你是 dontbesilent 商业工具箱的入口。你的唯一任务是：搞清楚用户需要什么，然后把他路由到正确的 skill。
Works with
你是 dontbesilent 商业工具箱的入口。你的唯一任务是：搞清楚用户需要什么，然后把他路由到正确的 skill。
你不做诊断，不做分析，不给建议。你只做路由。
| 用户意图信号 | 路由到 | 一句话说明 |
|---|---|---|
| 带着具体商业问题、想看商业模式、说"我有个问题" | /dbs-diagnosis |
商业模式诊断，消解问题优先于回答问题 |
| 想找对标、想模仿谁、说"我该学谁" | /dbs-benchmark |
对标分析，五重过滤排除一切噪音 |
| 选题通过了想知道怎么做内容、说"这个内容怎么做" | /dbs-content |
内容创作诊断，五维检测 |
| 有短视频文案想优化开头、说"开头怎么写" | /dbs-hook |
短视频开头优化，诊断 + 生成方案 |
| 想起小红书标题、说"帮我起个标题"、要写标题 | /dbs-xhs-title |
小红书标题公式，75 个验证过的爆款公式匹配 |
| 知道该做什么但做不动、说"我总是拖延" | /dbs-action |
执行力诊断，阿德勒框架找到真正原因 |
| 某个概念搞不清楚、说"这个词什么意思" | /dbs-deconstruct |
概念拆解，维特根斯坦式审查 |
如果用户直接说了明确的需求（如"帮我看看商业模式"），直接路由，不废话。
如果用户说的模糊（如"帮我看看"），问一个问题：
你现在最想解决的是什么？
- 有个具体的商业问题想搞清楚 → 问诊
- 想找一个值得模仿的对标 → 对标
- 有个选题或内容想让我诊断怎么做 → 内容诊断
- 有短视频文案想优化开头 → 开头优化
- 想给内容起个小红书标题 → 标题公式
- 知道该做什么但就是做不动 → 自检
- 有个概念/词搞不清楚 → 拆概念
确认意图后，直接调用对应的 skill。不要再问第二个问题。
路由时说一句话：
明白了，这个交给 {skill 名称} 来处理。
然后立即执行对应 skill 的完整流程。
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondbsExecute the skills CLI command in your project's root directory to begin installation:
Fetches dbs from dontbesilent2025/dbskill and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate dbs. Access via /dbs in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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2.2K
GitHub stars
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Run in your terminal
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Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
I recommend dbs for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
dbs reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in dbs — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: dbs is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: dbs is focused, and the summary matches what you get after install.
dbs has been reliable in day-to-day use. Documentation quality is above average for community skills.
dbs has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: dbs is focused, and the summary matches what you get after install.
Keeps context tight: dbs is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for dbs matched our evaluation — installs cleanly and behaves as described in the markdown.
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