Validate software changes on a remote CircleCI-managed chunk sidecar.
npx skills add https://github.com/CircleCI-Public/chunk-cli --skill chunk-sidecar
Please help me install this Agent Skill. Skill: chunk-sidecar Source: https://github.com/CircleCI-Public/chunk-cli/tree/main/skills/chunk-sidecar Command: npx skills add https://github.com/CircleCI-Public/chunk-cli --skill chunk-sidecar
It prevents CI churn by running your build, test, and validate steps in an isolated remote chunk sidecar before your changes reach your pipeline.
chunk validate with per-command routing so remote-only checks execute remotely..circleci/test-suites.yml suitable for CircleCI Smarter Testing, enabling shardable test execution driven by atoms and junit output.Ask your AI agent to validate on the sidecar and run the tight loop by telling it to “sync to the sidecar and validate remotely”.
High-intent search queries and answers about installing and using this skill.
Remote testing on a chunk sidecar prevents CI churn by running build, test, and validate steps in an isolated environment before your changes reach the pipeline. It mirrors your local working tree to the sidecar and executes remote-only checks remotely.
Yes, sidecar environment snapshotting captures your configured environment state after verification. You can then boot fast from the snapshot for future iterations, skipping the one-time setup and accelerating the remote testing loop.
You can scaffold a `.circleci/test-suites.yml` file suitable for CircleCI Smarter Testing. This enables shardable test execution driven by atoms and junit output, allowing your test suites to be divided and run in parallel across multiple executors.
Yes, mandatory `chunk` CLI orchestration is required for sidecar validation. It handles auth/orgID preflight, active sidecar selection or creation, sync, validate, snapshot, and looping, while forwarding `CIRCLE_TOKEN` over SSH and executing remote commands per `.chunk/config.json` routing rules.
Remote sidecar testing reduces CI rework by executing build, test, and validate steps in an isolated environment that mirrors your local working tree. This catches failures early in a remote-only execution context before changes ever reach your main pipeline.
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