webask-results-digest
77Summarize 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.
Assess Survey Sample Size
Survey teams need to know whether current responses support a decision and which gaps remain. This skill checks overall and subgroup counts, then gives practical collection guidance.
Kopieren Sie diese Anfrage in Ihren Agent. Sie enthält die maßgebliche Skill-Seite und das Manifest.
Review the Skillstore skill "webask-sample-oracle" from https://skillstore.io/skills/webaskio-webask-sample-oracle.md and its manifest at https://skillstore.io/api/skills/webaskio-webask-sample-oracle/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Ihr Agent sollte weiterhin seinen Plan anzeigen und alle von der Sicherheitsrichtlinie verlangten Bestätigungen anfordern.
Verwenden Sie diese Links, wenn ein KI-Agent, Crawler oder Skript sauberen Kontext benötigt, statt die vollständige Seite zu lesen.
„webask-sample-oracle“ wird verwendet. We have 318 completed responses. Can we summarize the overall result?
Erwartetes Ergebnis:
Yes. The sample supports an overall directional summary. Treat subgroup comparisons separately if their counts are lower.
„webask-sample-oracle“ wird verwendet. Can we compare the Moscow and Yekaterinburg results?
Erwartetes Ergebnis:
The comparison is premature if one segment has fewer than about 100 responses. Continue collection or label the comparison as uncertain.
„webask-sample-oracle“ wird verwendet. How many responses are useful for a general mood check?
Erwartetes Ergebnis:
About 30 to 50 responses can support a rough directional read. This is an estimate, not a guarantee of representativeness.
All three static findings are false positives. The flagged text is documentation content: relative Markdown links, a survey-results table row, and an inline tool name, with no filesystem mapping or command execution evidence.
Teile den versionierten Bewertungsbericht, das neutrale Badge, die Einbettungskarte und Zitate. Skillstore berichtet Nachweise, ohne zu entscheiden, ob dieser Skill sicher ist.
https://skillstore.io/skills/webaskio-webask-sample-oracle/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/webaskio-webask-sample-oracle?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/webaskio-webask-sample-oracle?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/webaskio-webask-sample-oracle/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/webaskio-webask-sample-oracle.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-sample-oracle security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/webaskio-webask-sample-oracle/audits/1@techreport{webaskio-webaskio-webask-sample-oracle-2026,
author = {webaskio},
title = {webask-sample-oracle security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/webaskio-webask-sample-oracle/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-sample-oracle 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-sample-oracle/audits/1"
identifiers:
- type: other
value: "skillstore:webaskio-webask-sample-oracle:audit:1"
description: "Skillstore immutable audit report identifier"
Check whether current customer responses support an internal product decision.
Estimate the additional responses needed before publishing a survey readout.
Separate reliable overall findings from under-sampled city or segment comparisons.
Review the survey summary and tell me whether there are enough responses for an overall directional conclusion.
Use the current survey counts to estimate how many more responses are needed for approximately five percent precision.
Assess whether each requested segment has enough responses to support a comparison, and identify the weakest segments.
Review the total and segment counts, explain which decisions are supported now, and recommend whether to stop or continue collection.
Autor
webaskioLizenz
MIT
Skillstore-Revision
r1
Versionshinweis
Der Autor hat keine Version angegeben.
Ref.
bad9dafc37d1638cd29cb9bab06d5f8dbcd0f6c2
Aktualität der Wartung
30.9.2026
Nutzung
0 Downloads · 0 Aufrufe
Dateistruktur
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.
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.
Analyze WebAsk Survey Comments by Theme
Open survey responses are difficult to compare as long lists of comments. This skill organizes WebAsk responses into themes with counts, percentages, and representative quotes.
Check WebAsk Survey Data Quality
Suspicious survey responses can distort results and weaken decisions. This skill guides checks of WebAsk responses and compares key metrics before recommending exclusions.
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.
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