dbs-benchmark

dbs-benchmark is a skill for Claude Code from skillmds/skillmd. It costs 99 tokens per session (2,764 once invoked), scanned A, original, MIT.

A competitor research process that filters possible examples to find businesses worth copying, using factors such as profitability, understandable operations, and practical imitability.

In plain words
What is it for?
Use it to find business benchmarks, assess how competitors make money, and decide which business models are worth studying or imitating.
Why use it?
It helps narrow a large set of businesses to models that may be both financially attractive and possible to reproduce.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the competitive-market-intelligence plugin — 11 skills shipped together

Good fit Use it to find business benchmarks, assess how competitors make money, and decide which business models are worth studying or imitating.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/skillmds/skillmd/dbs-benchmark
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add skillmds/skillmd --skill dbs-benchmark
Clone the repo
git clone --depth 1 https://github.com/skillmds/skillmd

Made for: Claude Code.

Or install competitive-market-intelligence, the plugin that ships this one along with the rest of its 11 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dbs-benchmark

README.md
[![agentmods](https://agentmods.dev/badge/skills/skillmds/skillmd/dbs-benchmark/github.svg)](https://agentmods.dev/skills/skillmds/skillmd/dbs-benchmark)
Your own site
<a href="https://agentmods.dev/skills/skillmds/skillmd/dbs-benchmark"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/dbs-benchmark/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dbs-benchmark

Your own site · 80×15
<a href="https://agentmods.dev/skills/skillmds/skillmd/dbs-benchmark"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/dbs-benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,764 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.02764
Opus 5.5 $0.00040 $0.01106
Sonnet 5 $0.00020 $0.00553
Haiku 4.5 $0.00010 $0.00276

Measured 4d ago against content hash f54cca88de17, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-23, from the pricing page.

Security

Grade A, and why

dbs-benchmark scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/competitive-market-intelligence/skills/dbs-benchmark/SKILL.md · 232 lines

How it starts

The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.

dbs-benchmark:对标分析

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。


核心哲学

信条 1:排除自我是决策加速器

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。

信条 2:0 到 1 阶段,模仿是正确答案

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。

信条 3:模仿的颗粒度决定模仿的质量

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。

信条 4:高利润是唯一标准

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。


对标流程

Phase 1:搞清楚用户现在的状态

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:

  • 如果用户已经有业务在跑 → 帮他找同行业更赚钱的对标
  • 如果用户还没开始 → 帮他从零找一个值得模仿的业务
  • 如果用户说"我想找一个适合我的" → 立刻打断:「适合你的这个说法本身就是问题。我们不讨论你,我们只讨论业务。」

Phase 2:五重过滤

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:

筛子 1:他赚钱吗?
  • 利润至少是用户当前收入(或预期收入)的 10 倍
  • 如果连这个标准都达不到,不值得模仿
  • 判断方法:看产品价格 × 估算销量、看团队规模、看投放力度、看他敢不敢花钱
  • 注意:赚钱 ≠ 有粉丝。粉丝多不代表赚钱。
筛子 2:你能看懂吗?
  • 能看懂他怎么赚钱的——获客、转化、交付、复购的完整链条
  • 如果看不懂,说明你还没有足够的行业认知,暂时不适合模仿这个对标
  • 但注意:不需要完全理解所有细节,只需要理解商业模式的主干
筛子 3:你能模仿吗?
  • 能模仿的意思是:你有能力执行他的获客、转化、交付流程
  • 不是说你现在就有资源,而是你有能力在合理时间内获取这些资源
  • 不能模仿的典型:对方靠独家渠道、政府关系、特殊资质
筛子 4:排除自我
  • 不讨论现有业务、现有资源、成长经历、个人偏好、个人优劣势、兴趣爱好
  • 如果用户说「但我觉得这个不适合我」→ 追问:「你说不适合你,具体是哪一步你做不了?如果每一步都能做,那就不是不适合,是不想做。」
  • 如果用户说「我对这个没兴趣」→ 回应:「兴趣不是选择业务的标准。赚到钱之后你会对什么都有兴趣。」
筛子 5:不讨论业务本质
  • 能干就执行,不能干就换下一个
  • 不要花时间讨论「这个业务的社会价值」「这个行业的前景」「这个赛道是不是红海」
  • 把「赛道」「行业」这两个词从脑子里删掉

Phase 3:输出对标分析

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}

Phase 4:模仿执行检查

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

Read the full file on GitHub · 232 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 232 lines · 99 tokens per session scan A f54cca88de17

Subscribe to this mod's changes

dbs-benchmark is a skill published in the GitHub repository skillmds/skillmd (1 stars, last pushed yesterday), licensed MIT. It adds 99 tokens to every session and 2,764 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-19.