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Ad Budget Rebalancer

作者 haidong · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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版本数
在 OpenClaw 中安装
/install ad-budget-rebalancer
功能描述
Analyze ecommerce ad spend notes across Meta Ads, Google Ads, TikTok Ads, Amazon Sponsored, and Xiaohongshu promotional feeds, then recommend budget realloca...
使用说明 (SKILL.md)

Ad Budget Rebalancer

Overview

Use this skill to diagnose ad spend patterns and generate a budget-rebalancing brief that prioritizes channels, campaign types, and audience segments based on efficiency signals. It applies a built-in efficiency framework and channel-mix matrix to surface reallocation recommendations.

This MVP is heuristic. It does not connect to live ad platforms, campaign managers, or analytics dashboards. It relies on the user's provided spend notes, performance context, and channel mix.

Trigger

Use this skill when the user wants to:

  • review ad spend efficiency across multiple channels (Meta, Google, Amazon, TikTok, Xiaohongshu)
  • diagnose why a channel or campaign is underperforming relative to spend
  • rebalance budget across awareness, consideration, and conversion campaign types
  • prepare a monthly or quarterly media budget review brief
  • identify where to cut spend or where to scale based on ROAS or MER signals

Example prompts

  • "Our Meta Ads ROAS dropped this month — should we reallocate budget?"
  • "Help me review and rebalance our Q1 ad spend across Amazon, Google, and TikTok"
  • "Diagnose why our TikTok campaign is burning budget without conversions"
  • "Create a budget rebalancing brief for a $50k monthly ad spend"

Workflow

  1. Capture the total budget, channel mix, campaign types, and performance signals.
  2. Apply the efficiency framework to score each channel and campaign type.
  3. Identify underperforming channels, audience segments, and campaign types.
  4. Generate rebalancing recommendations with expected impact.
  5. Return a markdown rebalancing brief.

Inputs

The user can provide any mix of:

  • total ad budget and channel breakdown: e.g., Meta 40%, Google 30%, Amazon 20%, TikTok 10%
  • campaign type mix: awareness, consideration, conversion, retargeting
  • performance signals: ROAS, MER, CPM, CPC, CPA, CTR, conversion rate by channel
  • audience segment notes: demographic, interest, lookalike, retarget
  • business context: seasonal window, product launch, clearance, brand campaign
  • constraints: minimum spend requirements, creative constraints, platform policies

Outputs

Return a markdown brief with:

  • budget health summary (total spend, channel mix, overall efficiency)
  • channel efficiency scorecard (ROAS/MER, CPM, CPC, CPA per channel)
  • campaign type efficiency breakdown (awareness vs. conversion)
  • audience segment performance notes
  • rebalancing recommendations with specific reallocation percentages
  • expected impact estimates and risk notes
  • creative or landing-page considerations that may affect efficiency

Safety

  • No live ad platform, campaign manager, or analytics API access.
  • Efficiency scores are directional unless complete spend and revenue data is provided.
  • Do not claim guaranteed ROAS improvements or budget savings.
  • Budget decisions remain human-approved; automated bid or budget changes are out of scope.

Best-fit Scenarios

  • SMB and mid-market teams managing $10k-$500k monthly ad budgets
  • operators running multi-channel campaigns without a dedicated media buyer
  • teams needing a regular budget review cadence without heavy BI tooling

Not Ideal For

  • real-time bid management, automated campaign optimization, or live spend control
  • businesses with incomplete or inconsistent spend reporting
  • highly complex attribution scenarios requiring multi-touch modeling

Acceptance Criteria

  • Return markdown text.
  • Include channel efficiency scorecard and rebalancing recommendations.
  • Make efficiency assumptions explicit when data is partial.
  • Keep the brief practical for ecommerce operators and media buyers.
安全使用建议
This skill appears internally consistent and safe: it uses only the user's provided notes, applies built-in heuristics, and outputs a markdown brief. Before using recommendations to change live budgets, verify all input numbers (spend, conversions, revenue) and any platform-specific ROAS assumptions—the skill uses default ROAS/CPM values and fallback channel lists when inputs are partial. Treat outputs as advisory (the SKILL.md emphasizes human approval) and avoid automating budget changes directly from this skill. If you need auditability, supply full spend and revenue data rather than short notes so the recommendations are less dependent on defaults.
功能分析
Type: OpenClaw Skill Name: ad-budget-rebalancer Version: 1.0.0 The skill is a heuristic-based tool for generating ad budget reallocation recommendations based on user-provided notes. The logic in handler.py is limited to string processing and keyword matching, with no network access, file system interaction, or use of dangerous functions like eval() or os.system(). The SKILL.md instructions are well-defined and explicitly state that the tool does not connect to live APIs, aligning perfectly with the implementation.
能力标签
cryptocan-make-purchases
能力评估
Purpose & Capability
Name/description match the implementation: handler.py parses user-provided spend notes, scores channels/campaigns with built-in heuristics, and renders a markdown brief. No unrelated credentials, binaries, or external services are requested.
Instruction Scope
SKILL.md explicitly limits the skill to user-provided data and disclaims live API access. The runtime code follows that constraint (string parsing, heuristic defaults, no network calls or file reads beyond stdin/argv). Instructions do not ask the agent to read unrelated system state or exfiltrate data.
Install Mechanism
No install spec; this is instruction-only with included Python files. No downloads, package installs, or archive extraction are performed.
Credentials
No environment variables, credentials, or config paths are required or accessed. The handler uses only its input argument/stdin and built-in defaults.
Persistence & Privilege
The skill does not request persistent presence (always: false), does not modify system or other skills' configs, and does not perform autonomous privileged actions beyond rendering recommendations.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ad-budget-rebalancer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ad-budget-rebalancer 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of Ad Budget Rebalancer skill. - Analyze ecommerce ad spend notes across Meta, Google, Amazon, TikTok, and Xiaohongshu channels. - Diagnose underperforming channels, campaign types, and audience segments using a heuristic efficiency framework. - Generate markdown briefs with channel scorecards, efficiency breakdowns, and actionable budget rebalancing recommendations. - Operates without live platform or analytics access—uses user-provided notes and context only. - Designed for practical use by operators and media buyers managing multi-channel ad budgets.
元数据
Slug ad-budget-rebalancer
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Ad Budget Rebalancer 是什么?

Analyze ecommerce ad spend notes across Meta Ads, Google Ads, TikTok Ads, Amazon Sponsored, and Xiaohongshu promotional feeds, then recommend budget realloca... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 89 次。

如何安装 Ad Budget Rebalancer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ad-budget-rebalancer」即可一键安装,无需额外配置。

Ad Budget Rebalancer 是免费的吗?

是的,Ad Budget Rebalancer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Ad Budget Rebalancer 支持哪些平台?

Ad Budget Rebalancer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ad Budget Rebalancer?

由 haidong(@harrylabsj)开发并维护,当前版本 v1.0.0。

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