Elastic Agent Skills is a library of instruction packages that teach AI coding agents how to work with Elastic products, including Elasticsearch, Kibana, Elastic Observability, and Elastic Security. Developers use the skills for tasks such as API work, Kibana content management, observability, and security workflows. The catalogue entries are skills and plugins from this library.
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/agent-skills --skill elasticsearch-index-designgit clone --depth 1 https://github.com/elastic/agent-skillsWrote 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/agent-skills/elasticsearch-index-design)<a href="https://agentmods.dev/skills/elastic/agent-skills/elasticsearch-index-design"><img src="https://agentmods.dev/badge/skills/elastic/agent-skills/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/agent-skills/elasticsearch-index-design"><img src="https://agentmods.dev/badge/skills/elastic/agent-skills/elasticsearch-index-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 24 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Prompt Injection · line 34 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- elasticsearch-index-design — 100% identical, 0 lines differ
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/agent-skills (575 stars, last pushed today), 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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