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sales-lindy销售林迪

Agent Skill

sales-lindy 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

329

周安装

14

GitHub Stars

13

下载量

115
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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-lindy(销售林迪)
来源仓库:https://github.com/sales-skills/sales
仓库路径:skills/sales-lindy
安装命令:
npx skills add https://github.com/sales-skills/sales --skill sales-lindy
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/sales-skills/sales --skill sales-lindy

简介

sales-lindy 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于关键词或任务导向的信息搜索场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装并使用。
  • 安装前需评估权限、维护状态及可能的联网或文件操作。
  • 建议结合原始文档核验具体实现逻辑。

SKILL.md

Lindy Platform Help

Step 1 — Gather context

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

  1. What are you trying to do?

- A) Set up Lindy for email + meeting management (personal AI assistant) - B) Build a custom AI agent workflow ("Lindy") for a specific task - C) Fix an existing agent that's not working right - D) Understand pricing / credits / plan limits - E) Compare Lindy to another tool - F) Something else

  1. Which Lindy modules are you using?

- A) Email triage and drafting - B) Meeting recording and notes - C) Calendar management and scheduling - D) Custom workflow builder (triggers, actions, HTTP requests) - E) AI phone calls - F) Chatbot / customer support agent - G) Multiple / all of the above

  1. What plan are you on?

- A) Free / trial - B) Plus ($49.99/mo) - C) Pro ($99.99/mo) - D) Max ($199.99/mo) - E) Enterprise - F) Not sure

Skip-ahead rule: if the user's prompt already contains enough context, skip to Step 2.

Step 2 — Route or answer directly

Problem domainRoute to
Picking a dedicated AI note-taker (Fathom vs Fireflies vs Gong etc.)/sales-note-taker {user's question}
General meeting scheduling strategy (Calendly, Chili Piper, etc.)/sales-meeting-scheduler {user's question}
Building chatbot flows across WhatsApp/Telegram/Messenger/sales-chatbot {user's question}
General CRM-to-tool integration patterns (Zapier, Make, iPaaS)/sales-integration {user's question}

Otherwise, answer directly below.

Step 3 — Lindy platform reference

Read references/platform-guide.md for the full platform reference — modules, pricing, integrations, workflow builder, credit system, and agent templates.

Answer the user's question using only the relevant section. Don't dump the full reference.

Step 4 — Actionable guidance

You no longer need the platform guide — focus on the user's specific situation.

Credit optimization: If credits are the concern, identify which actions consume the most credits and suggest simplifying workflows — use static payloads instead of "Prompt AI" mode, reduce unnecessary AI reasoning steps, batch operations where possible.

Agent debugging: If a workflow is failing, check trigger configuration first, then verify each action step has correct inputs from prior steps. Use Lindy's troubleshooting guide for common errors.

Tool comparison: If comparing Lindy to a specialized tool, emphasize that Lindy excels as a generalist AI assistant but dedicated tools (Fathom for note-taking, Calendly for scheduling, Zapier for simple automation) often outperform in their specific domain.

If you discover a gotcha, workaround, or tip not covered in references/learnings.md, append it there.

Gotchas

*Best-effort from research — review these, especially items about plan-gated features and credit consumption that may be outdated.*
  • Credits deplete faster than expected. Simple workflows use 1-3 credits but AI-intensive tasks (Prompt AI body mode, complex reasoning, phone calls) consume 10+ credits per action. Monitor credit usage in the dashboard before building multi-step workflows.
  • Pricing page and review sites show different tier structures. Lindy may be A/B testing or transitioning pricing models — the in-app pricing when you sign up is authoritative, not the marketing page.
  • Computer use is Pro+ only. If your workflow requires browser automation or screen interaction, you need the Pro plan ($99.99/mo) or higher.
  • Complex multi-step workflows are unreliable. Multiple reviews report "constant errors" when chaining 5+ actions with conditional logic. Start simple, test each step, then chain. Traditional automation tools (Make, n8n) are more reliable for deterministic multi-step flows.
  • No public developer API. You cannot build ON Lindy — there's no REST API to programmatically create agents, trigger workflows externally, or read results. The HTTP Fetch action lets Lindy call OTHER APIs, not the reverse.
  • Cancellation process has complaints. Multiple Trustpilot reviews report charges continuing after cancellation. Cancel through the web dashboard AND confirm via email to support@lindy.ai.
  • Inbox limits scale by plan. Plus connects 2 inboxes, Pro 3, Max 5. If you need more email accounts, you need a higher tier.

Related skills

  • /sales-note-taker — Picking or integrating an AI meeting note-taker across 24+ platforms
  • /sales-meeting-scheduler — Meeting scheduling strategy (Calendly, Chili Piper, booking pages, no-show reduction)
  • /sales-chatbot — Chatbot marketing and conversational automation across channels
  • /sales-integration — General tool integration patterns (Zapier, Make, webhooks, APIs)
  • /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

Examples

Example 1: Setting up Lindy as a personal AI assistant

User says: "I want Lindy to manage my inbox and take meeting notes — how do I set it up?" Skill does:

  1. Walks through account creation and 7-day free trial
  2. Connects Gmail/Outlook inbox and Google Calendar
  3. Configures email triage rules — what to flag, draft, or ignore
  4. Enables meeting recording with auto-join settings
  5. Sets up iMessage/Slack access for on-the-go delegation
  6. Warns about credit consumption — suggests starting with Plus plan and monitoring usage before upgrading Result: Fully configured personal AI assistant managing email and meetings

Example 2: Credits burning too fast

User says: "I'm on the Pro plan and running out of credits by the 15th of every month" Skill does:

  1. Identifies high-credit-consuming actions (Prompt AI mode, phone calls, complex reasoning chains)
  2. Suggests replacing "Prompt AI" body mode with static JSON payloads where possible
  3. Recommends breaking complex agents into simpler, focused ones that use fewer reasoning steps
  4. Calculates whether upgrading to Max ($199.99/mo, 7x usage) is more cost-effective than buying add-on credits ($10/1K)
  5. Notes that simple trigger-action workflows (1-3 credits) vs AI-intensive tasks (10+ credits) — restructure workflows to minimize AI reasoning steps Result: Credit optimization strategy with concrete actions to reduce consumption

Example 3: Comparing Lindy to dedicated tools

User says: "Should I use Lindy for meeting notes or get Fathom?" Skill does:

  1. Notes Lindy is a generalist — meeting notes are one feature among email, calendar, workflows
  2. Fathom is purpose-built for meeting notes — deeper CRM sync, better transcript search, dedicated coaching features, free tier with unlimited recordings
  3. Lindy advantage: single tool for email + meetings + calendar + custom workflows
  4. Fathom advantage: better note quality, native HubSpot/Salesforce field mapping, lower cost for notes-only use case
  5. Recommends Fathom if meeting notes are the primary need, Lindy if they want an all-in-one AI assistant Result: Clear comparison with recommendation based on primary use case

Troubleshooting

Agent workflow produces errors on multi-step automations

Symptom: Workflow runs the first 1-2 steps but fails on subsequent actions with vague error messages Cause: AI reasoning between steps loses context, or dynamic data references from prior steps aren't structured as expected Solution: Break complex workflows into smaller, focused agents. Use static/manual body mode instead of "Prompt AI" for predictable API payloads. Test each action step independently before chaining. Check that each action's output matches the expected input format of the next step.

Meeting notes not appearing after calls

Symptom: Lindy was supposed to record a meeting but no transcript/notes appeared Cause: Calendar sync disconnected, auto-join not enabled for that meeting type, or meeting platform (Zoom/Teams/Meet) blocked the bot Solution: Verify calendar integration is active in Settings. Check that auto-join is enabled for the correct calendar. For Zoom, ensure "Only authenticated users can join" isn't blocking Lindy. For Teams, check org policies for external bot access. Try a test meeting to confirm the flow works end-to-end.

Email drafts don't match your writing style

Symptom: Lindy's email drafts sound generic or don't match your tone Cause: Lindy hasn't learned enough from your writing patterns yet, or the style training needs more examples Solution: Provide explicit style instructions in your Lindy settings — tone (formal/casual), signature preferences, common phrases you use. Send more emails through Lindy and provide feedback (approve/edit/reject drafts) to train the model. It typically takes 20-30 interactions before style matching improves noticeably.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

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按下载量换算42

Claude

29.42%
按下载量换算34

Cursor

17.66%
按下载量换算20

Gemini CLI

9.35%
按下载量换算11

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通过

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安装前确认

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