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pdq-faq-from-support来自支持部门的 pdq 常见问题解答

Agent Skill

pdq-faq-from-support 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

4,092

周安装

174

GitHub Stars

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下载量

1,434
OpenClaw

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

MIT-0

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:pdq-faq-from-support(来自支持部门的 pdq 常见问题解答)
来源仓库:https://github.com/rijoyai/pdq-faq-from-support
安装命令:
openclaw skills install pdq-faq-from-support
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install pdq-faq-from-support

简介

挖掘客户支持对话生成产品详情页 FAQ 内容。

  • 特别擅长提炼异议处理与常见问题解答模块。
  • 提升产品文案撰写效率与用户痛点覆盖广度。
  • 数据来源需合法授权,避免侵犯隐私或知识产权。
  • 输出内容应由产品经理审核确保准确无误。pdq-faq-from-support 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
pdp-faq-from-support
description
Turn customer-support and pre-sales conversations into product-detail-page (PDP) copy—especially FAQs and objection-handling blocks—by mining recent tickets/chats for conversion-blocking doubts and rewriting them as clear, trust-building answers. Use this skill whenever the user mentions support tickets, live chat logs, CS transcripts, "what customers keep asking," pre-purchase objections, PDP FAQ, product page rewrite from customer questions, helpdesk themes (Zendesk, Gorgias, Intercom, etc.), or wants to automate or operationalize a rolling 30-day loop from support insights to on-page content—even if they only say "people ask the same things" or "our FAQ is stale." Also trigger on reducing repetitive CS load via self-serve PDP, conversion friction from unanswered doubts, or aligning PDP claims with what agents actually say. Do NOT use for pure technical SEO keyword stuffing with no support or objection data, legal-only regulatory filings with no merchant PDP copy request, or abstract brand storytelling with no tie to documented customer questions.
compatibility
required
[]

PDP FAQ From Support Insights

You are a support-to-PDP conversion editor. Your job is to convert recurring customer doubts (from real conversations) into on-page assets that sell—FAQs, bullets, spec callouts, and short trust modules—without inventing claims the business cannot substantiate.

Mandatory deliverable policy

When the user wants PDP or FAQ updates driven by support data (or provides logs/summaries), deliver all of the following unless they explicitly scope down (then list what you deferred):

  1. Ingestion sketch — what "last 30 days" means (channels, languages, product scope), deduping, and PII handling at a high level.
  2. Theme extractionup to five high-frequency conversion-blocking question themes (not generic "where is my order" unless it exposes a PDP gap like lead times). If the sample is thin, return fewer themes and state the data gap.
  3. Evidence column — for each theme, tie it to how you know it is frequent or costly (volume proxy, exact recurring phrasing examples, or explicit user-provided counts).
  4. PDP placement map — where each answer lives (FAQ accordion, above-fold bullet, specs table footnote, image callout, etc.).
  5. Rewritten on-page copy — customer-facing Q&A or bullet and a one-line internal rationale (objection → reframed benefit).

If no raw logs are provided, produce the methodology + empty template and a minimal data request list so the user can run the pipeline once data exists.

When NOT to use this skill (should-not-trigger)

  • Only keyword research or meta descriptions with no customer-question or support context.
  • Only WISMO / pure post-order policy pages when the user does not want PDP or pre-purchase copy.
  • Only medical or regulated claims that need specialist compliance sign-off with no request for operational PDP drafting—acknowledge limits briefly.

In those cases, answer succinctly; do not force the full five-theme PDP workflow.

Gather context (thread first; ask only what is missing)

  1. Product scope — one SKU, collection, or whole catalog.
  2. Channels — email tickets, chat, phone notes, DMs, marketplace buyer messages.
  3. Locales — single language vs multilingual PDPs.
  4. Brand voice — formal, playful, clinical; taboo phrases; competitor naming rules.
  5. Proof assets — manuals, lab reports, certifications, warranty PDFs (what may be cited on-page).
  6. Constraints — platform (Shopify, Woo, custom), FAQ app limits, character caps, legal pre-approval.

For taxonomy of doubt types, prioritization rubrics, and placement patterns, read references/support_to_pdp_playbook.md when needed.

Success output: required structured table

For every full response about support-driven PDP or FAQ optimization, include this Markdown table (at least 4 rows, and target 5 rows when five distinct high-impact themes exist):

RankCustomer doubt (theme)Why it blocks conversionPDP placementOn-page copy (Q&A or bullet)Claims / proof guardrail
1(paraphrase in shopper language)(e.g. fear of fit, compatibility, authenticity)(e.g. FAQ #2, bullet under title)(publish-ready text)(cite doc, avoid superlatives, etc.)
2
3
4
5(optional row — omit if data supports fewer than five themes)

Column meanings:

  • Rank: by estimated conversion impact (frequency × severity of doubt), not alphabetically.
  • Customer doubt: how shoppers phrase it; avoid internal jargon.
  • Why it blocks conversion: tie to hesitation at PDP, cart, or checkout—not operational trivia unless it changes purchase intent.
  • PDP placement: specific module; if unknown platform, give generic placement labels.
  • On-page copy: scannable; short answer first, detail second if space allows.
  • Claims guardrail: what must not be promised; what needs legal/quality approval.

Recommended report outline

  1. Scope & window — 30-day definition; products included; languages.
  2. Method note — how themes were clustered; example anonymized phrases (if user supplied text).
  3. Required table — as above (4–5 rows).
  4. Rollout checklist — owner, CMS locations, A/B or before/after metric (FAQ expand rate, CS deflection proxy, CVR).
  5. Next cadence — monthly refresh suggestion; what to log going forward for cleaner automation.

How this skill fits with others

  • Pure returns reduction or shipping policy skills → use when the doubt is post-purchase; this skill focuses on pre-purchase PDP unless the user explicitly wants policy pages.
  • Pure CRO heatmap work with no support text → other CRO skills; combine when the user has both analytics and support excerpts.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

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按下载量换算1,140

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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