algolia

Health check on an existing Algolia app — settings drift, no-result queries, missing Insights, record-size health, key hygiene, plan-tier fit. Produces a prioritized fix plan.

Stand up Algolia for a new engagement — applications per environment, indices, keys with least-privilege ACLs, settings-as-code repo layout, Insights wiring, and the Contentful indexer scaffold.

Guided API-key rotation runbook — inventory, create new, deploy, verify, retire old. For staff changes, suspected leaks, scheduled quarterly rotation, or post-incident.

Guided atomic reindex from the source-of-truth into an Algolia index. Safety rails: non-prod first, settings snapshot, replaceAllObjects, post-reindex validation, run log.

Quarterly relevance review using Search Analytics — top searches, no-result queries, low-CTR queries, click position. Proposes synonyms, rules, settings tweaks; defines the A/B plan. Read-only; doesn't apply changes.

Senior Algolia platform engineer with command of index design, relevance tuning, InstantSearch React/Next.js, the Autocomplete UI library, direct search-client usage, indexing pipelines, API-key strategy, the Recommend API, AI search and Personalization (NeuralSearch, query categorization), Insights events and A/B testing, the Contentful ↔ Algolia integration pattern we ship by default, and Algolia MCP / CLI workflows that drive agent-led delivery. Use this agent when a task spans multiple skills in this plugin, requires sequencing across index → implement → ship → tune, or needs senior judgment about which skill applies. Tagline: Algolia at depth — from record shape to relevance to the rendered SERP, with discipline at every layer.

Insights events and search analytics — designing the event taxonomy (eventType, eventName, objectIDs, queryID, userToken), wiring `view`, `click`, and `conversion` events from React / Next.js, the Insights middleware in InstantSearch, attributing search-driven revenue, A/B test setup, reading Search Analytics (top searches, no-result queries, click position, CTR by query), and the patterns that make every other AI feature work. Use this skill any time events are the topic — first integration, fixing missing attribution, debugging Personalization, evaluating relevance changes, or building the analytics dashboard for the engagement.

API-key strategy for Algolia — admin vs. search vs. monitoring vs. analytics keys, scoped keys with explicit ACLs, the secured API key pattern (HMAC-derived per-request keys with embedded filters and expiry) for multi-tenant filtering, IP allowlists, rate-limit partitioning, key rotation, and the audit trail. Use this skill any time the user is touching keys — first integration, multi-tenant rollout, security audit, key rotation after a staff change, or "we got a 403, what changed." Keys are the surface where production search experiences fail; treat them with discipline.

Building autocomplete and search-suggestion experiences with the Algolia Autocomplete UI library — distinct from InstantSearch. Covers query suggestions, multi-source autocomplete (suggestions + recent searches + records + redirects + content), the plugin architecture (`@algolia/autocomplete-plugin-*`), keyboard nav, accessibility, theming on shadcn, integration into a Next.js header, and the Query Suggestions index. Use this skill when building the global header search box, a command-palette experience, or any "type ahead and pick" UI. Don't reach for InstantSearch for these — Autocomplete is a different library with a different mental model.

The Contentful ↔ Algolia integration we ship by default on Composable DXP engagements — choosing between the Marketplace app, the Ingestion API source connector, and a custom Vercel-Function indexer; mapping Topics & Assemblies to Algolia records; per-locale fan-out; preview vs. delivery indices; webhook signature verification; on-publish revalidation; backfills; the moments where the Marketplace app is enough and the moments where it's not. Use this skill any time a Composable DXP engagement needs Contentful as the source of truth for an Algolia index — first integration, new content type, locale rollout, or migration from a hand-rolled indexer to a managed connector (or vice versa).

Index and record design for Algolia — designing the JSON record shape that powers search, deciding searchable vs. faceted vs. displayed attributes, choosing per-type indices vs. one federated index, structuring distinct/grouping for variant collapse, and architecting replicas (standard vs. virtual) for sort orders. Use this skill any time the user is starting a new Algolia integration, adding a new content type to an existing index, refactoring records that have gotten bloated, deciding between one index or many, or planning sort orders. The schema decisions here propagate into every other skill — get them right and ranking, faceting, and indexing pipelines fall into place.