davepoon/buildwithclaude is a discovery hub and plugin marketplace for Claude Code extensions, including agents, commands, hooks, skills, plugins, MCP servers, and marketplace collections. Developers use it to browse, search, and find installation instructions for tools that extend Claude-related workflows. Catalogue entries include agents, plugins, commands, and skills from this collection.
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.
git clone --depth 1 https://github.com/davepoon/buildwithclaudeWrote 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.
[](https://agentmods.dev/commands/davepoon/buildwithclaude/add-property-based-testing)<a href="https://agentmods.dev/commands/davepoon/buildwithclaude/add-property-based-testing"><img src="https://agentmods.dev/badge/commands/davepoon/buildwithclaude/add-property-based-testing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/davepoon/buildwithclaude/add-property-based-testing"><img src="https://agentmods.dev/badge/commands/davepoon/buildwithclaude/add-property-based-testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00005 | $0.00716 |
| Opus 5.5 | $0.00002 | $0.00286 |
| Sonnet 5.5 | $0.00001 | $0.00143 |
| Haiku 4.5 | $0.00001 | $0.00072 |
Grade A, and why
add-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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Property-Based Testing
Implement property-based testing framework
Instructions
-
Property-Based Testing Analysis
- Analyze current codebase to identify functions suitable for property-based testing
- Identify mathematical properties, invariants, and business rules to test
- Assess existing testing infrastructure and integration requirements
- Determine scope of property-based testing implementation
- Plan integration with existing unit and integration tests
-
Framework Selection and Installation
- Choose appropriate property-based testing framework:
- JavaScript/TypeScript: fast-check, JSVerify
- Python: Hypothesis, QuickCheck
- Java: jqwik, QuickTheories
- C#: FsCheck, CsCheck
- Rust: proptest, quickcheck
- Go: gopter, quick
- Install framework and configure with existing test runner
- Set up framework integration with build system
- Choose appropriate property-based testing framework:
-
Property Definition and Implementation
- Define mathematical properties and invariants for core functions
- Implement property tests for data transformation functions
- Create property tests for API contract validation
- Set up property tests for business logic validation
- Define properties for data structure consistency
-
Test Data Generation
- Configure generators for primitive data types
- Create custom generators for domain-specific objects
- Set up composite generators for complex data structures
- Configure generator constraints and boundaries
- Implement shrinking strategies for minimal failing examples
-
Property Test Categories
- Roundtrip Properties: Serialize/deserialize, encode/decode operations
- Invariant Properties: Data structure consistency, business rule validation
- Metamorphic Properties: Equivalent operations, transformation consistency
- Model-Based Properties: State machine testing, system behavior validation
- Oracle Properties: Comparison with reference implementations
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.
- 1mo ago First seen · 85 lines · 5 tokens per session scan A 7ac91c21606c
add-property-based-testing is a command published in the GitHub repository davepoon/buildwithclaude (3,660 stars, last pushed today), licensed MIT. It adds 5 tokens to every session and 716 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-09-05.
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