals/evals.json
• package.json
• references/PHASE2-RULES.md
• scripts/page-reduce-bundle.js

Open the folder on GitHubat commit cbc9952