How to use the fathom-web.score function in fathom-web

return scoreIfHas;
    }
    return 1;
};

const rules = ruleset(
    // Isolate the actual blog post body text. Based on Fathom's example
    // Readability rules
    rule(dom('p,li,ol,ul,code,blockquote,pre,h1,h2,h3,h4,h5,h6'),
        props(scoreByLength).type('paragraphish')),
    rule(type('paragraphish'), score(byInverseLinkDensity)),
    rule(dom('p'), score(4.5).type('paragraphish')),

    // Tweaks for this particular blog
    rule(type('paragraphish'), score(hasAncestor('article', 10))),
    rule(dom('.entry-summary p'), score(0).type('paragraphish')),
    rule(dom('figure'), props(scoreByImageSize).type('paragraphish')),

    // Find the best cluster of paragraph-ish nodes
    rule(
        type('paragraphish').bestCluster({
            splittingDistance: 3,
            differentDepthCost: 6.5,
            differentTagCost: 2,
            sameTagCost: 0.5,
            strideCost: 0,
        }),
        out('content').allThrough(Futils.domSort)));

async function ingestArticle(hatch, {title, link, date, author}) {
    let $ = await Libingester.util.fetch_html(link);
    const baseURI = Libingester.util.get_doc_base_uri($, link);

for (let element = fnode.element, parent;
        (parent = element.parentNode) != null &&
            parent.nodeType === parent.ELEMENT_NODE;
        element = parent) {
        if (element.tagName.toLowerCase() === lowerTag)
            return scoreIfHas;
    }
    return 1;
};

const rules = ruleset(
    // Isolate the actual blog post body text. Based on Fathom's example
    // Readability rules
    rule(dom('p,li,ol,ul,code,blockquote,pre,h1,h2,h3,h4,h5,h6'),
        props(scoreByLength).type('paragraphish')),
    rule(type('paragraphish'), score(byInverseLinkDensity)),
    rule(dom('p'), score(4.5).type('paragraphish')),

    // Tweaks for this particular blog
    rule(type('paragraphish'), score(hasAncestor('article', 10))),
    rule(dom('.entry-summary p'), score(0).type('paragraphish')),
    rule(dom('figure'), props(scoreByImageSize).type('paragraphish')),

    // Find the best cluster of paragraph-ish nodes
    rule(
        type('paragraphish').bestCluster({
            splittingDistance: 3,
            differentDepthCost: 6.5,
            differentTagCost: 2,
            sameTagCost: 0.5,
            strideCost: 0,
        }),

(parent = element.parentNode) != null &&
            parent.nodeType === parent.ELEMENT_NODE;
        element = parent) {
        if (element.tagName.toLowerCase() === lowerTag)
            return scoreIfHas;
    }
    return 1;
};

const rules = ruleset(
    // Isolate the actual blog post body text. Based on Fathom's example
    // Readability rules
    rule(dom('p,li,ol,ul,code,blockquote,pre,h1,h2,h3,h4,h5,h6'),
        props(scoreByLength).type('paragraphish')),
    rule(type('paragraphish'), score(byInverseLinkDensity)),
    rule(dom('p'), score(4.5).type('paragraphish')),

    // Tweaks for this particular blog
    rule(type('paragraphish'), score(hasAncestor('article', 10))),
    rule(dom('.entry-summary p'), score(0).type('paragraphish')),
    rule(dom('figure'), props(scoreByImageSize).type('paragraphish')),

    // Find the best cluster of paragraph-ish nodes
    rule(
        type('paragraphish').bestCluster({
            splittingDistance: 3,
            differentDepthCost: 6.5,
            differentTagCost: 2,
            sameTagCost: 0.5,
            strideCost: 0,
        }),
        out('content').allThrough(Futils.domSort)));

return scoreIfHas;
    }
    return 1;
};

const rules = ruleset(
    // Isolate the actual blog post body text. Based on Fathom's example
    // Readability rules
    rule(dom('p,li,ol,ul,code,blockquote,pre,h1,h2,h3,h4,h5,h6'),
        props(scoreByLength).type('paragraphish')),
    rule(type('paragraphish'), score(byInverseLinkDensity)),
    rule(dom('p'), score(4.5).type('paragraphish')),

    // Tweaks for this particular blog
    rule(type('paragraphish'), score(hasAncestor('article', 10))),
    rule(dom('.entry-summary p'), score(0).type('paragraphish')),
    rule(dom('figure'), props(scoreByImageSize).type('paragraphish')),
    rule(dom('.jetpack-video-wrapper'), props(() => ({
        score: 100,
        note: {length: 1},
    })).type('paragraphish')),

    // Find the best cluster of paragraph-ish nodes
    rule(
        type('paragraphish').bestCluster({
            splittingDistance: 3,
            differentDepthCost: 6.5,
            differentTagCost: 2,
            sameTagCost: 0.5,
            strideCost: 0,
        }),
        out('content').allThrough(Futils.domSort)));

for (let element = fnode.element, parent;
        (parent = element.parentNode) != null &&
            parent.nodeType === parent.ELEMENT_NODE;
        element = parent) {
        if (element.tagName.toLowerCase() === lowerTag)
            return scoreIfHas;
    }
    return 1;
};

const rules = ruleset(
    // Isolate the actual blog post body text. Based on Fathom's example
    // Readability rules
    rule(dom('p,li,ol,ul,code,blockquote,pre,h1,h2,h3,h4,h5,h6'),
        props(scoreByLength).type('paragraphish')),
    rule(type('paragraphish'), score(byInverseLinkDensity)),
    rule(dom('p'), score(4.5).type('paragraphish')),

    // Tweaks for this particular blog
    rule(type('paragraphish'), score(hasAncestor('article', 10))),
    rule(dom('.entry-summary p'), score(0).type('paragraphish')),
    rule(dom('figure'), props(scoreByImageSize).type('paragraphish')),
    rule(dom('.jetpack-video-wrapper'), props(() => ({
        score: 100,
        note: {length: 1},
    })).type('paragraphish')),

    // Find the best cluster of paragraph-ish nodes
    rule(
        type('paragraphish').bestCluster({
            splittingDistance: 3,
            differentDepthCost: 6.5,

*/
const scoreByLength = ({ element }) => ({
    score: inlineTextLength(element),
})

// Based on: https://hacks.mozilla.org/2017/04/fathom-a-framework-for-understanding-web-pages/
// Meant to be similar to Readability-like extraction of a page's main-content
// Initial tests of this are pretty innaccurate; lots to learn to be able to tweak the rules and use it well
const rules = ruleset(
    rule(
        dom('p,div,li,blockquote,h1,h2,h3,h4,h5,h6'),
        props(scoreByLength).type('paragraphish'),
    ),
    rule(
        type('paragraphish'),
        score(fnode => {
            const paragraphishNote = fnode.noteFor('paragraphish')
            return paragraphishNote
                ? (1 - linkDensity(fnode, paragraphishNote.inlineLength)) * 1.5
                : (1 - linkDensity(fnode)) * 1.5
        }),
    ),
    rule(dom('p'), score(4.5).type('paragraphish')),
    rule(
        type('paragraphish').bestCluster({
            splittingDistance: 3,
            differentDepthCost: 6.5,
            differentTagCost: 2,
            sameTagCost: 0.5,
            strideCost: 0,
        }),
        out('content').allThrough(domSort),

makeRuleset(coeffs, biases) {
    return ruleset([
      /**
       * Image rules
       */
      // consider all visible img elements
      rule(dom('img').when(this.isVisible.bind(this)), note(() => ({isVisible: true})).type('image')),
      // and divs, which sometimes have CSS background-images
      // TODO: Consider a bonus for <img> tags.
      rule(dom('div').when(fnode =&gt; this.isVisible(fnode) &amp;&amp; this.hasBackgroundImage(fnode)), type('image')),
      // better score the closer the element is to the top of the page
      rule(type('image'), score(this.isAboveTheFold.bind(this)), {name: 'isAboveTheFoldImage'}),
      // better score for larger images
      rule(type('image'), score(this.isBig.bind(this)), {name: 'isBig'}),
      // bonus for non-extreme aspect ratios, to filter out banners or nav elements
      // TODO: Meant to make this a penalty, but it turns out to work as is.
      // Try as a penalty.
      rule(type('image'), score(this.hasSquareAspectRatio.bind(this)), {name: 'hasSquareAspectRatio'}),
      // no background images, even ones that have reasonable aspect ratios
      // TODO: If necessary, also look at parents. I've seen them say
      // "background" in their IDs as well.
      rule(type('image'), score(this.hasBackgroundInID.bind(this)), {name: 'hasBackgroundInID'}),
      // return image element(s) with max score
      rule(type('image').max(), out('image')),

      /**
       * Title rules
       */

function saturation(r, g, b) {
                const cMax = Math.max(r, g, b);
                const cMin = Math.min(r, g, b);
                const delta = cMax - cMin;
                const lightness = (cMax + cMin) / 2;
                const denom = (1 - (Math.abs(2 * lightness - 1)));
                // Return 0 if it's black (R, G, and B all 0).
                return (denom === 0) ? 0 : delta / denom;
            }

            /* The actual ruleset */

            const rules = ruleset([
                rule(dom('div'), type('overlay')),
                rule(type('overlay'), score(big), {name: 'big'}),
                rule(type('overlay'), score(nearlyOpaque), {name: 'nearlyOpaque'}),
                rule(type('overlay'), score(monochrome), {name: 'monochrome'}),
                rule(type('overlay'), score(suspiciousClassOrId), {name: 'classOrId'}),
                rule(type('overlay'), score(visible), {name: 'visible'}),
                rule(type('overlay').max(), out('overlay'))
            ]);
            return rules;
        }
    }

if (element.tagName.toLowerCase() === lowerTag)
            return scoreIfHas;
    }
    return 1;
};

const rules = ruleset(
    // Isolate the actual blog post body text. Based on Fathom's example
    // Readability rules
    rule(dom('p,li,ol,ul,code,blockquote,pre,h1,h2,h3,h4,h5,h6'),
        props(scoreByLength).type('paragraphish')),
    rule(type('paragraphish'), score(byInverseLinkDensity)),
    rule(dom('p'), score(4.5).type('paragraphish')),

    // Tweaks for this particular blog
    rule(type('paragraphish'), score(hasAncestor('article', 10))),
    rule(dom('.entry-summary p'), score(0).type('paragraphish')),
    rule(dom('figure'), props(scoreByImageSize).type('paragraphish')),

    // Find the best cluster of paragraph-ish nodes
    rule(
        type('paragraphish').bestCluster({
            splittingDistance: 3,
            differentDepthCost: 6.5,
            differentTagCost: 2,
            sameTagCost: 0.5,
            strideCost: 0,
        }),
        out('content').allThrough(Futils.domSort)));

async function ingestArticle(hatch, {title, link, date, author}) {
    let $ = await Libingester.util.fetch_html(link);

const cMin = Math.min(r, g, b);
                const delta = cMax - cMin;
                const lightness = (cMax + cMin) / 2;
                const denom = (1 - (Math.abs(2 * lightness - 1)));
                // Return 0 if it's black (R, G, and B all 0).
                return (denom === 0) ? 0 : delta / denom;
            }

            /* The actual ruleset */

            const rules = ruleset([
                rule(dom('div'), type('overlay')),
                rule(type('overlay'), score(big), {name: 'big'}),
                rule(type('overlay'), score(nearlyOpaque), {name: 'nearlyOpaque'}),
                rule(type('overlay'), score(monochrome), {name: 'monochrome'}),
                rule(type('overlay'), score(suspiciousClassOrId), {name: 'classOrId'}),
                rule(type('overlay'), score(visible), {name: 'visible'}),
                rule(type('overlay').max(), out('overlay'))
            ]);
            return rules;
        }
    }