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Byted Escloud

  • 2 installs
  • 408 repo stars
  • Updated August 3, 2026
  • volcengine/agentkit-samples

Manages Volcengine ESCloud and CloudSearch clusters for lifecycle operations plus Elasticsearch/OpenSearch indexing, querying, and aggregation.

About

Manages Volcengine ESCloud and CloudSearch clusters, covering control-plane lifecycle actions and Elasticsearch/OpenSearch data-plane workflows. A developer uses it to create, scale, and inspect clusters and to index, query, and aggregate data with guardrails on destructive operations.

  • Splits control-plane lifecycle and data-plane indexing/query workflows via bundled CLIs
  • Requires explicit confirmation before deletes, reindex, or bulk mutations

Byted Escloud by the numbers

  • 2 all-time installs (skills.sh)
  • Ranked #916 of 1,039 Cloud & Infrastructure skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/volcengine/agentkit-samples --skill byted-escloud

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Listed on Skillselion
Installs2
repo stars408
Last updatedAugust 3, 2026
Repositoryvolcengine/agentkit-samples

What it does

Manages Volcengine ESCloud and CloudSearch clusters for lifecycle operations plus Elasticsearch/OpenSearch indexing, querying, and aggregation.

Files

SKILL.mdMarkdownGitHub ↗

Volcano Engine ESCloud

Use when

  • The user needs to manage ESCloud or CloudSearch on Volcano Engine / Volcengine.
  • The task is a control-plane lifecycle action such as create, inspect, scale, expose, restart, or delete.
  • The task is an Elasticsearch/OpenSearch data-plane workflow such as cluster validation, inspection, indexing, querying, aggregation, or bulk guidance.

Route

  • Control-plane lifecycle workflows -> scripts/control.py and CONTROL_PLANE.md
  • Control-plane fallback tools -> scripts/control_tools.py and CONTROL_TOOLS.md
  • Data-plane workflows -> DATA_PLANE.md

Guardrails

  • Always run the bundled CLIs with {baseDir}/venv/bin/python.
  • Before any data-plane read or write, run data.py --endpoint <endpoint> info; if it fails, stop and fix endpoint exposure, allowlist, credentials, or TLS first.
  • Use data.py smoke_test for new-cluster validation; if the test index already exists, pass --reuse-existing or choose a different --index; delete its test index only with --cleanup --confirm.
  • For non-routine data-plane work, prefer ad-hoc curl or small Python snippets grounded in the data-plane references instead of expanding data.py.
  • Require explicit confirmation before destructive or high-impact operations such as deletes, alias cutovers, bulk mutations, _delete_by_query, _update_by_query, or _reindex.

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