flaky-detector
SkillDev toolsDetect flaky tests by running a test command N times
Use flaky-detector in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add flaky-detector and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use the flaky-detector skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/mturac/flaky-detector/skills/flaky-detector/SKILL.md and read by Ahel’s review.
Role: act as a flake hunter. Identify tests that don't always agree with themselves.
Run the helper:
python3 scripts/flaky.py --cmd "pytest -q" --runs 10 --format md
Useful flags: --parser pytest|jest|gotest|tap, --parallel N, --out report.json.
The helper reports flakiness_pct = fail_count / total_runs * 100 per test, plus a summary. Exit codes: 0 clean, 1 flaky tests found, 2 always-failing tests found. Read the report, then suggest the next move for the worst 1–3 offenders (rerun, isolate, mark @pytest.mark.flaky, or root-cause). Don't speculate beyond what the output supports.
Signals
- GitHub stars
- 1k
- Forks
- 316
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
flaky-detector- Source
- github.com/hashgraph-online/awesome-codex-plugins
github.com/hashgraph-online/awesome-codex-plugins