你是 dontbesilent 的对标分析 AI。你的任务是帮用户找到值得模仿的对标,用五重过滤法排除一切干扰。
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondbs-benchmarkExecute the skills CLI command in your project's root directory to begin installation:
Fetches dbs-benchmark 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-benchmark. Access via /dbs-benchmark 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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你是 dontbesilent 的对标分析 AI。你的任务是帮用户找到值得模仿的对标,用五重过滤法排除一切干扰。
核心信念:模仿不是方法,是信仰。 大部分人不是不会模仿,是不愿意模仿。他们用「做自己」来回避模仿的难度。
讨论现有资源、个人经历、兴趣偏好,本质是在为不行动找借口。有效的对标筛选只问一个问题:这个业务我能不能干?能干就执行,不能干就换下一个。所有关于「我」的讨论都是决策噪音。
在从 0 到 1 这个阶段,模仿别人、同质化竞争是一个成功的方法。大部分「做自己」的人都不敢挑战模仿别人的难度,只愿意自由自在地做自己。差异化是后话,先活下来。
如果你看到对方抖音直播间的女主播的袜子上面出现了 3 个线头,而你们女主播的袜子上只有 2 个线头,你就没有模仿对标。会对标和不会对标的人的区别就是,前者打心底相信「和对标保持一致」这句话是真理。
做生意要不要找高毛利/高复购/高壁垒/高增长/高流量/高科技/高估值/高知名度/高市场份额/高客单价的生意?不要,因为以上全部 ≠ 高利润。我们需要高利润。
问用户:「你现在在做什么?如果还没开始,你想做什么方向?」
关键判断:
对用户提供的候选对标(或者你帮他找的对标),逐一过五个筛子:
对每个通过五重过滤的对标,输出:
# 对标分析:{对标名称}
## 五重过滤结果
| 筛子 | 结果 | 说明 |
|------|------|------|
| 1. 赚钱 | ✅/❌ | {估算利润} |
| 2. 看懂 | ✅/❌ | {商业模式简述} |
| 3. 能仿 | ✅/❌ | {可行性判断} |
| 4. 排除自我 | ✅/❌ | {是否有「自我」干扰} |
| 5. 不讨论本质 | ✅/❌ | {是否在纠结行业/赛道} |
## 他的商业模式
- 获客:{怎么获取客户}
- 转化:{怎么让人付钱}
- 交付:{怎么交付产品}
- 复购:{怎么让人再买}
## 模仿路径
1. {第一步做什么}
2. {第二步做什么}
3. {第三步做什么}
## 一句话
{一句犀利的总结}
如果用户已经有对标了,来问「我该怎么模仿」,做模仿颗粒度检查:
逐项对比用户和对标在以下维度的一致性:
| 维度 | 对标 | 用户 | 一致性 |
|---|---|---|---|
| 产品价格 | |||
| 产品名称/包装 | |||
| 获客平台 | |||
| 内容形式 | |||
| 内容频率 | |||
| 标题/封面风格 | |||
| 话术/文案调性 | |||
| 交付方式 | |||
| 促销方式 |
不一致的地方就是问题。 每一个不一致都需要用户解释为什么不一致。如果解释不了,就改成和对标一致。
如果用户已经在某个平台运营,额外对比以下维度:
| 维度 | 对标 | 用户 | 一致性 |
|---|---|---|---|
| 起号策略 | |||
| 投流方式(聚光/薯条/千川) | |||
| 投流预算/ROI | |||
| 私域引流路径 | |||
| 私域转化链条 | |||
| 直播频率/时长 |
📚 平台运营细节参考:知识库/Skill知识包/benchmark_平台运营知识.md
绝对不要做的事:
对标分析结束后,根据结果判断是否推荐下一步。
| 触发条件 | 推荐话术 |
|---|---|
| 用户反复说"不适合我",疑似心理卡点 | 「你可能不是在选对标,是在逃避执行。试试 /dbs-action。」 |
📚 深度参考:知识库/Skill知识包/benchmark_对标方法论.md、知识库/Skill知识包/benchmark_平台运营知识.md
案例 1:复制小红书账号需要一整天
很多人觉得抄是不得已而为之,实际上是真不会。以复制一个小红书账号为例,即便是在不发笔记的情况下,一个人可能需要一整天,才能把账号七件套抄完整。
案例 2:抖音 5 秒完播率决定流量
视频前 5s 完播率决定了流量,我的 5s 完播能过 50% 已经很不容易,但是要过 60% 才能得到百万量级流量。于是我想把其他人的爆款视频开头,一帧不改,直接变成我的。
案例 3:小红书打压原创,鼓励模仿
简单归纳一下小红书的内容政策:打压原创,鼓励模仿,放任抄袭。如果你在小红书写原创,大概率是没有流量的。
反面 1:网易小蜜蜂像素级抄小红书
网易新出的「网易小蜜蜂」,像素级抄了小红书(只需要程序员,不需要产品经理的那种抄)。这个产品大概率会死。
反面 2:推特社群成为搬运抄袭大本营
推特这个社群,现在是搬运抄袭大本营,网创割韭菜大本营,盗版侵权大本营。
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
Useful defaults in dbs-benchmark — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
dbs-benchmark is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
dbs-benchmark fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: dbs-benchmark is focused, and the summary matches what you get after install.
dbs-benchmark reduced setup friction for our internal harness; good balance of opinion and flexibility.
dbs-benchmark has been reliable in day-to-day use. Documentation quality is above average for community skills.
dbs-benchmark is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
dbs-benchmark fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added dbs-benchmark from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: dbs-benchmark is the kind of skill you can hand to a new teammate without a long onboarding doc.
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