转化漏斗与成交优化执行

SKILL商业运营

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

商业运营 未标注权限 许可证不明确
安装这个技能

围绕用户需求、方案设计、优先级和验证迭代给出具体执行方法,帮助梳理转化漏斗各环节并推进成交优化落地。

一句话选型结论

按资料字段整理

转化漏斗与成交优化执行是商业运营类的 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-inodash
  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15.3 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
梳理转化漏斗环节设计成交优化方案验证迭代优化效果

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
转化漏斗与成交优化执行当前 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

15.3 KB
模型实际读到的说明书原文,来自技能仓库

Inodash Platform Help

Inodash (inodash.com) is an AI product-validation and innovation platform built to help teams
reach product-market fit faster. Its free Startup Idea Validator — describe an idea → an instant
market/audience/competitor read plus a saved report (Target Audience, Market Analysis, Competitors,
Revenue Models, Validation Methods, GTM, and "Critical Investor Questions") — is the front door to a
broader workspace
: Smart Boards (AI-generated business canvases), a Persona Maker, an Idea
Generator
, a Competitor Analyzer, a Financial Forecast Builder, Deck Evaluators (founder
and investor views), a team progress dashboard, and — on paid tiers — custom RAG model training
on your own data. Work is metered by AI tokens per project, and the whole thing is team-first
(workspaces, roles, collaboration). It's a fast structured second opinion and a place to organize
early-stage work — not a substitute for real demand validation — 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 Inodash?
    - A) Run an idea through the validator and interpret the report (market, audience, competitors, "Critical Investor Questions")
    - B) Use one of the other tools — Persona Maker, Idea Generator, Competitor Analyzer, Financial Forecast Builder, Deck Evaluator, Smart Boards
    - C) Understand the pricing (AI tokens per project, workspace/project limits, what's plan-gated — dashboard, data export, RAG training)
    - D) Collaborate with a team, or export/automate 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. Solo or team? Inodash is workspace/collaboration-first; if they're a solo founder wanting a
    one-shot report, note the free tier is very thin (see Step 4) and cover cheaper single-shot peers.

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 Inodash against other validators (Validator AI, IdeaCheck, WorthBuild, VenturusAI…) /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 Inodash-specific questions using Step 3.

Step 3 — Inodash platform reference

Read references/platform-guide.md for the full reference — the module inventory (validator report
anatomy, Persona Maker, Idea Generator, Competitor Analyzer, Financial Forecast Builder, Deck Evaluators,
Smart Boards, RAG training), the AI-token-per-project metering and the four tiers (Free/Starter/
Business/Enterprise) with their workspace/project/token limits and plan gates (dashboard, data export,
RAG), why the free tier is effectively a demo, why an AI score reads directional, and the no-public-API
automation reality.

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

Step 4 — Actionable guidance

  • Treat every score and number as a directional gut check, not demand. The validator report — the
    market analysis, revenue models, competitor set, and any score — is an LLM opinion generated from a
    short description; the market-size and financial-forecast figures are AI estimates, not measured
    demand. Tell the user to keep the structured outputs (competitor map, target audience, revenue
    models, the "Critical Investor Questions") to sharpen the pitch, and take the go/no-go from real
    behavior
    — a smoke test or pre-sale — via /sales-idea-validation, not from the report.
  • Frame it as a team workspace + tool suite, not a one-shot report — and flag the stingy free tier.
    Inodash's edge over solo one-shot validators is team collaboration, multiple bundled tools (personas,
    competitor analysis, financial forecasts, deck evaluation), Smart Boards, and reusable RAG context
    on
    paid tiers. Its trade-off: the free tier is effectively a demo (best-effort at research: 1 workspace,
    1 project, ~3 AI tokens total) — say so plainly. If the user is a solo founder who just wants one cheap
    report, point them (via /sales-idea-validation) to cheaper single-shot peers; if they're a team
    organizing validation across projects, Inodash fits.
  • Explain the AI-token-per-project metering and what's plan-gated. Work is metered by AI tokens per
    project
    , and tokens reset/scale per project, not per account (best-effort: Free ~3 total, Starter
    ~50/project, Business ~100/project, Enterprise ~500/project). The insights dashboard, data export, and
    advanced data masking are Business+
    , and custom RAG model training is Enterprise-gated. Always
    flag pricing/token numbers as best-effort and tell the user to confirm current tiers on inodash.com
    —
    they move — and note yearly billing is marketed at ~50% off.
  • A "bundled suite" is broad, not deep — judge each tool on its own. One platform doing six jobs
    (validate + personas + competitors + financials + decks + boards) rarely goes as deep as a specialist on
    any one. Treat the persona, competitor, and financial-forecast outputs as editable first drafts to
    verify
    , not finished analysis — especially the financial forecast (invented assumptions for an
    untested idea). Use the good-enough pieces to move fast; redo anything you'd stake a decision on.
  • 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, and no Zapier/Make/MCP.
    Data export exists only as a Business+ UI feature (in-app export), not a programmatic endpoint — the
    only way to get data out is from the browser. The thing worth automating is the real signal
    (landing-page conversions), not the generated report — 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) — Inodash's pricing, AI-token limits, plan gates, and module set move; verify at inodash.com.

  • The validator report is an AI opinion, not demand. A market analysis, revenue models, and any score
    generated from a short description validate nothing on their own — follow with a real-behavior test
    (smoke test / pre-sale).
  • Free tier is effectively a demo. Best-effort: 1 workspace, 1 project, ~3 AI tokens total — enough to
    try one idea, not to run real work. Real use needs a paid tier; don't assume "free plan, full access."
  • Metered by AI tokens per project. Tokens scale by tier per project (Free ~3 total → Enterprise
    ~500/project) — running the validator, personas, forecasts, etc. all spend tokens; budget accordingly.
  • Dashboard, data export, and RAG are plan-gated. The insights dashboard + data export are Business+;
    custom RAG model training is Enterprise. The free/Starter tiers can't export or train on your data.
  • Financial forecasts and market sizes are AI estimates. The Financial Forecast Builder invents
    assumptions for an untested idea — verify every figure against primary sources before quoting it.
  • Bundled breadth ≠ depth. Six tools in one workspace is convenient, but each is a broad first draft;
    a specialist tool will go deeper on personas, competitor analysis, or financials.
  • No public API, no webhooks, no Zapier/Make/MCP. It's a UI tool; export is a Business+ in-app feature,
    not a programmatic path — there's no supported way to script or batch.
  • Enterprise-clientele framing, but genuinely self-serve at the bottom. Marketing highlights large
    innovation-team clients; the free/Starter tiers are still self-serve for solo founders — weigh the
    enterprise positioning against your actual use.

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-venturusai — VenturusAI platform help (a comparable framework-driven validator + business-plan/persona/forecast bundle; contrast its SWOT/PESTEL framing against Inodash's team-workspace + Smart Boards approach)
  • /sales-founderpal — FounderPal platform help (a solopreneur marketing suite with a free idea validator; the solo-tool counterpart to Inodash's team workspace)
  • /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-content — Turn the report's market/audience sections into a real content/ad program
  • /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: "Inodash validated my idea and gave a big market size — should I build?"

User says: "I ran my idea through Inodash's free validator, it looks positive and shows a large market. Good to go?"
Skill does: Reframes the report — market analysis, revenue models, competitor set, any score — as an
LLM opinion generated from a short description; the market size and any financial numbers are AI
estimates
, not demand. Tells the user to keep the structured parts ("Critical Investor Questions",
competitor map, target audience) 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 report.
Result: The founder earns a real demand signal before building, using Inodash's structure, not its verdict.

Example 2: How does the free tier / token pricing actually work?

User says: "Inodash says it's free — how much can I actually do, and what do the paid plans add?"
Skill does: Explains work is metered by AI tokens per project and that the free tier is
effectively a demo
(best-effort ~1 workspace / 1 project / ~3 tokens). Paid tiers scale tokens per
project (Starter ~50, Business ~100, Enterprise ~500) and gate features: dashboard + data export are
Business+
, custom RAG training is Enterprise. Flags all numbers as best-effort to confirm on
inodash.com and notes yearly billing is ~50% off. Adds that a solo founder wanting one cheap report may
prefer a single-shot peer — pointing to /sales-idea-validation.
Result: The user sizes the right tier and knows what "free" really covers.

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

User says: "I want to run ideas through Inodash and pull the reports into my own dashboard via API or Zapier."
Skill does: States plainly there's no documented public API, no webhooks, and no Zapier/Make/MCP —
data export exists only as a Business+ in-app UI feature, not a programmatic endpoint, so the only way
to get data out is from the browser. 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 report — 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 report looks positive but I'm not sure it means anything

Symptom: A glowing validator report (big market, encouraging revenue models) the founder senses is too easy.
Cause: The report is a short-prompt LLM output — it pattern-matches to plausible encouragement and can
invent supporting "facts" (market size, demand, financials).
Solution: Stop treating the report as the decision. Keep the structured outputs (competitor map, target
audience, "Critical Investor Questions", risks) and run a real demand test — smoke test or pre-sale — via
/sales-idea-validation. Escalate commitment to a card/pre-order for willingness-to-pay signal.

I ran out of AI tokens / hit a project limit

Symptom: The free plan won't let me run more, or a tool says I'm out of tokens.
Cause: Inodash meters by AI tokens per project, and the free tier is ~3 tokens total with 1
workspace / 1 project — it's a demo allotment.
Solution: Upgrade to a tier sized to your usage (Starter ~50/project, Business ~100, Enterprise ~500),
or finalize each idea's framing before spending tokens so you don't burn them on thin input. Confirm
current token limits on inodash.com — they're best-effort here.

I want an API, data export, or a way to automate

Symptom: Want to script Inodash, pull reports into another system, or trigger it from a workflow.
Cause: Inodash has no documented public API, webhooks, or iPaaS connectors; data export is a
Business+ UI feature
, not an endpoint.
Solution: There's no supported programmatic path — export from the browser on a Business+ plan, or use
a tool intended for programmatic use if you need a pipeline. Automate a real demand signal (landing-page
analytics) instead. See /sales-idea-validation.

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常见问题

5 问
答案由本站依据条目字段整理
转化漏斗与成交优化执行怎么安装?

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

转化漏斗与成交优化执行支持哪些客户端?

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。

转化漏斗与成交优化执行权限高吗,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。

转化漏斗与成交优化执行收费吗?

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。

转化漏斗与成交优化执行用什么许可证?

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。