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-index-designgit 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-index-design)<a href="https://agentmods.dev/skills/elastic/cursor-plugins/elasticsearch-index-design"><img src="https://agentmods.dev/badge/skills/elastic/cursor-plugins/elasticsearch-index-design/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/elastic/cursor-plugins/elasticsearch-index-design"><img src="https://agentmods.dev/badge/skills/elastic/cursor-plugins/elasticsearch-index-design.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00083 | $0.02847 |
| Opus 5 | $0.00042 | $0.01424 |
| Sonnet 5 | $0.00017 | $0.00569 |
| Haiku 4.5 | $0.00008 | $0.00285 |
Grade A, and why
elasticsearch-index-design 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 6d 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-index-design — 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elasticsearch Index Design
Design explicit index mappings from access patterns, review existing mappings for type and storage mistakes, and apply corrections through a new index plus reindex when field types must change.
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.
Process
-
Gather access patterns per field. Before choosing types, list how each field is used. For every field capture:
- Search — full-text match, phrase, relevance scoring?
- Filter — exact term, terms set, prefix?
- Aggregate — terms, cardinality, histogram, stats?
- Sort — ascending/d descending in result sets?
- Retrieve only — returned in
_sourcebut never queried?
The decision: classify each field into one primary access pattern (search, exact, numeric metric, date, boolean, structured object, or retrieve-only). Missing access-pattern data is a blocker — ask the user rather than guessing. Call
GET /to confirm connectivity; when reviewing an existing index, callGET /{index}/_mappingto ground the discussion in the current mapping. -
Choose field types from access patterns. Map each field to the minimal type set that satisfies its pattern. Read Field Type Decisions and Multi-Field Patterns before proposing mappings.
What ships with it
3 files 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.
- 6d ago First seen · 223 lines · 83 tokens per session scan A 67638bfd5d2b
elasticsearch-index-design is a skill published in the GitHub repository elastic/cursor-plugins (32 stars, last pushed 7d ago), licensed Apache-2.0. It adds 83 tokens to every session and 2,847 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-index-design, differing in 0 lines, and is treated as a copy.
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