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pixel-attribution-readiness-checker像素归因就绪检查器

Agent Skill

pixel-attribution-readiness-checker 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

8,862

周安装

362

GitHub Stars

1

下载量

2,838
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:pixel-attribution-readiness-checker(像素归因就绪检查器)
来源仓库:https://github.com/danyangliu-sandwichlab/pixel-attribution-readiness-checker
安装命令:
openclaw skills install pixel-attribution-readiness-checker
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 pixel-attribution-readiness-checker

简介

验证 Meta Pixel、Google Ads 标签、TikTok Pixel 和跨渠道优化的事件跟踪和归因准备情况。

SKILL.md

name
pixel-attribution-readiness-checker
description
Validate event tracking and attribution readiness for Meta Pixel, Google Ads tags, TikTok Pixel, and cross-channel optimization.

Ads Pixel Readiness

Purpose

Core mission:

  • pixel install checks, event integrity, attribution readiness

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

When To Trigger

Use this skill when the user asks for:

  • ad execution guidance tied to business outcomes
  • growth decisions involving revenue, roas, cpa, or budget efficiency
  • platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads
  • this specific capability: pixel install checks, event integrity, attribution readiness

High-signal keywords:

  • ads, advertising, campaign, growth, revenue, profit
  • roas, cpa, roi, budget, bidding, traffic, conversion, funnel
  • meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

Input Contract

Required:

  • entity_ids: account, campaign, adset, or ad identifiers
  • incident_or_audit_scope
  • time_window

Optional:

  • logs_or_events
  • policy_flags
  • alert_thresholds
  • owner_contacts

Output Contract

  1. Operational Status Summary
  2. Severity-ranked Findings
  3. Mitigation Actions
  4. Escalation Ticket Payload
  5. Monitoring Checklist

Workflow

  1. Confirm operational scope and impacted entities.
  2. Validate data freshness and event completeness.
  3. Detect anomalies, policy flags, or setup gaps.
  4. Rank fixes by spend risk and recovery speed.
  5. Emit owner-ready action and ticket payload.

Decision Rules

  • If data is stale, block final judgement and request refresh timestamp.
  • If high-severity risk is found, recommend containment action first.
  • If root cause is uncertain, provide top hypotheses with validation order.

Platform Notes

Primary scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads

Platform behavior guidance:

  • Keep recommendations channel-aware; do not collapse all channels into one generic plan.
  • For Meta and TikTok Ads, prioritize creative testing cadence.
  • For Google Ads and Amazon Ads, prioritize demand-capture and query/listing intent.
  • For DSP/programmatic, prioritize audience control and frequency governance.

Constraints And Guardrails

  • Never fabricate metrics or policy outcomes.
  • Separate observed facts from assumptions.
  • Use measurable language for each proposed action.
  • Include at least one rollback or stop-loss condition when spend risk exists.

Failure Handling And Escalation

  • If critical inputs are missing, ask for only the minimum required fields.
  • If platform constraints conflict, show trade-offs and a safe default.
  • If confidence is low, mark it explicitly and provide a validation checklist.
  • If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.

Code Examples

Incident Ticket Example

ticket_id: INC-ads-001 severity: high impact: spend_waste_risk owner: media-ops next_check_at: 2026-03-03T10:00:00Z

Health Rule Example

rule: delivery_drop condition: impressions_down_pct > 40 action: alert_and_pause_review

Examples

Example 1: Pixel breakage before launch

Input:

  • Purchase event missing
  • Campaign start in 24h

Output focus:

  • severity ranking
  • immediate mitigation
  • relaunch checklist

Example 2: Account health audit

Input:

  • Multiple platform accounts
  • Unknown policy or billing status

Output focus:

  • readiness scorecard
  • blocking risks
  • owner-level actions

Example 3: Live anomaly handling

Input:

  • Spend spikes with no conversion lift
  • Multiple campaigns impacted

Output focus:

  • anomaly triage path
  • containment actions
  • incident ticket payload

Quality Checklist

  • [ ] Required sections are complete and non-empty
  • [ ] Trigger keywords include at least 3 registry terms
  • [ ] Input and output contracts are operationally testable
  • [ ] Workflow and decision rules are capability-specific
  • [ ] Platform references are explicit and concrete
  • [ ] At least 3 practical examples are included

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

85.56%
按下载量换算2,428

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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