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 nizos · Claude Skill · ★ 2.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is tdd-guard safe to install? View the security audit →
TDD Guard Automated Test-Driven Development enforcement for Claude Code. Overview TDD Guard ensures Claude Code follows Test-Driven Development principles. When your agent tries to skip tests or over-implement, TDD Guard blocks the action and explains what needs to happen instead. Click to watch TDD Guard in action Features Test-First Enforcement - Blocks implementation without failing tests Minimal Implementation - Prevents code beyond current test requirements Lint Integration - Enforces refactoring using your linting rules Customizable Rules - Adjust validation rules to match your TDD style Flexible Validation - Choose faster or more capable models for your needs -
| Stars | 2,341 |
| Forks | 186 |
| Language | TypeScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 67.6839033158702/100 |
| Open Issues | 20 |
| Last Updated | 2026-09-14 |
| Created | 2025-07-07 |
| Platforms | claude-code, node |
| Est. Tokens | ~14k |
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tdd-guard is Automated TDD enforcement for Claude Code. It is categorized as a Claude Skill with 2.3k GitHub stars.
tdd-guard is primarily written in TypeScript. It covers topics such as agentic-coding, automation, claude-code.
You can find installation instructions and usage details in the tdd-guard GitHub repository at github.com/nizos/tdd-guard. The project has 2.3k stars and 186 forks, indicating an active community.
tdd-guard is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to tdd-guard on Agent Skills Hub include vibe-coding-prompt-template, pilot-shell, claude-forge. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: