Analyze WebAsk Lead Quality
Survey completion counts can hide missing or unusable contact details. This skill guides assistants through WebAsk reports to assess contact quality, compare channels, and prioritize improvements.
將此請求複製給你的智慧代理，其中包含權威 Skill 頁面和清單。
Review the Skillstore skill "webask-lead-quality" from https://skillstore.io/skills/webaskio-webask-lead-quality.md and its manifest at https://skillstore.io/api/skills/webaskio-webask-lead-quality/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.你的智慧代理仍應顯示其計畫，並依安全政策請求必要確認。
當 AI Agent、爬蟲或腳本需要乾淨脈絡、而不是讀取完整頁面時，請使用這些連結。
正在使用「webask-lead-quality」。 Illustrative data: 512 starters, 243 reached the contact step, 186 submitted contacts, and 164 contacts appear usable. Summarize lead quality.
預期結果:
正在使用「webask-lead-quality」。 Illustrative labeled data: newsletter has 100 starters and 38 usable contacts; website banner has 100 starters and 19. Compare these sources.
預期結果:
All five static findings are false positives: documentation navigation links and Markdown inline text do not execute commands or perform filesystem traversal. No evidence found of prompt injection, credential theft, or unauthorized data disclosure in the supplied files. The skill requests survey reporting tools and explicitly prohibits posting contacts in chat; external tool implementations are outside this review.
分享版本化評估報告、中性徽章、嵌入卡片與引用。Skillstore 只報告證據，不判斷該 Skill 是否安全。
https://skillstore.io/skills/webaskio-webask-lead-quality/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/webaskio-webask-lead-quality?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/webaskio-webask-lead-quality?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/webaskio-webask-lead-quality/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/webaskio-webask-lead-quality.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>webaskio. (2026). webask-lead-quality security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/webaskio-webask-lead-quality/audits/1@techreport{webaskio-webaskio-webask-lead-quality-2026,
author = {webaskio},
title = {webask-lead-quality security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/webaskio-webask-lead-quality/audits/1},
note = {Author version unspecified}
}cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "webask-lead-quality security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
- name: "webaskio"
date-released: "2026-09-29"
url: "https://skillstore.io/skills/webaskio-webask-lead-quality/audits/1"
identifiers:
- type: other
value: "skillstore:webaskio-webask-lead-quality:audit:1"
description: "Skillstore immutable audit report identifier"
Compare apparently usable contact rates across labeled sources to identify channels that generate stronger leads.
Separate survey completions from submissions with apparently usable contacts before evaluating the incoming lead volume.
Identify losses around contact questions and prioritize changes to field requirements, question order, and contact explanations.
Analyze WebAsk survey [survey]. Show starters, contact submissions, apparently usable contacts, and their share of starters. Keep personal contact details out of chat.
Review [survey] and compare response counts before and at the contact question. Estimate the loss and suggest prioritized improvements. State data limitations.
Compare lead quality for each source label in [survey]. Show counts and usable contact rates. Identify missing labels and avoid unsupported cost claims.
Audit [survey] across contact conversion, suspicious values, and labeled channels. Explain denominators and heuristic limits. Rank recommendations by expected impact without changing the survey.
作者
webaskio授權
MIT
Skillstore 修訂
r1
版本提示
作者未聲明版本。
引用
bad9dafc37d1638cd29cb9bab06d5f8dbcd0f6c2
維護新鮮度
2026/9/30
使用量
0 次下載 · 0 次瀏覽
檔案結構
Summarize WebAsk Survey Results
Survey totals and raw responses can make conclusions difficult to identify. This skill guides assistants through WebAsk summaries, filtered reports, and text themes to explain results clearly.
Organize Your WebAsk Workspace
Crowded WebAsk workspaces make completed surveys, active projects, and reusable templates difficult to manage. This skill guides approved cleanup, survey duplication, archiving, and file management through WebAsk MCP tools.
Compare WebAsk A/B Survey Results
Small survey samples can make random differences look like meaningful improvements. This skill guides comparisons using outcome counts, percentage-point differences, and checks for comparable groups.
Compare WebAsk Survey Sources
Survey totals can hide differences between recruitment channels. This skill guides your assistant to compare tagged WebAsk responses by volume, completion rate, and your selected outcome.
Create WebAsk Surveys from a Brief
Turning a survey brief into suitable questions, branching, and formatting takes manual work. This skill guides connected WebAsk tools to create a draft and publish it after your approval.
Prepare WebAsk Surveys for Distribution
Survey responses become difficult to attribute when every channel shares an unlabelled link. This skill guides WebAsk distribution with source labels, QR codes, access passwords, and printable versions.
Score and Clean Prospect Lists
由 cmj-hub
Duplicates, stale signals, and targeting mismatches waste outreach capacity. This skill guides CSV or JSONL list reviews with a weighted rubric, removal reasons, and prioritized cleanup recommendations.
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Visualize Personal Finances in a Local Report
由 jasonhmy
Financial records can obscure spending patterns when transfers, refunds, and shared purchases are mixed together. This skill reconciles authorized records and creates local interactive charts with transaction details and optional daily allowances.
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科學資料檔案很難檢查，因為每種格式儲存結構與中繼資料的方式都不同。此技能會偵測格式、剖析資料品質，並建立實用的 Markdown EDA 報告。
使用 Scanpy 分析單細胞 RNA-Seq
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處理 JSON、YAML 和 TOML 資料
由 0xDarkMatter
結構化設定資料在 JSON、YAML 和 TOML 檔案之間可能難以檢視。此技能會引導使用 jq 和 yq 查詢來進行擷取、篩選、轉換和更新。