Algolia Core Workflow A — Search & Filtering
SkillSearchLets your agent add Algolia search to an app with filters, facets, highlighting, and pagination.
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Then ask your AI: use the Algolia Core Workflow A — Search & Filtering skill
About this capability
Implement or review a single-index Algolia search contract with filters, facets, pagination, and highlighting. Use when building product or content search against the JavaScript v5 client. Trigger with "Algolia search workflow", "add facets", or "searchSingleIndex".
What this skill tells your AI
The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/algolia-core-workflow-a/SKILL.md and read by ahel’s review.
Overview
Primary Algolia workflow: full-text search with filters, faceted navigation, hit highlighting, and pagination. Uses searchSingleIndex (v5) with real Algolia search parameters.
Prerequisites
- Completed
algolia-install-authandalgolia-hello-worldsetup - Index populated with records (see
algolia-hello-world) - Index settings configured with
searchableAttributesandattributesForFaceting
Instructions
Step 1: Configure Index for Filtering
import { algoliasearch } from 'algoliasearch';
const client = algoliasearch(process.env.ALGOLIA_APP_ID!, process.env.ALGOLIA_ADMIN_KEY!);
await client.setSettings({
indexName: 'products',
indexSettings: {
// What to search (ordered = priority matters)
searchableAttributes: ['name', 'description', 'brand', 'category'],
// What to filter/facet on — prefix with filterOnly() if no facet counts needed
attributesForFaceting: [
'searchable(brand)', // Searchable facet: users can search within brand values
'category', // Regular facet: shown in facet panels
'filterOnly(price)', // Filter only: no counts computed, saves CPU
'filterOnly(in_stock)',
],
// Custom ranking: tie-breaker after Algolia's relevance ranking
customRanking: ['desc(sales_count)', 'desc(rating)'],
// What comes back in hits
attributesToRetrieve: ['name', 'brand', 'price', 'image_url', 'category'],
attributesToHighlight: ['name', 'description'],
attributesToSnippet: ['description:30'], // 30-word snippet
},
});
Step 2: Search with Filters
// Algolia filter syntax uses SQL-like expressions
const { hits, nbHits, facets } = await client.searchSingleIndex({
indexName: 'products',
searchParams: {
query: 'running shoes',
// Numeric/boolean/string filters
filters: 'price < 150 AND in_stock = true',
// OR: facetFilters for UI-driven filtering (array = OR, nested = AND)
// facetFilters: [['category:shoes', 'category:sneakers'], ['brand:Nike']],
// ^ shoes OR sneakers, AND brand is Nike
// Numeric range filters
numericFilters: ['price >= 50', 'price <= 150'],
// Request facet counts for these attributes
facets: ['category', 'brand'],
// Pagination
hitsPerPage: 20,
page: 0,
// Highlighting
highlightPreTag: '<mark>',
highlightPostTag: '</mark>',
},
});
console.log(`${nbHits} results found`);
// Access facet counts for building filter UI
// facets = { category: { shoes: 42, sneakers: 18 }, brand: { Nike: 30, Adidas: 25 } }
for (const [facetName, values] of Object.entries(facets || {})) {
console.log(`${facetName}:`);
for (const [value, count] of Object.entries(values)) {
console.log(` ${value}: ${count}`);
}
}
Step 3: Display Highlighted Results
hits.forEach(hit => {
// _highlightResult contains highlighted versions of each field
const highlighted = hit._highlightResult;
const name = highlighted?.name?.value || hit.name;
const snippet = hit._snippetResult?.description?.value || '';
console.log(`${name} — $${hit.price}`);
if (snippet) console.log(` ${snippet}`);
});
Step 4: Implement Pagination
async function paginatedSearch(query: string, page: number = 0) {
const { hits, nbHits, nbPages, hitsPerPage } = await client.searchSingleIndex({
indexName: 'products',
searchParams: {
query,
hitsPerPage: 20,
page,
},
});
return {
hits,
totalHits: nbHits,
totalPages: nbPages,
currentPage: page,
hasMore: page < nbPages - 1,
};
}
Output
The configured index returns paginated, highlighted search hits with the requested filters and facets. The examples also show how to extend that baseline to federated and optional-filter search without changing the indexing contract.
Error Handling
| Error | Cause | Solution |
|---|---|---|
Invalid filter syntax | Malformed filters string | Check filter syntax: field:value, field < N, use AND/OR/NOT |
Attribute not valid for filtering | Field not in attributesForFaceting | Add field to attributesForFaceting in settings |
0 results unexpectedly | Typo tolerance may be disabled | Check typoTolerance setting; verify data is indexed |
| Stale results after update | Didn't wait for task | Use await client.waitForTask() after indexing |
Examples
Multi-Index Search (Federated)
const { results } = await client.search({
requests: [
{ indexName: 'products', query: 'laptop', hitsPerPage: 5 },
{ indexName: 'articles', query: 'laptop', hitsPerPage: 3 },
],
});
// results[0].hits = product hits, results[1].hits = article hits
Search with Optional Filters (boost, not require)
const { hits } = await client.searchSingleIndex({
indexName: 'products',
searchParams: {
query: 'shoes',
optionalFilters: ['brand:Nike'], // Nike products ranked higher but not required
},
});
Resources
Next Steps
For indexing and data sync workflows, see algolia-core-workflow-b.
Signals
- GitHub stars
- 3k
- Forks
- 396
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
algolia-core-workflow-a- Source
- github.com/jeremylongshore/tons-of-skills-marketplace