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 agentmods add skills/cookiemonsterdev/agents-skills/elasticsearch-docsnpx skills add cookieMonsterDev/agents-skills --skill elasticsearch-docsgit clone --depth 1 https://github.com/cookieMonsterDev/agents-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/cookiemonsterdev/agents-skills/elasticsearch-docs)<a href="https://agentmods.dev/skills/cookiemonsterdev/agents-skills/elasticsearch-docs"><img src="https://agentmods.dev/badge/skills/cookiemonsterdev/agents-skills/elasticsearch-docs.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 | $0.00099 | $0.01333 |
| Opus 5 | $0.00049 | $0.00666 |
| Sonnet 5 | $0.00020 | $0.00267 |
| Haiku 4.5 | $0.00010 | $0.00133 |
Grade A, and why
elasticsearch-docs 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.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elasticsearch questions are easy to answer from stale memory, OpenSearch assumptions, or pre–data-stream patterns. Use this skill to ground answers in the official Elastic documentation and return the closest authoritative page instead of generic search-engine advice.
When to Use
Use this skill when the request is about:
- Elasticsearch concepts, indices, documents, mappings, and data streams
- Getting started with Elastic Cloud, self-managed, or serverless deployments
- Indexing, updating, searching, aggregating, and deleting data
- Query DSL, ES|QL, EQL, SQL, and search application patterns
- Mappings, analyzers, templates, aliases, and text analysis
- Ingest pipelines, connectors, Fleet, Elastic Agent, Beats, and Logstash
- Vector search, semantic search, RAG, and Elastic Inference
- Machine learning, anomaly detection, and alerting
- Kibana: Discover, Lens, Dashboards, reporting, and workflows
- Cluster deployment, scaling, autoscaling, backup, and snapshot/restore
- Security: users, roles, API keys, encryption, and Elastic Security
- Elastic Observability: logs, metrics, traces, APM, and Synthetics
- Cross-cluster search, remote clusters, and data lifecycle management
- Troubleshooting cluster health, shard allocation, and query performance
Do not use this skill for:
- OpenSearch-specific plugins, APIs, or Dashboards behavior. Use
opensearch-docsinstead. - Raw AWS OpenSearch Service console operations when the question is provider-specific rather than Elasticsearch behavior.
- Solr, Meilisearch, or other search engines unless the question maps to documented Elasticsearch API behavior.
- Grafana or OpenTelemetry unless the question is specifically about Elastic Observability integration documented by Elastic.
Workflow
1. Classify the request
Decide which bucket the question belongs to before searching:
- Getting started and deployment choice
- Data store: indices, mappings, templates, and data streams
- Ingestion, pipelines, and connectors
- Search, query languages, and aggregations
- Vector search, AI features, and machine learning
- Kibana exploration, visualization, and alerting
- Deploy, scale, backup, and production guidance
- Security, users, roles, and API keys
- Elastic Observability or Elastic Security solutions
- Reference APIs, clients, and scripting
- Troubleshooting and release notes
What ships with it
2 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 · 115 lines · 99 tokens per session scan A 726df1d53601
elasticsearch-docs is a skill published in the GitHub repository cookieMonsterDev/agents-skills (4 stars, last pushed 16d ago), licensed MIT. It adds 99 tokens to every session and 1,333 once invoked, about $0.0005 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 2026-08-31.
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