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Command

/e2e-analyze

Analyze test errors

From plugin
hypershift
5368 skills5 agents8 commands
Install
$ npx -y skills add openshift/hypershift --agent claude-code

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/e2e-analyze

Context preview

What this command does when you run it.

Analyze test errors

Command definition

e2e-analyze.md
description: "Analyze test errors"
allowed-tools: ["Read", "Bash(curl)", "Bash(gcloud)", "Bash(echo:*)", "Bash(ls:*)", "Bash(find:*)", "Bash(grep:*)", "Bash(test:*)"]
argument-hint: Pass URL of a CI run as $1, the test name as $2 and target directory for artifacts as $3

General instructions

  • Validate that "$3" is an existing directory; fail if it is not. Do NOT create the directory.
  • Extract {BUILD_NUMBER} from "$1" by matching a 10–20 digit sequence; fail if none is found.
  • Use the extracted number as {BUILD_NUMBER}.
  • Use curl to download the file build-log.txt under "$1". Only allow HTTPS URLs (reject HTTP).
  • When fetching, use: `curl -fsSL --max-time 20 --retry 3 --retry-connrefused --proto '=https' --max-filesize 100M "${1}/build-log.txt"`.
  • The build-log.txt file contains e2e failures, store the artifacts related to failure "$2" under directory specified by "$3" to determine a possible root cause for the failure.
  • Use the "gcloud storage" command to fetch given artifacts under "$3" and make sure to use {BUILD_NUMBER} in URLs.
  • Provide evidence for the failure.
  • Try to find additional evidence. For example, in logs and events.
  • Do not delete downloaded artifacts during the cleanup phase.

Output format

  • The output should be formatted as:
  Error: {Error message here}
  Summary: {Failure analysis here}
  Evidence: {Evidence here}
  Additional evidence: {Additional evidence here}
Read more
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HyperShift is a middleware for hosting OpenShift control planes at scale that solves for cost and time to provision, as well as portability cross cloud with strong separation of concerns between management and workloads.

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