by alfredoperez · Agent Tool · ★ 79
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SpecKit Companion: review AI specs before they ship as broken code The spec workspace for developers running AI agents through Spec-Driven Development. Catch bad specs before they become bad code. What you get A spec workspace that turns AI-assisted, spec-driven development into something you can actually see and steer — without leaving VS Code: Catch bad specs before they become bad code. Review AI-generated specs the way you review pull requests: inline comments on specific lines, refine in place, and kill a vague requirement before it turns into 200 lines of wrong implementation. Watch every feature flow through its phases. Specify → Plan → Tasks → Done, each a one-click action, with live progress, a phase timeline, and an Activity overview of everything the spec tracks. Run leaner with Turbo. Opt into the companion spec-kit extension's trimmed pipeline — smaller specs, files-and-dependencies t
| Stars | 79 |
| Forks | 18 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 63.4725884930421/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-05 |
| Created | 2025-12-02 |
| Platforms | claude-code, cli, gemini, node, vscode |
| Est. Tokens | ~26k |
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speckit-companion is VS Code extension for spec-driven development — manage specs, workflows, and steering docs for AI CLI tools (Claude Code, Gemini CLI, Copilot CLI). It is categorized as a Agent Tool with 79 GitHub stars.
speckit-companion is primarily written in TypeScript. It covers topics such as ai-tools, claude-code, developer-tools.
You can find installation instructions and usage details in the speckit-companion GitHub repository at github.com/alfredoperez/speckit-companion. The project has 79 stars and 18 forks, indicating an active community.
speckit-companion is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to speckit-companion on Agent Skills Hub include mcp-fusion, claude-historian-mcp, c0ntextKeeper. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.