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Design Elasticsearch and OpenSearch search systems with mappings, relevance, scaling, and operational safeguards.
$9.99
Search Engine Architect
Example session with this skill installed
Design search for a 2-million-product catalog with filters, typo tolerance, and frequent inventory updates. Outline index and query strategy.
- Read your context and instructions
- Compiled the search engine architect
Search Engine Architect: practical plan
Search architecture outline
Data flow
Use a durable catalog source as system of record. Publish versioned product changes to an indexing pipeline with retries, dead-letter handling and replay. Make inventory updates high priority and monitor index freshness.
Mapping
Use explicit mappings for identifiers, exact facets, analyzed text, numeric price, availability and timestamps. Avoid uncontrolled dynamic fields. Normalize brand and category values.
Query behavior
Combine text relevance with filters for availability, price and category. Apply typo tolerance selectively to user-facing text, not identifiers. Use deterministic sorting and cursor/search-after pagination for deep results.
Relevance evaluation
Build a judged query set from real, authorized searches. Measure recall, ranking quality, zero-result rate, latency and conversion. Tune synonyms carefully and review regressions.
Scale and operations
Estimate shards from data size and throughput; avoid oversharding. Test refresh intervals, bulk indexing, snapshots, replica placement and cluster recovery.
Safety
Validate query input, constrain expensive wildcard/fuzzy operations, protect admin APIs and monitor stale or missing inventory. Keep index rebuild and rollback procedures.
Measurement and review
Record the baseline, source, date range, denominator and owner. Use one primary measure plus quality guardrails; compare like-for-like cohorts and disclose missing data. Treat estimates as scenarios, not observed outcomes.
Risks and controls
Check relevance, consent, disclosure, workload and downside before scaling. Keep an evidence trail, obtain human review for material commitments, and pause if trust, quality or compliance signals deteriorate.
Next steps
- Confirm the goal, audience and available capacity.
- Gather the minimum evidence for a first test.
- Assign an owner, budget and review date.
- Run a small pilot, record outcomes and decide whether to iterate, expand or stop.
Connects securely to your tools. The creator never sees your data.
About this skill
Create a practical, evidence-led Search Engine Architect workflow. Design Elasticsearch and OpenSearch search systems with mappings, relevance, scaling, and operational safeguards. Distinguish observations from assumptions, request missing inputs, give actionable recommendations with owners and measurable outcomes, and flag uncertainty. Avoid fabricated metrics, unsupported guarantees, deceptive tactics and unnecessary personal data.
How to use
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