Skip to main content

audit-a-web-analytics-implementation

Audit web analytics for event meaning, consent, identity, payload quality, duplication, loss, attribution, governance, and report reconciliation. Use when metrics are untrusted, tracking changes, or privacy and decision risks need review.

소스 정보

저장소
protosphinx/sphinxstack
최근 소스 활동
2026년 7월 29일 13:55
감지된 SKILL.md 언어
영어
스타
3
포크
0

설치 방법

기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.

소스 파일 검토

설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.

파일 탐색기
2 개 파일

SKILL.md 표시 중

SKILL.md
소스 지침 · 읽기 전용 미리보기
name
audit-a-web-analytics-implementation
category
web
description
Audit web analytics for event meaning, consent, identity, payload quality, duplication, loss, attribution, governance, and report reconciliation. Use when metrics are untrusted, tracking changes, or privacy and decision risks need review.
# audit-a-web-analytics-implementation Trace a representative user action from interface through collection to the report. ## When to use - Use before major decisions, after instrumentation changes, or during privacy and data-quality reviews. - Do not collect secrets, raw form values, sensitive URLs, or unnecessary personal data. ## Procedure 1. Define decisions, metrics, users, regions, platforms, consent states, environments, and authoritative event specifications. 2. Inventory scripts, tags, SDKs, server events, proxies, destinations, identities, cookies, storage, and data retention. 3. Map each event's trigger, schema, properties, timestamp, identity, consent requirement, deduplication key, and report use. 4. Observe network and server payloads for representative journeys without recording sensitive values. 5. Test initial load, navigation, history, refresh, retry, multiple tabs, authentication, logout, consent change, blockers, offline, and restoration. 6. Reconcile interface actions to collector receipt, warehouse rows, transformed models, and published metrics. 7. Quantify missing, duplicate, late, malformed, bot, internal, and misattributed events. 8. Review access, retention, deletion, downstream sharing, data contracts, change control, and monitoring. 9. Correct defects through versioned specifications and verify reports after the relevant processing delay. ## Done - An analytics audit report records inventory, event contracts, consent, identity, payload findings, lineage, defects, owners, and decisions at risk - Journey, duplicate, loss, consent, cross-tab, offline, collector, warehouse, deletion, and report-reconciliation checks verify the implementation
GitHub에서 보기