jepsen-testing

Jepsen-style correctness testing for distributed systems under faults (partitions, crashes, clock skew) using concurrent operation histories and formal checkers (linearizability/serializability and Elle-style anomalies). Use when designing, implementing, or running Jepsen tests, or interpreting histories/violations.

16 stars

Best use case

jepsen-testing is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Jepsen-style correctness testing for distributed systems under faults (partitions, crashes, clock skew) using concurrent operation histories and formal checkers (linearizability/serializability and Elle-style anomalies). Use when designing, implementing, or running Jepsen tests, or interpreting histories/violations.

Teams using jepsen-testing should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/jepsen-testing/SKILL.md --create-dirs "https://raw.githubusercontent.com/plurigrid/asi/main/.claude/skills/jepsen-testing/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/jepsen-testing/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How jepsen-testing Compares

Feature / Agentjepsen-testingStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Jepsen-style correctness testing for distributed systems under faults (partitions, crashes, clock skew) using concurrent operation histories and formal checkers (linearizability/serializability and Elle-style anomalies). Use when designing, implementing, or running Jepsen tests, or interpreting histories/violations.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Jepsen Testing

## Intake

- Identify the system under test and the exact client surface (Redis, S3, Kafka, HTTP, gRPC).
- Define what "acknowledged" means for each operation (what does the client treat as committed).
- Write the claimed consistency guarantees as a checkable property (linearizable register, RYW, monotonic reads, serializable txns).
- Specify the failure model to test (crash-stop, partitions, clock skew, disk stalls, restarts).
- Decide whether the test must be multi-surface (write via Redis, read via S3) to validate cross-frontend coherence.

## Workload Design

- Prefer the smallest workload that can falsify the claim.
- Use a mix of reads and writes that creates ambiguous interleavings.
- Add a "witness" invariant that is easy to explain:
- Lost acknowledged write.
- Read sees a value that cannot be explained by any sequential execution respecting real-time order.
- List-append: element lost/duplicated or observed order implies a cycle.

## Checker Selection

- Register or map semantics: use a linearizability checker.
- Transactional / multi-object semantics: use Elle-style anomaly detection (write cycles, dirty reads, lost updates).
- If linearizability is too strong for the product, explicitly select a weaker model and encode it (do not silently downgrade).

## Fault (Nemesis) Selection

- Partitions: majority/minority splits, bridge partitions, flapping partitions.
- Process faults: kill and restart, node reboot, rolling restarts.
- Time faults: clock offsets and jumps if the system relies on time.
- Storage faults: fsync latency, I/O stalls, disk-full behavior (only if safe and reversible).

## Run and Minimize

- Start with a short, low-concurrency run until the harness is stable.
- When a failure appears, minimize by reducing:
- Keys, operation count, and concurrency.
- Fault intensity and schedule complexity.
- Preserve determinism (fixed seeds, fixed partition schedule) so a failing history can be reproduced.

## Reporting

- State the exact claim under test and the precise pass/fail property.
- Include the workload, nemesis schedule, and a minimal failing history excerpt.
- Distinguish availability failures (timeouts) from safety failures (incorrect ok results).

Related Skills

We are still matching the closest adjacent skills for this page. In the meantime, continue through the full directory.