Great Question 销售线索与客户运营|简诗 AI

SKILL商业运营
商业运营 未标注权限 许可证不明确
安装这个技能

围绕“Great Question 销售线索与客户运营”提供具体执行方法,涵盖用户需求、方案设计、优先级和验证迭代。

一句话选型结论

按资料字段整理

Great Question 销售线索与客户运营|简诗 AI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-great-question
  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
最近核验未标注上游最后核验时间 · 数据更新 1791655001
正文体量18.2 KBSKILL.md 原文大小,越大说明说明书写得越细

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
Great Question 销售线索与客户运营|简诗 AI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

18.2 KB
模型实际读到的说明书原文,来自技能仓库

Great Question Platform Help

Great Question (greatquestion.co) is an all-in-one UX research platform — "the UX research platform
for every team building and improving products." It bundles three jobs teams usually buy separately:
recruit (a 6M+ B2B/B2C panel and your own customers via a built-in Research CRM —
segmentation, eligibility rules, scheduling, automated incentives via Tremendous), run studies
(moderated + AI-moderated [beta] interviews, unmoderated Figma prototype testing, surveys, focus
groups, card sorting, tree testing, online tasks, observer rooms, blind studies), and analyze & store
(a centralized research repository, AI synthesis, highlight reels).

Its place in the landscape is the research-ops / real-participant class — closest to User Interviews
(recruitment) + Dovetail (repository) combined
, run on real people. It is not a synthetic-persona
tool (Synthetic Users, Ditto) and not a pure AI-moderated-interview tool (User Intuition, Strella,
Voicepanel) — moderation is primarily human/scheduled, with AI moderation in beta.

Two things to say almost every time:
- Real research, but a stated "I'd pay" is still not a purchase. Interviews and unmoderated tasks surface
genuine reasoning/objections/language (strong signal) — but the WTP go/no-go belongs to a real behavior test (pre-sale, smoke test), not a transcript → /sales-idea-validation.
- The automation surface is unusually complete — pick the right one. Great Question has a REST API, HMAC-signed webhooks,
and a native MCP server all at once (MCP for agent ops, REST for a pipeline, webhooks for event sync) — but note the gates: API tokens need Team/Enterprise, and MCP is Enterprise/early-access.

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 Great Question?
    - A) Set up a study — pick a method (moderated/AI-moderated interview, unmoderated Figma test,
    survey, card sort, tree test, focus group), objective, screener, incentive
    - B) Recruit — the 6M+ panel (screening/eligibility) vs your own customers (Research CRM import)
    - C) Analyze — repository, AI synthesis, highlight reels, sessions
    - D) Automate / integrate — REST API pipeline, webhooks, the MCP server, or Zapier/Make
    - E) Choose / price — self-serve ($129/seat, 5-seat cap) vs Enterprise, or GQ vs another tool
  2. Is this discovery (strangers on the panel) or feedback from your own users? That decides panel
    vs Research-CRM and how honest the signal is.

Skip-ahead: if the user wants to compare research tools across the market or the
validate-before-building method, that's a /sales-idea-validation question — route in Step 2.

Step 2 — Route or answer directly

If the user's question is about… Route to
Comparing research/idea/synthetic tools across the market, or the validate-before-building method /sales-idea-validation {question}
Running a real behavior demand test (smoke-test page, waitlist, pre-sale) after research /sales-idea-validation or /sales-funnel {question}
Analyzing existing NPS/CSAT/VoC feedback (post-launch surveys, not new studies) /sales-customer-feedback {question}
A synthetic-persona approach (AI personas instead of real people) /sales-syntheticusers or /sales-ditto {question}
A pure AI-moderated real-human interview tool with a self-serve API/webhooks /sales-userintuition {question}

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

Otherwise, answer Great Question-specific questions using Step 3.

Step 3 — Great Question reference

Read references/platform-guide.md for the full reference — the module/automation-surface table
(API vs webhook vs MCP vs UI-only), best-effort pricing/plan gates, the Study → Candidate → Participant →
Session data model, recruiting (panel vs Research CRM), and quick-start recipes (REST sync, CRM upsert,
webhook verification, MCP). Read references/great-question-api-reference.md for the verbatim API
surface (Bearer auth + non-standard header, endpoints, JSON models, webhook HMAC, MCP). Answer using only
the relevant section — don't dump the full reference.

Step 4 — Actionable guidance

  • Say the caveat: real research is not a purchase. Whatever the user asks, make explicit that Great
    Question studies real people (a step up from synthetic personas — genuine reasoning, objections,
    language), but a stated "I'd pay" in an interview/survey is not observed demand. Keep the
    why/objections/language; take the go/no-go from a real behavior test (smoke-test click, pre-sale)
    → /sales-idea-validation.
  • Match the automation surface to the job, and name the gates. Great Question has all three: REST
    API
    (data pipeline into a CRM/warehouse), HMAC-signed webhooks (event-driven sync), and a
    native MCP server (agent-driven study/candidate ops from Claude/Cursor). Recommend by job — but
    always state the plan gates: API tokens require Team/Enterprise (admin-generated at Account >
    API tokens; access enabled by support), and MCP is Enterprise/early-access. No self-serve API key.
  • For webhooks, warn it's concierge + no retries. Endpoints are set up by contacting support (no
    self-serve UI) and there's no documented retry policy — verify the HMAC signature
    (X-Signature-SHA256: t=<ts>,v1=<sig>, sign ts + "." + body, timing-safe compare) and add a
    reconcile poll (GET /v1/studies/{id}/participants) to catch missed participation.completed events.
  • Note the non-standard auth header and beta status. The documented header is literally
    Authorization: "BEARER: <token>" (with BEARER: and quotes) and the API is V1.0 / beta, under
    active development
    — tell the user to confirm the exact header spelling and base host in their
    Account > API tokens screen, and to code defensively against changes.
  • Watch the 5-seat self-serve cap. Self-Serve is $129/seat/mo, capped at 5 seats (unlimited free
    observer seats). Focus groups, card sort/tree test, Salesforce/Snowflake/Qualtrics/Databricks
    connectors, SSO/SCIM, HIPAA, and MCP are Enterprise-only (quote-only). If the user needs any of
    those or a 6th seat, they're on the Enterprise path — flag it early; present all pricing as best-effort
    (confirm at greatquestion.co/pricing).
  • Panel vs Research CRM: match to the question. The 6M+ panel reaches strangers for
    discovery/concept tests; your own customers (CSV import, POST /v1/candidates upsert by email, or
    Salesforce/Snowflake connectors) are the honest audience for churn/win-loss feedback — check
    consented_at/unsubscribed before contacting; use POST /v1/studies/{id}/candidates (≤5,000, poll
    status_url) for a study-scoped batch. Before wiring MCP, enable "Hide PII via MCP" and connect
    with a role scoped to what the agent should do (MCP mirrors your in-app permissions).

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) — pricing ($129/seat self-serve, 5-seat cap; Enterprise quote-only),
panel size ("6M+"), the V1.0-beta API surface, and MCP early-access status all move; verify at
greatquestion.co/pricing and developer.greatquestion.co.

  • Real ≠ demand. Studies reveal the why better than any synthetic tool, but a stated intent to pay
    is not a purchase — the go/no-go still belongs to a real behavior test (pre-sale, smoke test).
  • API tokens are plan-gated (Team/Enterprise) and access must be enabled. Not available on the
    $129 self-serve plan by default — admins generate tokens at Account > API tokens, and support must
    enable API access for the workspace. Don't assume an instant key.
  • The auth header is non-standard. Documented as Authorization: "BEARER: <token>" (with the colon
    and quotes) — verify exact spelling in-app; the API is V1.0/beta, so code defensively.
  • Webhooks are concierge-registered with no documented retries. Email support to set up an endpoint;
    verify the HMAC signature and poll to reconcile missed participation.completed events.
  • MCP is Enterprise / early-access. https://greatquestion.co/api/mcp/v1 (OAuth, 112+ actions) is
    not instant self-serve — request access. Enable "Hide PII via MCP" and connect with a scoped role.
  • The 5-seat self-serve cap + Enterprise-only methods are the real constraints. A growing team (6th
    seat), focus groups, card sorting, tree testing, warehouse/CRM connectors, SSO, HIPAA, or MCP all
    push you to Enterprise (quote-only) — don't design a self-serve card-sort study.
  • G2 reviewers flag occasional bugs, slow performance, and "limited survey features." Set
    expectations for complex surveys; the platform's strength is consolidation, not depth in every module.

Related skills

  • /sales-idea-validation — The tool-agnostic validate-before-building method + the full research/persona/validator tool landscape (use this to decide build-or-not; a research "yes" is not demand). Install: npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code
  • /sales-customer-feedback — Analyze existing NPS/CSAT/VoC feedback across tools (Great Question runs new studies and stores them in its repository; this is the post-launch feedback-strategy peer). Install: npx skills add sales-skills/sales --skill sales-customer-feedback -a claude-code
  • /sales-notably — Notably (notably.ai) — the analysis-only research repository peer: it synthesizes qualitative data you already have (transcripts/notes/open-ends) into AI-clustered themes + insights, where Great Question recruits and runs the studies that produce that data. The pick for the synthesis step once you have data — but it has no panel/recruiting and no API/webhooks/MCP (Miro/FigJam sync + manual export only). Install: npx skills add sales-skills/sales --skill sales-notably -a claude-code
  • /sales-userintuition — Pure real-human AI-moderated interviews with a self-serve REST API + webhooks + MCP — the pick when you want deep automated interviews, not an all-in-one recruit+repository suite. Install: npx skills add sales-skills/sales --skill sales-userintuition -a claude-code
  • /sales-respondent — Respondent (respondent.io) — the recruit-only peer (the direct twin of User Interviews): recruit + screen + schedule + pay real participants from a 4M+ B2B/professional panel via a Partner REST API, then run the study in your own tool. The pick when you only need recruiting (not Great Question's run + repository). Install: npx skills add sales-skills/sales --skill sales-respondent -a claude-code
  • /sales-lookback — Lookback (lookback.com) — the self-serve, run-the-live-session peer: live/moderated video interviews + usability tests with observer rooms and best-in-class mobile screen+gesture recording (recruits via User Interviews, no own panel). The pick when you want to run the live session yourself rather than Great Question's all-in-one recruit+repository suite — but it's UI-first (no self-serve API). Install: npx skills add sales-skills/sales --skill sales-lookback -a claude-code
  • /sales-participant-kit — Participant Kit (participantkit.com, formerly Consent Kit) — the consent + participant-ops peer: informed consent forms/NDAs with e-signatures + audit trail, a participant CRM + opt-in panels, retention/deletion reminders, and UK/EU data residency — the compliance/ops layer around studies, where Great Question runs and stores them. The pick when the job is consent/GDPR governance, not recruit-and-run — but its API is Enterprise + request-only (no webhooks/MCP). Install: npx skills add sales-skills/sales --skill sales-participant-kit -a claude-code
  • /sales-syntheticusers — Synthetic-research studies (AI personas, not real people) for a fast, cheap directional pre-test before spending on real recruits. Install: npx skills add sales-skills/sales --skill sales-syntheticusers -a claude-code
  • /sales-funnel — Build the smoke-test / fake-door landing page that turns a research hypothesis into a real demand test. Install: npx skills add sales-skills/sales --skill sales-funnel -a claude-code
  • /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: "How do I sync completed Great Question research into my warehouse?" (developer/automation)

User says: "I want completed interviews and participant data flowing into Snowflake automatically."
Skill does: Lays out the three surfaces and picks by job — a REST pipeline (GET /v1/studies?status=closed → GET /v1/studies/{id}/participants, paginated 100/page, Bearer auth) for a
scheduled pull, plus participation.completed webhooks (HMAC-verified) for near-real-time sync,
with a poll to reconcile since retries are undocumented. Flags that API tokens require a
Team/Enterprise plan
and API access must be enabled by support, and that the header is the
non-standard Authorization: "BEARER: <token>". Notes native Snowflake/Salesforce connectors are
Enterprise-gated as a no-code alternative.
Result: The user builds a webhook + reconcile-poll pipeline and knows the plan gate up front.

Example 2: "The interviews loved my concept — should I build it?"

User says: "I ran 15 Great Question interviews and a survey; people said they'd pay. Green light?"
Skill does: Credits the signal as real (actual people, genuine reasoning — far better than a
synthetic tool), then draws the line: a stated "I'd pay" in a study is not a purchase. Tells the
user to mine the repository highlight reels and transcripts for objections, hesitation, and pricing
language, then take the go/no-go from a real behavior test (pre-sale or "buy" click) via
/sales-idea-validation.
Result: The founder keeps the qualitative depth and runs a pre-sale before committing to build.

Example 3: "Is the $129 plan enough for my team, and can I run a card sort?"

User says: "We're 6 people and want card sorting and Salesforce sync on the self-serve plan."
Skill does: Flags two Enterprise gates on Self-Serve: it's capped at 5 seats (a 6th person
pushes you to Enterprise), and card sorting, tree testing, and the Salesforce/Snowflake connectors
are Enterprise-only
. Explains Self-Serve is $129/seat/mo (unlimited free observer seats, 100
participants / 100 hr storage) and Enterprise is quote-only, all best-effort — confirm at
greatquestion.co/pricing.
Result: The team plans the Enterprise conversation instead of hitting the wall mid-setup.

Troubleshooting

"Where's my Great Question API key? I'm on the self-serve plan"

Symptom: You can't find an API token screen or your calls 401.
Cause: API tokens require a Team or Enterprise plan, are admin-generated (Account > API
tokens), and API access must be enabled for the workspace by Great Question support.
Solution: Confirm you're on Team/Enterprise, have an admin generate the token, and email
support@greatquestion.co to enable API access. Use the documented header exactly:
Authorization: "BEARER: <token>" (verify the spelling in-app; the API is V1.0/beta).

"My webhook never fired / I missed a completion event"

Symptom: participation.completed didn't arrive, or arrived and you can't verify it.
Cause: Webhook endpoints are registered by contacting support (no self-serve UI), and there's
no documented retry policy.
Solution: Ask support to register your endpoint; verify each request's X-Signature-SHA256
(t=<ts>,v1=<sig> — sign ts + "." + rawBody with HMAC-SHA256, timing-safe compare); and add a
reconcile poll (GET /v1/studies/{id}/participants) to catch anything the webhook missed.

"My agent can't run a card sort / can't see a study over MCP"

Symptom: The MCP connection works but a method or study is unavailable.
Cause: MCP mirrors your in-app role and plan — card sorting/tree testing/focus groups are
Enterprise-only
, and if a study is hidden from your UI role it's hidden from MCP. MCP itself is
Enterprise/early-access.
Solution: Confirm MCP access is enabled (request it), connect with a role scoped to the studies you
need, and enable "Hide PII via MCP" to redact candidate PII before it reaches the agent. For
Enterprise-only methods, use the UI on an Enterprise plan.

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    获取使用帮助和更多实用 Skill,请关注公众号「简诗 AI」,或在 SkillHub 搜索「简诗 AI」

常见问题

5 问
答案由本站依据条目字段整理
Great Question 销售线索与客户运营|简诗 AI怎么安装?

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

Great Question 销售线索与客户运营|简诗 AI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。

Great Question 销售线索与客户运营|简诗 AI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。

Great Question 销售线索与客户运营|简诗 AI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。

Great Question 销售线索与客户运营|简诗 AI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 未标注。