No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by shenli · Agent Tool · ★ 227
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🔒 Is distributed-system-testing safe to install? View the security audit →
Distributed Systems Testing Skills Two skills for AI coding agents that design and run claim-driven tests for distributed and stateful systems. Together they produce a structured Markdown test plan and a findings report with 10-state verdicts and an explicit SUT / harness / checker / environment blame classification. A reviewer reads the two artifacts and decides whether to ship; nothing else has to be re-run. Works with Claude Code, Codex, Copilot CLI, Cursor, Gemini, or any agent that reads Markdown and runs shell. The skills are plain SKILL.md files. The agent executes them; the plan and findings report are the output. One skill designs the plan. The other runs it. A plan starts from the product's claims, generates hypotheses tied to those claims, and writes scenarios named after the claim each tries to falsify. For consistency-critical scenarios, each scenario also binds an abstract model () to an operation-history schema, a named checker, and a nemesis with observable landing evidence. The plan ends with a coverage adequacy argument and a conservative confidence statement.
| Stars | 227 |
| Forks | 12 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 70.3835924722572/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-21 |
| Created | 2026-05-16 |
| Est. Tokens | ~18k |
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distributed-system-testing is AI-agent skills for distributed-systems testing. It is categorized as a Agent Tool with 227 GitHub stars.
You can find installation instructions and usage details in the distributed-system-testing GitHub repository at github.com/shenli/distributed-system-testing. The project has 227 stars and 12 forks, indicating an active community.
distributed-system-testing is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to distributed-system-testing on Agent Skills Hub include claude-code-skills, agent-skills, ai-maestro. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.