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.
npx skills add Data-Wise/craft --skill test-generatorgit clone --depth 1 https://github.com/Data-Wise/craftWrote 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/skills/data-wise/craft/test-generator)<a href="https://agentmods.dev/skills/data-wise/craft/test-generator"><img src="https://agentmods.dev/badge/skills/data-wise/craft/test-generator/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/skills/data-wise/craft/test-generator"><img src="https://agentmods.dev/badge/skills/data-wise/craft/test-generator.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 | $0.00063 | $0.00977 |
| Opus 5 | $0.00032 | $0.00489 |
| Sonnet 5 | $0.00013 | $0.00195 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
test-generator 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 7d 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Generator Skill
Generates dogfooding test suites (automated + interactive) for any project type.
When to Use
Use this skill when:
- Setting up CLI tests for a new project
- Creating plugin validation tests
- Generating interactive QA test suites
- Need both automated and manual test coverage
- Want consistent test patterns across projects
Capabilities
Project Type Detection
Automatically detects project type and generates appropriate tests:
| Project Type | Detection | Test Focus |
|---|---|---|
| CLI Tool | pyproject.toml + CLI entry |
Commands, subcommands, exit codes, help |
| Claude Plugin | .claude-plugin/plugin.json |
Structure, commands, skills, agents |
| Python Library | pyproject.toml (no CLI) |
Module imports, API surface |
| Node Package | package.json + bin |
CLI commands, npm scripts |
| R Package | DESCRIPTION |
Package structure, exports |
| Shell Scripts | *.sh files |
Script execution, options |
Test Suite Generation
Generates two complementary test suites:
1. Automated Tests (automated-tests.sh)
- Non-interactive, CI-ready
- Exit code validation
- Output pattern matching
- Structure validation
- Runs in < 60 seconds
2. Interactive Tests (interactive-tests.sh)
- Human-guided QA
- Expected vs actual comparison
- Single-key responses (y/n/q)
- Logging to
tests/cli/logs/ - Visual output validation
Test Categories by Project Type
CLI Tools:
- Smoke tests (version, help, aliases)
- Core commands (each subcommand)
- Error handling (invalid commands)
- Exit codes (success/failure)
- Help accessibility
Claude Plugins:
- Plugin structure (plugin.json)
- Directory structure (commands/, skills/, agents/)
- File counts and validity
- Markdown syntax validation
- Cross-reference checks
Libraries:
- Import validation
- API surface coverage
- Module structure
- Documentation presence
Usage
Basic Generation
Generate CLI tests for this project
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.
- 7d ago First seen · 181 lines · 63 tokens per session scan A ebcf695323ee
test-generator is a skill published in the GitHub repository Data-Wise/craft (4 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 977 once invoked, about $0.0003 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.
Other skills, from other repositories
azure-microsoft-playwright-testing-ts
Run Playwright tests at scale using Azure Playwright Workspaces (formerly Microsoft Playwright Testing). Use when scaling browser tests across cloud-hosted browsers, integrating with CI/CD pipelines, or publishing test results to the Azure portal.
playwright-ci
Production-ready CI/CD configurations for Playwright — GitHub Actions, GitLab CI, CircleCI, Azure DevOps, Jenkins, Docker, parallel sharding, reporting, code coverage, and global setup/teardown.
playwright-testing
E2E testing with Playwright - Page Objects, cross-browser, CI/CD.
azure-microsoft-playwright-testing-ts
Run Playwright tests at scale using Azure Playwright Workspaces (formerly Microsoft Playwright Testing). Use when scaling browser tests across cloud-hosted browsers, integrating with CI/CD pipeline...
testing-e2e
End-to-end testing patterns with Playwright — page objects, AI agent testing, visual regression, accessibility testing with axe-core, and CI integration. Use when writing E2E tests, setting up Playwright, implementing visual regression, or testing accessibility.
design-ship
One-shot pipeline turning a claude.ai/design link into a pull request: scaffold via /ork:design-import, stories and specs via /ork:cover, browser verification via /ork:expect, then open the PR. Use when a design link should come back as a PR with no intermediate steps; if all you need is the components written to…