flaky-test-killer
Skill69 starsChanged 4 days agoNo licenceView on GitHub
Find why a test is flaky and fix the root cause, never by adding retries, sleeps or bigger timeouts. Measures the flake rate with a confidence interval, runs the test under stressors (random order, timezone, fake clock at month end or DST, CPU load, fresh temp dir, low file limits), bisects for the test that pollutes it, and proves the fix with before and after numbers. Use when the user says "flaky test", "test passes locally fails in CI", "intermittent failure", "random test failure", "works on my machine", "test fails sometimes", "only fails in the full suite", or wants to quarantine or retry a test.
In this repository23 other files it gives its agents.
- api-design-reviewSkill
- benchmark-honestlySkill
- bisect-anythingSkill
- codebase-mapSkill
- dx-auditSkill
- security-threat-modelSkill
- brand-kitSkill
- image-genSkill
- from-scratchSkill
- paper-to-runnableSkill
- system-design-from-scratchSkill
- teach-backSkill
- next-stepSkill
- skill-routerSkill
- video-scriptSkill
- clean-audioSkill
- code-loopSkill
- perspective-illusionSkill
- repo-timelapseSkill
- reverse-engineer-videoSkill
- rough-cutSkill
- scripted-screencastSkill
- vox-explainerSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.