创业想法多维验证与成交优化

SKILL商业运营

原名 Cresh 转化漏斗与成交优化|简诗 AI · 标识 sales-cresh

商业运营 未标注权限 许可证不明确
安装这个技能

借助多智能体对创业或商业想法做 33 项指标、6 个维度的打分评估,帮助梳理用户需求、设计优化方案、确定优先级并验证迭代,适合在投入前判断想法是否值得推进。

一句话选型结论

按资料字段整理

创业想法多维验证与成交优化是商业运营类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类商业运营 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_fccf428b/sales-cresh
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

商业运营
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_fccf428b仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验2026-11-06上游最后核验时间 · 数据更新 2026-11-06
正文体量14.8 KBSKILL.md 原文大小,越大说明说明书写得越细

能做什么

0 项能力
上游给出的能力概览与适用场景
验证创业想法评估商业方案梳理需求优先级

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
写运营方案

按目标产出活动方案与执行清单。

分析数据与指标

从报表里找问题、给结论。

整理客户与销售材料

把客户信息与话术整理成可直接用的材料。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在商业运营场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
创业想法多维验证与成交优化当前 未标注权限 未标注 未标注 未标注 有
MX 股票筛选器 联网访问 ClawHub 市场 79.9 万 OpenClaw 有
交易 未标注权限 ClawHub 市场 58.1 万 OpenClaw 有
营销技巧 只读 ClawHub 市场 54.0 万 OpenClaw 有
百灵鸟好 联网访问 GitHub 仓库 52.6 万 Codex、Claude、Cursor 有
股票信息浏览器 接触敏感数据 ClawHub 市场 40.5 万 OpenClaw 有

SKILL.md 全文

14.8 KB
模型实际读到的说明书原文,来自技能仓库

Cresh Platform Help

Cresh (cresh.me — the live product; the backlog's cresh.ai does not resolve) is a multi-agent AI
startup/business-idea validator
. You describe an idea in a guided wizard (problem, solution,
audience, competition, business model) and it returns a structured report scoring the idea across 33
metrics
organized into 6 groups — Market & Competition, Business Model & Revenue, Customer Need &
Problem Fit, Product & Technology, Go-to-Market, and Feasibility & Risks. Each metric gets a score, a
plain-language explanation, and improvement suggestions
, and Cresh markets a per-metric web search
that pulls "real sources and real data" behind each score. A full run takes ~3–6 minutes and exports
a PDF to share with a co-founder or investor.

It's a fast, structured second opinion — not a substitute for real demand validation — the report is
an AI opinion, the "sources" are disputed (reviewers report no visible citation trail), and it has
no public API (UI tool).

Step 1 — Gather context

If references/learnings.md exists, read it first for accumulated platform knowledge.

Ask only what you can't infer:

  1. What do you want from Cresh?
    - A) Run an idea through it and interpret the report — the 33 metrics, the 6 group scores, or a section
    - B) Understand the credit-based Cresh Coins pricing and the free-tier metric limit (~5–6 of 33)
    - C) Judge whether its cited "real sources" can be trusted, or export/share the PDF
    - D) Automate or export programmatically (API reality)
  2. What's the real question — "is this idea worth building?" or "how do I use this tool?" If it's
    the go/no-go decision, that's /sales-idea-validation (a score is not demand) — route in Step 2.
  3. Are you the target user? Cresh's self-serve tier is for solo founders / indie hackers; its
    separate enterprise "decision intelligence" tier (InnoScore, €500–€10k/mo) is for innovation
    teams
    — don't send a solo founder to the enterprise offer.

Skip-ahead: if the user wants the validate-before-building method or to compare validators across the
market, route to /sales-idea-validation immediately.

Step 2 — Route or answer directly

If the user's question is about… Route to
The validate-before-building method, or the go/no-go decision itself /sales-idea-validation {question}
Comparing Cresh against other validators (Preuve, DimeADozen, IdeaScore, Validator AI…) /sales-idea-validation {question}
Building the smoke-test / fake-door landing page to test real demand /sales-funnel {question}
Growing a pre-launch waitlist / capturing real demand /sales-audience-growth {question}
Turning the report's market/audience sections into a real content program /sales-content {question}

When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"

Otherwise, answer Cresh-specific questions using Step 3.

Step 3 — Cresh platform reference

Read references/platform-guide.md for the full reference — the wizard input, the 6 metric groups
and 33 metrics
(with the labels marketing uses), the per-metric explanation/improvement structure, the
"deep search per metric" claim and why its source transparency is disputed, the 6-metric free
snapshot vs the full 33-metric paid report + PDF
, the credit-based Cresh Coins model and the
best-effort price points, the enterprise "decision intelligence" tier (and why it's off-target for a
solo founder), and the no-public-API automation reality.

Answer using only the relevant section — don't dump the full reference.

Step 4 — Actionable guidance

  • Treat the 33-metric score as a directional gut check, not demand. The whole report is an LLM
    opinion
    generated from a short idea description — the group scores, the market sizing, and the
    competitor set are AI estimates, not measured demand. Tell the user to keep the structured
    outputs
    (the flagged weak metrics, competitor read, risks, improvement tips) to sharpen the pitch,
    and take the go/no-go from real behavior — a smoke test or pre-sale — not from a high Cresh score.
    Route the real test to /sales-idea-validation.
  • Don't over-trust the "real sources / real data" claim — verify the citations yourself. Cresh's
    differentiator is a per-metric web search that supposedly cites real sources, but reviewers report no
    visible citation trail
    and market/retention numbers you can't trace. Before quoting any figure or
    "sourced" claim, open the underlying source (if one is shown) and sanity-check it against a primary
    reference — treat unsourced numbers as AI estimates. This is the report-auditing discipline in
    /sales-idea-validation, applied to Cresh.
  • Do the credit math on Cresh Coins, and flag the pricing as unsettled. Cresh runs on credit-based
    "Cresh Coins"
    : a free tier shows only ~5–6 of 33 metrics (a snapshot), and the full 33-metric
    report + PDF
    costs coins. Best-effort at research (sources conflict): ~$3 per analysis in some
    reviews, or roughly $9 / $19 / $29 monthly for 1 / 3 / 5 analyses in others. Always tell the user
    to confirm current pricing on cresh.me
    and to finalize the idea framing before spending a coin —
    garbage-in, garbage-out, and each pivot re-run costs again.
  • Match the tier to the user — don't send a solo founder to the enterprise offer. The self-serve
    product is for indie founders; the enterprise "decision intelligence" / InnoScore tier (€500/mo
    pilot → €2k–€10k/mo + a large implementation fee, for 200–5,000-employee innovation teams) is a
    different product. A solopreneur validating one idea wants the self-serve tier.
  • There's no public API — don't plan an integration around it. If asked to automate, batch, or pipe
    reports elsewhere, say plainly there's no documented public API, no webhooks, no Zapier/Make, no
    MCP
    . The only way to get a report out is the PDF export (or copy/screenshot from the browser) —
    there is no supported programmatic or batch path. The thing worth automating is the real signal
    (landing-page conversions), not the generated score — route that to /sales-idea-validation and
    /sales-funnel.

If you discover a gotcha or tip not in references/learnings.md, append it there with today's date.

Gotchas

Best-effort from research (2026-07) — Cresh's pricing, credit terms, metric groups, and source claims move; verify at cresh.me.

  • Right domain: cresh.me. The live validator is at cresh.me; the backlog's cresh.ai does not
    resolve
    — don't route users there.
  • The 33-metric score is an AI opinion, not demand. A high aggregate score generated from a short
    description validates nothing on its own — follow it with a real-behavior test (smoke test / pre-sale).
  • "Real sources" is disputed. Cresh markets per-metric web search with real data, but reviewers
    report no visible citation trail
    ; verify any sourced figure against a primary reference before quoting it.
  • Garbage-in, garbage-out. Output quality tracks input specificity — a vague idea yields a generic
    report, and each pivoted re-run spends another credit. Sharpen the customer + problem + differentiation first.
  • It can overlook adjacent segments. Reviewers note Cresh anchors on the segment you describe and can
    miss adjacent buyers — don't treat its market read as exhaustive.
  • Pricing is credit-based and unsettled. Cresh Coins fund each run; the free tier shows only ~5–6 of
    33 metrics, and quoted prices (per-analysis vs monthly) conflict across sources — confirm on cresh.me.
  • Enterprise tier is a different product. The €500–€10k/mo "decision intelligence" / InnoScore tier
    targets corporate innovation teams, not solo founders — don't conflate it with the self-serve validator.
  • No public API, no webhooks, no Zapier/Make/MCP. It's a UI tool; the report leaves only as a PDF —
    there's no supported way to script, batch, or export programmatically.

Related skills

  • /sales-idea-validation — The tool-agnostic validate-before-building method + the full validator landscape (use this to actually decide build-or-not; a score is not demand)
  • /sales-preuve — Preuve AI platform help (the source-linked validator that cites every claim across 50+ live sources — the credible counterpart to Cresh's disputed "real sources" claim)
  • /sales-ideascore — IdeaScore platform help (a lean, letter-graded triage validator; contrast its terse "decision-ready" output against Cresh's fuller 33-metric report)
  • /sales-dimeadozen — DimeADozen platform help (a one-time 200+ page report validator; contrast its depth + disputed citations against Cresh's 33-metric report)
  • /sales-funnel — Build the smoke-test / fake-door landing page the real demand test runs on
  • /sales-audience-growth — Grow a pre-launch waitlist and capture real demand
  • /sales-do — Not sure which skill to use? The router matches any sales objective to the right skill. Install: npx skills add sales-skills/sales --skill sales-do -a claude-code

Examples

Example 1: "Cresh scored my idea high across the 33 metrics — should I build it?"

User says: "Cresh gave my SaaS idea strong scores across most of its 33 metrics and a good overall read. Is that validated — should I start building?"
Skill does: Explains the 33-metric report is an LLM opinion generated from a short description — the
scores, market sizing, and competitor set are AI estimates, not demand. Tells the user to keep the
structured parts (weak-metric flags, competitor read, risks, improvement tips) to sharpen the pitch, then
route the real go/no-go to /sales-idea-validation — a smoke test or pre-sale where a stranger takes an
action — rather than trusting the score.
Result: The founder earns a real demand signal before building, using Cresh's structure, not its score.

Example 2: How Cresh Coins pricing and the free tier work

User says: "How much does Cresh cost? The free run only showed me a handful of metrics — how do I get the full 33 and the PDF, and is it a subscription?"
Skill does: Explains Cresh is credit-based Cresh Coins — the free tier shows only ~5–6 of 33
metrics
(a snapshot), and the full 33-metric report + PDF costs coins. Gives the best-effort price
points (~$3/analysis in some reviews vs ~$9/$19/$29 monthly for 1/3/5 in others), flags them as
conflicting/unsettled to confirm on cresh.me
, and advises finalizing the idea framing before spending a
coin since each pivot re-run costs again.
Result: The user understands the metric gate and credit model and confirms live prices before paying.

Example 3: Can I export or automate Cresh reports via API? (developer/automation)

User says: "I want to run ideas through Cresh automatically and pull the reports into my own dashboard via an API or Zapier. How do I set that up?"
Skill does: States plainly there's no documented public API, no webhooks, no Zapier/Make, no MCP —
it's a UI tool whose only data-out is the PDF export (or copy/screenshot), so there's no supported way
to batch or export programmatically. Suggests a tool built for programmatic validation if a pipeline is
required, and notes the thing worth automating is a real demand signal (landing-page conversions), not a
generated score — pointing to /sales-idea-validation and /sales-funnel.
Result: The user avoids building on a non-existent API and picks a workable path.

Troubleshooting

The scores feel generous / it never really tells me to stop

Symptom: The 33-metric report reads encouraging even for a weak idea.
Cause: The report is a short-prompt LLM output — it pattern-matches to plausible-sounding encouragement
and can invent supporting "facts" (market size, demand, sources).
Solution: Stop treating the score as the decision. Keep the structured outputs (weak-metric flags,
competitor read, risks, improvement tips) and run a real demand test — smoke test or pre-sale — via
/sales-idea-validation. Treat a low group score as a cheap early filter, not the go/no-go.

I can't find the "real sources" behind the metrics

Symptom: Cresh markets per-metric web search with real data, but you can't see or open the citations.
Cause: Reviewers report no visible citation trail — the "sources" claim isn't consistently backed
by traceable references in the report.
Solution: Treat any figure as an AI estimate until you verify it. Where a source is shown, open it and
check it against a primary reference; if you need genuinely cited validation, use a source-linked validator
(/sales-preuve cites every claim). Never quote a Cresh number you can't trace.

I want an API or a way to export/automate

Symptom: Want to script Cresh or pull reports into another system.
Cause: Cresh has no documented public API, webhooks, or iPaaS connectors; it's a web tool whose only
data-out is the PDF.
Solution: There's no supported programmatic path — export the PDF (or copy from the browser) and
parse it if you must. Use a tool intended for programmatic use if you need a pipeline, and automate a real
demand signal (landing-page analytics) instead. See /sales-idea-validation and /sales-funnel.

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常见问题

5 问
答案由本站依据条目字段整理
创业想法多维验证与成交优化怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_fccf428b/sales-cresh。安装方式为未标注。装完刷新技能列表或重开客户端。

创业想法多维验证与成交优化支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

创业想法多维验证与成交优化权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

创业想法多维验证与成交优化收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

创业想法多维验证与成交优化用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 2026-11-06。