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 walterra/eddoapp --skill elasticsearch-esqlgit clone --depth 1 https://github.com/walterra/eddoappWrote 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/walterra/eddoapp/elasticsearch-esql)<a href="https://agentmods.dev/skills/walterra/eddoapp/elasticsearch-esql"><img src="https://agentmods.dev/badge/skills/walterra/eddoapp/elasticsearch-esql/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/walterra/eddoapp/elasticsearch-esql"><img src="https://agentmods.dev/badge/skills/walterra/eddoapp/elasticsearch-esql.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00098 | $0.03747 |
| Opus 5 | $0.00049 | $0.01873 |
| Sonnet 5 | $0.00020 | $0.00749 |
| Haiku 4.5 | $0.00010 | $0.00375 |
Grade A, and why
elasticsearch-esql 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 9d 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 — 495 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elasticsearch ES|QL
Generate ES|QL queries from natural language descriptions and execute them against Elasticsearch.
For visualization tasks: Always read references/vega-lite-reference.md first. It contains the complete grammar of graphics including data types, encoding channels, mark types, multi-view composition (layer, facet, concat, repeat), and professional best practices.
For architecture diagrams: Use the
graphviz_charttool with DOT syntax. Best for flowcharts, dependency graphs, state machines, and system architecture diagrams. Always read references/graphviz-reference.md for complete syntax, node shapes, edge styles, and layout patterns.
What is ES|QL?
ES|QL (Elasticsearch Query Language) is a piped query language for Elasticsearch. It is NOT the same as:
- Elasticsearch Query DSL (JSON-based)
- SQL
- EQL (Event Query Language)
ES|QL uses pipes (|) to chain commands: FROM index | WHERE condition | STATS aggregation BY field | SORT field | LIMIT n
Version Compatibility: ES|QL was introduced in 8.11 (tech preview) and became GA in 8.14. Features like
LOOKUP JOIN,MATCH, andINLINESTATSwere added in later versions. Check references/esql-version-history.md for feature availability by version.
Container Environment
Inside Docker containers, the skill is available at:
ESQL="{baseDir}/esql.js"
Environment Configuration
Elasticsearch connection is configured via environment variables (set by the container):
# Option 1: Elastic Cloud (recommended)
export ELASTICSEARCH_CLOUD_ID="deployment-name:base64encodedcloudid"
export ELASTICSEARCH_API_KEY="base64encodedapikey"
# Option 2: Direct URL with API Key
export ELASTICSEARCH_URL="https://elasticsearch:9200"
export ELASTICSEARCH_API_KEY="base64encodedapikey"
# Option 3: Basic Auth
export ELASTICSEARCH_URL="https://elasticsearch:9200"
export ELASTICSEARCH_USERNAME="elastic"
export ELASTICSEARCH_PASSWORD="changeme"
# Optional: Skip TLS verification (development only)
export ELASTICSEARCH_INSECURE="true"
What ships with it
9 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.
- esql.js 23 KB runs code
- package.json 330 B
- references/dsl-to-esql-migration.md 15 KB
- references/esql-reference.md 18 KB
- references/esql-version-history.md 14 KB
- references/generation-tips.md 8.5 KB
- references/graphviz-reference.md 25 KB
- references/query-patterns.md 7.6 KB
- references/vega-lite-reference.md 40 KB
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.
- 9d ago First seen · 495 lines · 98 tokens per session scan A ce03fcd310e4
elasticsearch-esql is a skill published in the GitHub repository walterra/eddoapp (58 stars, last pushed 7d ago), licensed Apache-2.0. It adds 98 tokens to every session and 3,747 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 2026-08-30.
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pace-bridge
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pace-knowledge
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agent-context
Bootstrap persistent project context for AI coding agents.
agent-context-system
Persistent local-only memory for AI coding agents. AGENTS.md (committed) + .agents.local.md (gitignored) = context that persists across sessions. Read both at start, update scratchpad at end, promote stable patterns over time.