elastic/cursor-plugins is a collection of Cursor plugins that give AI assistants access to Elastic documentation and guidance for Elastic Cloud, Elasticsearch, Kibana, Observability, and Security. Developers use it when working with Elastic products and related technologies. The catalogue lists these plugins' skills and documentation MCP tools.
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.
npx skills add elastic/cursor-plugins --skill elasticsearch-query-optimizationgit clone --depth 1 https://github.com/elastic/cursor-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/elastic/cursor-plugins/elasticsearch-query-optimization)<a href="https://agentmods.dev/skills/elastic/cursor-plugins/elasticsearch-query-optimization"><img src="https://agentmods.dev/badge/skills/elastic/cursor-plugins/elasticsearch-query-optimization.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.02637 |
| Opus 5 | $0.00037 | $0.01319 |
| Sonnet 5 | $0.00015 | $0.00527 |
| Haiku 4.5 | $0.00007 | $0.00264 |
Grade A, and why
elasticsearch-query-optimization 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.
This is a copy
100% identical to elasticsearch-query-optimization — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elasticsearch Query DSL Optimization
Diagnose why a Query DSL search is slow, identify the dominant cost from the profile (not guesswork), rewrite the query to remove that cost while preserving match semantics, and re-measure with profiling enabled.
Environment Configuration
This skill executes Elasticsearch operations through the elastic CLI. If the
elastic CLI is not installed, tell the user what it is needed for. Do
not guess credentials, call the HTTP API directly, or attempt other workarounds.
This skill references operations in HTTP-shorthand form (e.g., GET /, GET /_cat/indices, GET /{index}/_mapping,
GET /{index}/_settings/index.mode, POST /_query). The Operations table at the end of this document
maps each shorthand to the equivalent elastic CLI command — always use the CLI rather than calling the HTTP API
directly.
Scope: Query DSL searches via
POST /{index}/_search. This skill does not migrate queries to ES|QL — it optimizes the existing bool/match/term/wildcard structure the user already runs.Ground rule: Never recommend "add shards" or "scale hardware" as the primary fix when the profile names a specific clause (for example
WildcardQueryat ~3.8s). Fix the query first; infrastructure changes require evidence the query is already optimal.
Process
-
Confirm connectivity and locate the target index. Call
GET /. If the call fails, stop — do not guess endpoints or credentials. When the user names an index pattern (for examplelogs-*), narrow candidates withGET /_cat/indicesand pick the index or pattern the query actually targets.Decision: proceed only when the index is known. Data needed: index name or pattern, and the slow Query DSL body (from the user or from a saved search).
-
Profile the slow query to find the dominant cost. Call
POST /{index}/_searchwith"profile": trueand the user's query unchanged. Readtook, then inspectprofile.shards[].searches[].query— sort child collectors bytime_in_nanosand identify the top contributor.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 203 lines · 75 tokens per session scan A e838f555ad06
elasticsearch-query-optimization is a skill published in the GitHub repository elastic/cursor-plugins (31 stars, last pushed 2d ago), licensed Apache-2.0. It adds 75 tokens to every session and 2,637 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to elasticsearch-query-optimization, differing in 0 lines, and is treated as a copy.
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