Ad Budget Rebalancer

Analyze ecommerce ad spend notes across Meta Ads, Google Ads, TikTok Ads, Amazon Sponsored, and Xiaohongshu promotional feeds, then recommend budget realloca...

Security Scan

The skill's code, instructions, and requirements are coherent with its stated purpose: it is a heuristic, offline ad-budget reviewer that does not access external services or request secrets.

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.

Assessment

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.

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.