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 attilaszasz · Codex Skill · ★ 95
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sdd-pilot safe to install? View the security audit →
SDD Pilot Enhance your AI coding tool with a structured, spec-driven delivery workflow. What is SDD Pilot? Most AI coding tools jump straight to code. SDD Pilot adds a spec-driven development layer on top — so you specify what to build before how to build it. Phase-by-phase process — each feature moves through Specify → Plan → Tasks → Implement → QC Quality gates — you cannot skip ahead; each phase requires the previous phase's artifacts Structured artifacts — specs, plans, tasks, and QC reports live under
| Stars | 95 |
| Forks | 9 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 71.6730208590176/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-04 |
| Created | 2026-02-18 |
| Platforms | claude-code, cli, codex, gemini, node, vscode |
| Est. Tokens | ~16k |
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sdd-pilot is Replace chaotic AI code generation with a disciplined, spec-driven workflow. SDD Pilot enforces structured development phases and quality gates, leveraging AI agents to conduct online research for bes. It is categorized as a Codex Skill with 95 GitHub stars.
sdd-pilot is primarily written in JavaScript. It covers topics such as antigravity, claude-code, codex.
You can find installation instructions and usage details in the sdd-pilot GitHub repository at github.com/attilaszasz/sdd-pilot. The project has 95 stars and 9 forks, indicating an active community.
sdd-pilot is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to sdd-pilot on Agent Skills Hub include Conductor-for-all, spec-kit-zh, sub-agents-mcp. 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: