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algolia-reference-architecture

Plan or review an Algolia search system by mapping its data sources, indexing, queries, user interface, permissions, and operations. Get documented architecture decisions, failure handling, validation steps, and a phased rollout with a rollback path.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Design or review an Algolia search architecture across source data, indexing, query, UI, events, and operations. Use when establishing system boundaries or evaluating an existing integration. Trigger with "Algolia architecture", "design search platform", or "review Algolia integration".

실행 점수 미검증

설치 방법 보기

이럴 때 유용합니다

  • Planning a new Algolia search integration
  • Reviewing an existing search architecture
  • Defining tenant access and indexing boundaries
  • Preparing rollout and rollback steps

포함된 파일(2)

  • SKILL.md4.0 KB
  • references/official-docs.md1.3 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Algolia Reference Architecture

Overview

This skill produces an evidence-backed architecture tailored to the repository. It avoids presenting optional Algolia products or provider features as mandatory and makes trust, data, and failure boundaries explicit.

Prerequisites

  • A named repository, environment, and Algolia application or index in scope
  • The local lockfile and installed client types as implementation authority
  • A safe read-only query or explicitly disposable test target
  • Current first-party documentation for any provider behavior that affects the change

Tool Discipline

Use Read, Glob, and Grep to inspect local code, configuration names, tests, and dependency versions. Use WebFetch only for current official Algolia documentation. Use Write or Edit only after identifying the target files, constraints, and verification plan.

Current Contract

  • The source system remains authoritative; Algolia is a derived search projection.
  • Separate indexing, browser search, server search, events, analytics, and workforce administration trust zones.
  • Version record transforms and search configuration with the application.
  • Design task completion, reconciliation, observability, and rollback before production cutover.

Authentication

Assign distinct least-privilege credentials to each machine actor and use provider team controls for human access. Generate tenant-scoped secured keys only on trusted servers.

Instructions

  1. Map current components, data stores, producers, consumers, credentials, indices, and deployment environments.
  2. Define the record contract, stable identity, deletion semantics, settings ownership, and freshness objective.
  3. Choose query and UI boundaries, including browser versus server execution and tenant restrictions.
  4. Add event flow only where consent, user-token, query-ID, and validation requirements are owned.
  5. Model failures for source lag, partial indexing, key denial, provider degradation, and relevance regressions.
  6. Produce architecture decisions, interfaces, tests, observability, rollout, and rollback.

Approval Boundaries

Do not select paid features, centralize unrestricted credentials, or authorize a migration solely from a generic reference diagram.

Output

Return the as-is and proposed boundaries, data and trust flows, decision records, interfaces, failure modes, security controls, validation plan, and phased rollout.

Error Handling

ConditionResponse
Repository contradicts assumed topologyFollow repository evidence and revise the design.
Feature entitlement unknownMark it optional pending current account confirmation.
Trust boundary crosses browserReplace write access with a backend capability.
Rollback projection missingAdd a retained prior target or rebuild path.

Examples

Use this compact input and expected handoff to calibrate scope and evidence quality.

Input:

scope=catalog-search; source=postgres; consumers=web,mobile; tenants=120

Expected handoff:

projection=versioned; browser=secured-search; indexing=job-key; rollback=prior-index

Resources

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