opensearch

A set of patterns for using OpenSearch, a search service for finding text and locations in data, from AWS Lambda functions.

In plain words
What is it for?
Use it to configure authenticated clients and indexes, load documents in batches, handle partial failures, and write full-text, exact-match, and geographic searches.
Why use it?
It helps avoid inefficient indexing and searching, excessive memory use, connection problems, and missed errors during bulk operations.

Cursor rule for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/goranerhartic/cursor-development-rules/opensearch
Clone the repo
git clone --depth 1 https://github.com/GoranErhartic/cursor-development-rules

Made for: Cursor.

Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 470 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00017 $0.00470
Opus 5 $0.00009 $0.00235
Sonnet 5 $0.00003 $0.00094
Haiku 4.5 $0.00002 $0.00047

Measured 2d ago against content hash 33d1e2637a4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

opensearch scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/languages/aws-lambda/opensearch.mdc · 45 lines

What it actually says

OpenSearch Patterns

Overview

OpenSearch provides full-text search and geo queries. Lambda integration requires memory-efficient bulk operations and connection reuse.

Client

  • Use @opensearch-project/opensearch with AwsSigv4Signer for auth; singleton client; node: process.env.OPENSEARCH_ENDPOINT; close client on cold start teardown if needed
  • Set maxRetries, requestTimeout; use aoss service for OpenSearch Serverless

Index and Mapping

  • Define mapping (keyword vs text, geo_point for location); use custom analyzers for address/text search
  • Create index with client.indices.create({ index, body: mapping }); check exists before create
  • Use environment-based index name

Bulk Indexing

  • Bulk API: Build body as array of { index: { _index, _id } } and { ...doc } pairs; chunk (e.g. 500–1000 docs) to avoid memory/timeout
  • Memory: Stream or batch from DynamoDB Streams; do not load full result set into memory
  • Handle partial failures: check response.body.items for per-item errors; retry failed items or log and continue

Search Queries

  • Full-text: match, match_phrase, multi_match; use keyword for exact filters
  • Geo: geo_distance, geo_bounding_box with location as geo_point; distance in km/mi
  • Compound: bool with must, filter, should, must_not; filter for non-scoring
  • Pagination: from/size or search_after for deep pagination

Conventions

  • Single client per Lambda; chunk bulk ops; use filters to reduce result size; avoid large size in one request
  • Include correlationId/traceId in logs for debugging

Anti-Patterns

  • Loading entire dataset into memory; unbounded bulk size; scanning without filters; ignoring bulk item errors

See also: dynamodb-streams.mdc, logging-setup.mdc

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 45 lines · 17 tokens per session scan A 33d1e2637a4a

Subscribe to this mod's changes

opensearch is a cursor rule published in the GitHub repository GoranErhartic/cursor-development-rules (19 stars, last pushed 6mo ago), licensed MIT. It adds 17 tokens to every session and 470 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.