nw-property-based-testing

nw-property-based-testing is a skill for Claude Code, Codex from nWave-ai/nWave. It costs 26 tokens per session (1,680 once invoked), scanned A, original, MIT.

Testing guidance that checks general rules across many generated inputs instead of only a few hand-written examples. It also covers mutation testing, which changes code deliberately to see whether tests detect the change.

In plain words
What is it for?
Use it to design property-based tests, define invariants and round-trip checks, shrink failing cases, and assess whether tests can catch realistic code changes.
Why use it?
It finds edge cases that example-based tests may miss and reduces the effort of diagnosing failures by shrinking them to simpler inputs.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/nwave-ai/nwave/nw-property-based-testing
Any agent
npx skills add nWave-ai/nWave --skill nw-property-based-testing
Clone the repo
git clone --depth 1 https://github.com/nWave-ai/nWave

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nw-property-based-testing

README.md
[![agentmods](https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-property-based-testing.svg)](https://agentmods.dev/skills/nwave-ai/nwave/nw-property-based-testing)
Your own site
<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-property-based-testing"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-property-based-testing.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,680 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00026 $0.01680
Opus 5 $0.00013 $0.00840
Sonnet 5 $0.00005 $0.00336
Haiku 4.5 $0.00003 $0.00168

Measured 2d ago against content hash f83ab800c7bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

nw-property-based-testing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

nWave/skills/nw-property-based-testing/SKILL.md · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Property-Based Testing and Mutation Testing

Deferred to Phase 2.25: Mutation testing runs ONCE per feature as final quality gate at orchestrator Phase 2.25 (after all steps complete). Do NOT run mutation testing during inner TDD loop.

Property-Based Testing (PBT)

Instead of examples ("given X, expect Y"), write properties ("for all valid inputs, condition Z holds"). Framework generates hundreds/thousands of inputs checking property. Dramatically expands test coverage.

Property Patterns

  1. Invariants: "for all inputs, condition holds" (sorted list is ordered, balance >= 0)
  2. Roundtrip: "encode then decode = original" (serialize/deserialize, compress/decompress)
  3. Oracle: "compare against reference implementation" (optimized vs correct-but-slow)
  4. Metamorphic: "different operations, same result" (add(a,b)==add(b,a), filter can't increase size)

Shrinking

When property fails, framework auto-finds minimal failing input. Dramatically accelerates debugging. Algorithm: find failing input -> try simpler variants -> if still fails, use as new candidate -> repeat.

PBT Tools by Language

Language Framework
Python Hypothesis
JavaScript/TypeScript fast-check
Haskell QuickCheck
Rust quickcheck
Java jqwik
C# FsCheck

Adopted by Amazon, Volvo, Stripe, Jane Street (ICSE 2024 study).

When PBT Adds Value

HIGH value: algorithms | data structures | serialization | business rules (validation, calculations) | protocols/state machines | unbounded input domain with universal invariant. LOW value: simple CRUD | UI logic | external API integrations | closed-world finite domain (use parametrize instead — see falsifier-gate below). PBT complements example-based testing, doesn't replace it.

Falsifier-gate: closed-world finite → parametrize, NOT PBT

If the input domain is finite + enumerable (N known files, M known event types, K known skill names, fixed Python versions), PBT is the wrong tool:

Read the full file on GitHub · 161 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 161 lines · 26 tokens per session scan A f83ab800c7bf

Subscribe to this mod's changes

nw-property-based-testing is a skill published in the GitHub repository nWave-ai/nWave (605 stars, last pushed 6d ago), licensed MIT. It adds 26 tokens to every session and 1,680 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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