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Agent Skill · 研究检索

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

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。

pdq-faq-from-support 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,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 24,125。

总安装 4,092周安装 174GitHub Stars 公开资料未说明下载 1,434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
许可证
MIT-0
版本
1.0.0

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

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。

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。

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 OpenClaw;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 openclaw skills install pdq-faq-from-support;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

pdq-faq-from-support 怎么安装?

在终端执行 openclaw skills install pdq-faq-from-support。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pdq-faq-from-support 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

pdq-faq-from-support 需要什么权限?

权限级别是只读。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。

pdq-faq-from-support 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pdq-faq-from-support 用的人多吗?

公开数据是累计安装 4,092 次,近一周安装 174 次,下载 1,434 次。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。

pdq-faq-from-support 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
pdq-faq-from-support

来自支持部门的 pdq 常见问题解答 · 本页

4,092—只读MIT-0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

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 extraction — up 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.

平台分布

OpenClaw

79.49%
按下载量换算1,140

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

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

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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