Test Tier Selection
CheckedAutomatically assigns test tiers (e.g., smoke, regression, performance) based on code changes and risk assessment.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add laurigates/claude-plugins --skill test-tier-selection -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
laurigates
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned laurigates/claude-plugins at 45d1d7dcf6.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 45d1d7dcf6
- Scanned
- 1 file, 123 lines
About this skill
The test-tier-selection skill enables AI agents to dynamically choose appropriate testing strategies based on specific project requirements and risk profiles. It automates the decision-making process for selecting between unit, integration, end-to-end, or performance testing suites without manual intervention.
When to use it
- Automate test strategy selection in CI/CD pipelines to reduce configuration overhead.
- Adjust testing depth dynamically based on code changes or criticality levels.
- Ensure consistent test coverage standards across microservices or monolithic architectures.
- Optimize resource allocation by matching test complexity to available compute budgets.
Key capabilities
- Analyzes project context to recommend optimal test tiers.
- Integrates with existing testing frameworks and CI/CD workflows.
- Supports flexible configuration for diverse testing needs.
- Provides actionable insights on test strategy adjustments.
Example prompts
- "Analyze this codebase and suggest the most appropriate test tier for our new feature deployment."
- "Configure automated test selection based on our current CI/CD pipeline constraints."
- "Recommend a testing strategy that balances speed and coverage for our microservices architecture."
Tips & gotchas
Ensure your project has clear documentation defining test tier criteria to maximize accuracy. This skill works best when integrated early in the development lifecycle to establish robust testing foundations.