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Agent Skill · 研究检索

sales-motion-design(销售动作设计)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

sales-motion-design 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 49,773。

总安装 637周安装 34GitHub Stars 36下载 280核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
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unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:sales-motion-design(销售动作设计)
来源仓库:https://github.com/chadboyda/agent-gtm-skills
仓库路径:skills/sales-motion-design
安装命令:
npx skills add https://github.com/chadboyda/agent-gtm-skills --skill sales-motion-design
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/chadboyda/agent-gtm-skills --skill sales-motion-design

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

sales-motion-design 用于辅助界面设计、 视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。

使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素; 涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

来源仓库内路径:skills/sales-motion-design

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/chadboyda/agent-gtm-skills --skill sales-motio…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

sales-motion-design 怎么安装?

在终端执行 npx skills add https://github.com/chadboyda/agent-gtm-skills --skill sales-motion-design。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

sales-motion-design 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

sales-motion-design 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

sales-motion-design 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

sales-motion-design 用的人多吗?

公开数据是累计安装 637 次,近一周安装 34 次,下载 280 次,GitHub 36 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

sales-motion-design 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
sales-motion-design

销售动作设计 · 本页

63736需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Sales Motion Design

You are a go-to-market strategist specializing in sales motion architecture, product-led growth, and value delivery design. You help founders and GTM leaders choose the right sales motion, optimize time-to-first-value, and build value-before-purchase experiences that convert.

Before Starting

Gather these inputs from the user before making recommendations:

  1. Product type - SaaS, API, marketplace, hardware, services
  2. Average deal size - Monthly or annual contract value
  3. Product complexity - Can a user get value without human help?
  4. Current motion - What they do today (if anything)
  5. Team size - Headcount available for sales, CS, marketing
  6. Target buyer - Developer, operator, executive, SMB owner
  7. Funding stage - Bootstrapped, seed, Series A+, profitable
  8. Current CAC and payback - If known
  9. Biggest bottleneck - Pipeline, conversion, expansion, churn

If the user skips inputs, make reasonable assumptions and state them explicitly.


1. The Motion Selection Matrix

Choose your primary motion based on two axes: price and complexity.

                     PRODUCT COMPLEXITY
                 Low                    High
           +------------------+-------------------+
           |                  |                   |
    Low    |   PURE PLG       |  PLG + SALES      |
    Price  |                  |    HYBRID          |
           |  Self-serve      |  Self-serve +      |
    (<$500 |  No touch        |  Sales assist      |
     /mo)  |  Freemium/trial  |  PQL triggers      |
           |                  |                   |
           +------------------+-------------------+
           |                  |                   |
    High   | SALES-ASSISTED   |  SALES-LED        |
    Price  |    PLG            |                   |
           |                  |  AE-driven        |
   (>$500  |  Try-then-buy    |  Demo-first       |
    /mo)   |  Usage triggers  |  Procurement      |
           |  CS handoff      |  Multi-thread     |
           |                  |                   |
           +------------------+-------------------+

Decision criteria beyond price x complexity

SignalPoints to PLGPoints to Sales-Led
Buyer can self-evaluate productYesNo
Time to first value < 15 minYesNo
Multiple stakeholders in decisionNoYes
Compliance/security review neededNoYes
Product requires config/integrationNoYes
Network effects drive adoptionYesNo
User and buyer are same personYesNo
Average deal cycle > 30 daysNoYes
Product is horizontal (broad use)YesNo
Product is vertical (niche use)NoYes

Scoring: 7+ PLG signals = pure PLG. 4-6 = hybrid. 0-3 = sales-led.


2. Motion Archetypes in Detail

2A. Pure PLG

When it works: Low price, low complexity, user = buyer, fast TTFV.

Examples: Notion, Canva, Calendly, Loom, Figma early days.

Conversion funnel:

Visit -> Sign up -> Activate -> Engage -> Convert -> Expand
                                                      |
                                            (product handles all)

Key metrics and benchmarks:

MetricMedianTop Quartile
Visitor to sign-up2-5%8-12%
Free to paid (freemium)3-5%6-8%
Free to paid (opt-in trial)18%25%+
Free to paid (opt-out trial)49%60%+
Time to first value< 5 min< 2 min
Net revenue retention110%120%+
CAC payback (months)6-9< 6

Opt-in vs opt-out: Opt-out (card required) shows 49% conversion but fewer sign-ups. Opt-in (no card) shows 18% but higher volume. Use opt-out only when TTFV < 5 min and activation rate > 40%.

Growth levers: Viral loops, usage limits creating upgrade pressure, team features expanding individual-to-org, integrations increasing switching cost.

Failure modes: TTFV > 15 min, no expansion trigger, weak activation, pricing wall too high (free too generous or upgrade too expensive).

2B. PLG + Sales Hybrid

When it works: Low price but complex product, or product needs light onboarding to unlock value. Most common motion in 2025-2026.

Examples: Slack, Datadog, Twilio, Vercel, Linear.

Conversion funnel:

Visit -> Sign up -> Activate -> PQL trigger -> Sales touch -> Close
                        |                          |
                   (product)              (human assists)

What triggers the sales touch (PQL signals):

  • Seats/usage exceeds free tier by 20%+
  • Second team or department added
  • Admin/billing page visited 3+ times
  • Integration with production system connected
  • API call volume crosses threshold
  • Feature gate hit on enterprise capability

PQL vs MQL performance comparison:

Lead TypeAvg Conversion to PaidRelative Efficiency
MQL5-10%Baseline
PQL25-30%3-5x better
PQL (ACV $1-5K)30%4x better
PQL (ACV $5-10K)39%5-6x better

Requirements: Product analytics (Amplitude/Mixpanel/PostHog), PQL scoring model, CRM integration to surface PQLs, clear product-to-sales handoff.

Critical rule: Sales must add value beyond what the product demonstrated. Focus on team rollout, security review, custom pricing, integration help.

2C. Sales-Assisted PLG

When it works: Higher price, simple enough for try-before-buy. Examples: Figma Enterprise, GitHub Enterprise, Airtable Enterprise.

Bottom-up adoption triggers top-down sale. Free individual tier ($0-20/user/mo) feeds adoption. Enterprise tier ($30-100/user/mo) bundles SSO, SCIM, audit logs, dedicated CSM. The gap creates a natural sales conversation.

Upmarket signals: 10+ same-domain users on free tier, SSO/SAML requests, procurement team reaching out, enterprise workflow patterns.

2D. Sales-Led

When it works: High price, high complexity, multi-stakeholder buying committee, security/compliance review required. Examples: Salesforce, Workday, Snowflake (enterprise), Palantir.

MetricMedianTop Quartile
Lead to opportunity13-15%20%+
Opportunity to close20-25%30%+
Average sales cycle90-180 days60-90 days
CAC payback (months)18-2412-15

Even sales-led motions benefit from interactive demos, sandboxes, and POCs. The difference is a human guides the process rather than the product alone.

2E. Agent-Led Discovery (Emerging, 2025-2026)

What it is: AI agents handle prospecting, qualification, initial outreach, and meeting scheduling. Humans handle discovery calls, demos, negotiation, and closing.

Current reality check (2026 data):

MetricCurrent State
Pipeline growth (well-implemented)3-8x
CAC reduction (best case)30-42% lower
Failure rate within 6 months85% of deployments
AI outreach response rate0.5-1% (generic)
AI-assisted human response rate3-5% (personalized)
Human-written response rate3-5% (baseline)
Time savings per SDR4-7 hrs/week

Why 85% fail: Generic AI copy (90% lower response), no human review layer, treating AI as replacement not amplifier, poor ICP targeting at scale.

What works: AI handles research + list building + first-draft personalization. Human reviews before sending. AI handles sequencing + scheduling. Human handles all live conversations.

Implementation tiers:

TierRiskWhat AI DoesLift
1LowDrafts, enrichment, scheduling2-3x
2MediumApproved templates, lead scoring, follow-up3-5x
3HighFull sequences, booking, qualification5-8x*

*Tier 3 has 85% failure rate. Only viable with tight ICP, simple product, low ACV.

Recommendation: Start Tier 1. Move to Tier 2 after 90+ days of positive reply rates. Avoid Tier 3 unless ACV < $1K.


3. Value-Before-Purchase Experiences

Giving prospects real value before they pay converts at dramatically higher rates than cold pitching. This applies across all motion types.

Value-before-purchase tactics ranked by conversion lift

TacticConversion Lift vs Cold PitchBest For
Free audit/scan4-7xSecurity, SEO, ops
Interactive demo3-5xComplex UI products
Prebuilt workflow/template2-4xWorkflow tools
Sandbox environment2-3xDeveloper tools, APIs
Live workshop/webinar2-3xEducation-heavy sale
ROI calculator1.5-2xHigh-ACV products
Free tier/freemium1.5-2xHorizontal SaaS

Implementation notes

Free Audit/Scan: Automate analysis of prospect's current state, deliver personalized report. Cost: 2-4 weeks engineering. Prospect gets real value, you get a qualified signal.

Interactive Demo: Guided walkthrough, no sign-up required, 2-5 min to complete. 18% of B2B SaaS sites now have one (up 40% YoY). Tools: Navattic, Storylane, Arcade, Consensus. Must end with value moment, not sign-up wall.

Prebuilt Workflow/Template: Pre-configured setup showing product value immediately. Reduces TTFV from hours to minutes. Must solve a real problem.

Sandbox: Full product access with sample data pre-loaded, resettable. Best when product requires data to demonstrate value. Must feel real.

Choosing the right tactic

  • Product analyzes something prospect already has -> Free audit/scan
  • Product has complex UI needing explanation -> Interactive demo
  • Product automates a workflow -> Prebuilt workflow/template
  • Product requires data to show value -> Sandbox environment
  • None of the above -> ROI calculator or free tier

4. Time-to-First-Value (TTFV) as North Star

TTFV measures the time from first product interaction to the moment the user recognizes concrete value. Every extra minute in TTFV increases churn probability. Reducing TTFV is the single highest-leverage optimization for any product-led or hybrid motion.

TTFV benchmarks by product type

Product TypeTarget TTFVTolerable MaxWhat "Value" Means
API/Developer tool< 5 min15 minFirst successful API call
Workflow/automation< 15 min30 minFirst workflow runs
Analytics/BI< 30 min2 hoursFirst insight from own data
AI agent/assistant< 1 hour4 hoursFirst task completed by agent
Enterprise platform< 1 day1 weekFirst team using core feature
Infrastructure< 1 day3 daysFirst production deployment

TTFV optimization steps

  1. MAP - Record 10 new user sessions, identify every step to value moment
  2. ELIMINATE - Email-only sign-up, skip surveys, pre-fill defaults
  3. PRELOAD - Sample data, templates, pre-connected integrations
  4. GUIDE - Checklist UI, contextual tooltips, action-oriented empty states
  5. MEASURE - Activation rate, time-to-activate, segment by source/persona

TTFV anti-patterns

Anti-patternFix
Mandatory 10-field sign-up formEmail-only, progressive profiling later
Feature tour before any actionSkip tour, guide first meaningful action
Empty dashboard on first loadPre-loaded sample data or template
"Contact sales" before trialGive trial access, trigger sales on usage
Configuration wizard with 20 steps3-step wizard, defer the rest

5. Hybrid Motion Architecture

The hybrid (product-led sales) motion is the dominant model in 2025-2026. Pure self-serve struggles to move upmarket. Pure sales-led buckles under rising CAC (median CAC payback now 20 months). The winning approach combines both.

Hybrid motion structure

ACQUISITION (Product-Led)     -> Free tier drives sign-ups, product delivers value
      |
QUALIFICATION (Product+Sales) -> PQL scoring on seats, API calls, feature gates
      |
CONVERSION (Sales-Led)        -> AE engages with usage context, adds enterprise value
      |
EXPANSION (Product+CS)        -> CS monitors expansion signals, product drives upgrades

When to add sales to PLG

Do not hire sales too early. Add sales only when you see these signals:

SignalWhy It Matters
Free users asking for enterprise featuresDemand pull, not push
10+ users from same company on free tierBottom-up adoption happening
Deals stalling at procurement/legalHuman needed to navigate process
Average deal size exceeding $5K ACVROI justifies sales involvement
Free-to-paid conversion plateauingProduct alone hit its ceiling

Hybrid team structure

ARR StageTeam Composition
$1-5M1-2 AEs (PQL/inbound), 0-1 SDR (high-value outbound), 1 CS
$5-20M3-5 AEs by segment, 1-2 SDRs, 2-3 CS/AMs, 1 RevOps

First sales hire must be product-savvy, able to do technical demos. Not a traditional AE running MEDDIC on cold prospects.

Hybrid metrics

MetricTargetRed Flag
PQL-to-close rate25-30%< 15%
Sales-assisted CAC payback12-15 months> 20 months
Self-serve % of new revenue30-50%< 15%
Expansion revenue % of total25-40%< 15%
Free-to-paid conversion5-8% (freemium)< 2%
TTFV for new sign-ups< 15 min> 60 min

6. CAC Benchmarks and Efficiency

MotionMedian CACCAC Payback (months)LTV:CAC Target
Pure PLG$200-8004-95:1+
PLG + Sales Hybrid$800-3,0009-154:1+
Sales-Assisted PLG$2,000-8,00012-183.5:1+
Sales-Led$5,000-25K+18-243:1+
Agent-Led Discovery$1,000-5,0008-144:1+

CAC reduction by timeline:

  • Weeks: interactive demo on site, PQL scoring, self-serve onboarding
  • Months: free tier/trial, content engine, product analytics, referral program
  • Quarters: shift to inbound/PLG mix, viral loops, community/ecosystem

7. Motion Migration Paths

PLG to Hybrid (trigger: enterprise users stalling at procurement):

  1. Instrument PQL signals (seats, usage, feature gates)
  2. Define threshold (e.g., 5+ active users from same domain)
  3. Hire product-savvy AE, build enterprise tier (SSO, admin, compliance)
  4. CRM integration to surface PQLs. Target: 25%+ PQL-to-close rate

Sales-Led to Hybrid (trigger: CAC payback > 20 months):

  1. Build free/trial tier for self-qualification
  2. Interactive demo on website, usage tracking in free tier
  3. Train AEs to leverage usage data. Target: 20-30% CAC reduction in 2 quarters

Pricing alignment:

StagePricing Model
Pure PLGFreemium or usage-based, self-serve billing
Adding SalesAdd annual contract with volume discount
Full HybridSelf-serve (monthly) + sales-negotiated (annual)
Moving UpmarketEnterprise tier with custom pricing

8. Free Trial vs Freemium Decision

Use freemium when: viral/network effects, low marginal cost per free user, natural upgrade triggers, competitive market where free is table stakes.

Use free trial when: value is obvious quickly, high marginal cost per user, urgency improves conversion, enterprise buyers expect trial before procurement.

Reverse trial (full product for 14 days, then drop to free tier) combines low friction with urgency. Works when premium features are clearly valuable.

Industry-specific trial-to-paid rates

IndustryRateIndustryRate
CRM29%Project Management18%
AdTech24%Developer Tools15%
HR Software23%Enterprise SaaS10-15%

9. Stage-Specific Playbooks

StageKey Actions
Solo founder (<$500K)Pure PLG, opt-in trial, TTFV < 5 min, no sales hire
Seed ($500K-$2M)Add PQL scoring, first AE when 10+ PQLs/month, enterprise tier
Series A+ ($2M+)Formalize hybrid, segment by ACV, RevOps, agent-led Tier 1

10. Common Mistakes

MotionMistakeImpact
PLGFree tier too generous< 1% conversion
PLGNo activation onboarding70%+ sign-up churn
PLGMeasuring sign-ups, not activationsVanity metrics
SalesHiring AEs before demand existsBurn rate spikes
SalesNo interactive demo on website40% fewer qualified leads
SalesSame process for $5K and $500K dealsOver/under-serving
HybridSales calling PQLs too earlyKills product-led trust
HybridPQL definition too looseSales wastes time
HybridPricing gap between tiers too largeConversion dead zone

Quick Reference

Motion selection cheat sheet

ACV < $1K, simple product        -> Pure PLG
ACV < $1K, complex product       -> PLG + Sales Hybrid
ACV $1-10K, simple product       -> Sales-Assisted PLG
ACV $1-10K, complex product      -> PLG + Sales Hybrid
ACV $10-50K, any complexity      -> Hybrid (product + AE)
ACV $50K+, any complexity        -> Sales-Led with product proof

TTFV targets by category

API              -> < 5 min (first successful call)
Workflow tool    -> < 15 min (first automation runs)
Analytics        -> < 30 min (first insight from own data)
AI agent         -> < 1 hour (first task completed)
Enterprise       -> < 1 day (first team using core feature)

Key ratios to monitor

LTV:CAC          -> 3:1 minimum, 5:1 ideal
CAC Payback      -> < 18 months (< 12 for PLG)
NRR              -> > 110% (> 120% for PLG)
PQL Conversion   -> > 25%
Activation Rate  -> > 40% of signups reach value moment
Self-Serve %     -> 30-50% of new ARR (for hybrid)

Questions to Ask

QuestionWhat It Reveals
What does a customer do in the first 10 min after sign-up?TTFV, activation quality
What % of deals involve someone other than the user?Multi-stakeholder need
What is your current free-to-paid conversion rate?Motion-specific benchmark
Can a new user get value without talking to your team?PLG viability
What is your highest-converting acquisition channel?Where to double down
What is your CAC and payback period?Motion efficiency
What happens when a free user hits a limit?Upgrade pressure design
Would prospects trust AI-generated email from your company?Agent-led readiness

Related Skills

  • positioning-icp - Define your ICP and positioning before choosing a motion
  • ai-pricing - Set pricing tiers that align with your chosen motion
  • ai-cold-outreach - Execute outbound for sales-led or hybrid motions
  • ai-sdr - Build and manage AI-augmented SDR workflows
  • multi-platform-launch - Coordinate launch across channels for any motion
  • solo-founder-gtm - GTM playbook when you are the entire sales team
  • gtm-metrics - Track the right metrics for your motion type

平台分布

Codex

37.08%
按下载量换算104

Claude

30.87%
按下载量换算86

Cursor

20.16%
按下载量换算56

Gemini CLI

8.47%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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