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Budget rebalance

Skill logly/mureo/skills/budget-rebalance

Rebalance campaign budgets across all configured platforms based on strategy and performance signals. Use when the user asks to optimize budgets, redistribute spend, scale efficient campaigns, or cap overspending ones. Reads STRATEGY.md goals, analyzes campaign efficiency, and proposes budget changes with rationale. Also use when the user asks in Japanese (予算を最適化して / 予算の再配分 / 好調なキャンペーンに予算を寄せて / 予算リバランス).From its SKILL.md

Install
npx -y skills add logly/mureo --skill budget-rebalance

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SKILL.md

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Budget Rebalance

PREREQUISITE: Read ../_mureo-shared/SKILL.md for auth, security rules, output format, and Tool Selection (Read/Write on Code, mureo_strategy_* / mureo_state_* MCP on Desktop / Cowork).

Analyze budget allocation and suggest rebalancing across all campaigns.

Prerequisites

  • STRATEGY.md and STATE.json must exist (run the onboard skill first)

Steps

Before you start: Run the Diagnostic preamble from ../_mureo-shared/SKILL.md — load learning insights (mureo_learning_insights_get) and consult advisors (mureo_consult_advisor) before drawing conclusions.

  1. Establish today: call mureo_state_get first, on every host (including Claude Code, where you would otherwise Read the file) and take server_now from its response — ISO 8601 with UTC offset, e.g. 2026-07-28T10:12:33+09:00. Its date is the only source of the current date for this run: the observation_due you write in step 16, and every "is a previous change still inside its observation window?" check in step 14, are measured from it. Do not shell out (this skill must run in Bash-less headless hosts) and do not read the date off STATE.json — last_synced_at, reports.*.period and action_log timestamps are history, never evidence of what day it is now. Never write server_now into STATE.json: it is a response field, and a persisted copy becomes tomorrow's stale "today".

  2. Load context: Read STRATEGY.md (Operation Mode, Market Context, Goal sections, Data Sources) and STATE.json (the same mureo_state_get response from step 0 on MCP hosts).

  3. Discover platforms: Identify all configured ad platforms from STATE.json platforms. Also include any hosted official-MCP connector present in the session (e.g. TikTok, key tiktok_ads) — drive it via its own tools and skip mureo-only value-adds; see ../_mureo-shared/SKILL.md → Hosted-connector platforms.

  4. Analyze budget efficiency: For each ad platform:

    • Google Ads: prefer mureo native — call google_ads_budget_efficiency (campaign × budget × spend × conv ratio) and google_ads_performance_report for the period. In BYOD mode, budget.efficiency may return [] because daily budgets aren't carried in the Apps Script bundle — fall back to performance.report cost / conv numbers and rank by CPA. If mureo's Google Ads tools are unavailable (e.g. MUREO_DISABLE_GOOGLE_ADS=1 after mureo providers add google-ads-official), fall back to the official google-ads-official MCP for the performance report only, then skip google_ads_budget_efficiency (mureo-only analysis) and rank campaigns by CPA from the raw cost / conv numbers yourself; note to the user that mureo's automated budget-efficiency scoring requires the native MCP (mureo setup claude-code).
    • Meta Ads: prefer mureo native — call meta_ads_insights_report and meta_ads_analysis_cost. In BYOD mode, daily budgets aren't surfaced — rank by spend × result_indicator-aware conversions instead. If mureo's Meta Ads tools are unavailable, fall back to the official meta-ads-official hosted MCP for raw insights only, then skip meta_ads_analysis_cost (mureo-only cost-trend analysis) and the result_indicator-aware ranking; rank by raw spend / conversions from the official MCP's response instead and warn the user that CV-definition mismatches across campaigns are NOT detected in this fallback path.
    • mureo BYOD data is centralized in the workspace byod/ directory (or ~/.mureo/byod/ for legacy CLI users) and is only accessible through mureo MCP tools — do not look for raw CSVs in the project directory.
  5. Rank campaigns by efficiency (CPA, ROAS, or CVR depending on campaign goals) across all platforms to enable cross-platform comparison.

  6. Goal-driven prioritization: Reference Goal sections from STRATEGY.md to guide allocation:

    • Identify which platform is closer to achieving each Goal
    • Consider shifting budget toward the platform with better Goal progress
  7. Cross-platform rebalancing: Evaluate whether budget should move between any configured platforms:

    • Compare CPA/ROAS across all platforms
    • If one platform significantly outperforms, suggest cross-platform budget shift
    • Present cross-platform comparison before within-platform reallocation
  8. Organic intelligence (if Search Console is available): If organic rankings are strong for certain keywords, consider reducing paid spend on those terms and reallocating to keywords without organic coverage.

  9. Conversion quality check (if GA4 is available): Incorporate conversion quality data (bounce rate, pages/session, time on site by traffic source) into budget decisions. A platform with lower CPA but higher bounce rate may not be the better allocation.

  10. Mode guard: If Operation Mode is ONBOARDING_LEARNING or CREATIVE_TESTING, warn that budget changes are discouraged in this mode and ask whether to proceed.

  11. Generate reallocation plan based on Operation Mode:

    • EFFICIENCY_STABILIZE: Shift budget from high-CPA to low-CPA campaigns
    • SCALE_EXPANSION: Increase budget for campaigns not limited by budget but performing well
    • TURNAROUND_RESCUE: Cut budget from campaigns with 0 conversions
    • COMPETITOR_DEFENSE: Increase budget on core brand/keyword campaigns under competitive pressure
    • LTV_QUALITY_FOCUS: Prioritize campaigns with highest conversion quality
    • ONBOARDING_LEARNING: Minimal changes only if user confirmed in step 9
    • CREATIVE_TESTING: Minimal changes only if user confirmed in step 9
  12. Present plan as a table:

    PlatformCampaignCurrent BudgetProposed BudgetChangeReason

    Every Reason must be marginal, not average. A rank by average CPA identifies candidates; it does not justify the move. State what the next (or removed) unit of spend is expected to do — a top-average campaign that is not budget-limited is usually saturated, and a bad-average campaign may simply be spend-suppressed. Where the marginal effect is genuinely unknown, say so and offer /experiment instead of asserting it. See ../_mureo-pro-diagnosis/SKILL.md → Allocation & Learning-State Discipline.

  13. Risk assessment: Flag any single budget change >20% — on Google Ads Smart Bidding / Meta CBO a large step can reset the learning phase, so prefer staged changes (e.g. two ≤20% steps). A platform that does not select delivery by a bid has no learning phase to reset: do not warn about one for it.

  14. Ask for approval before any changes.

  15. Check pending observations: Before executing, check action_log for campaigns being modified. If a previous budget change is still within its observation window, warn about stacking changes.

  16. Execute: Use each platform's budget update tools to apply approved changes.

  17. Record outcome context: For each campaign modified, log to action_log with metrics_at_action (current cost, impressions, clicks, conversions, CPA, budget utilization) and observation_due (7 days from server_now's date for budget changes).

  18. Update STATE.json with new budget values, notes, and log the rebalancing action to action_log.

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