/digital-marketing-pro:budget-tracker

/digital-marketing-pro:budget-tracker

Script location. If your host does not set ${CLAUDE_PLUGIN_ROOT}, the scripts are in this plugin's scripts/ folder, next to skills/. Run them with Python 3.10 or newer: python, or python3 where python is not found (macOS, many Linux systems).

Purpose

Track advertising budget in real-time across all connected ad platforms. Analyze spend pacing against targets, project end-of-period totals, flag overspend risks and underspend inefficiencies, calculate daily burn rates, and recommend budget reallocations to maximize ROI within the remaining budget window. Designed for media buyers and marketing managers who need a single view of where money is going and whether it is being spent effectively.

Input Required

The user must provide (or will be prompted for):

• Budget period: This month, this quarter, or a custom date range (e.g., "Feb 1 - Mar 31"). Determines the pacing denominator and projection horizon
• Ad platforms to include: All connected platforms or specific ones (e.g., "Google Ads and Meta only"). Defaults to all connected ad MCPs
• Budget targets per platform (optional): Specific spend targets per platform for the period. If omitted, targets are pulled from profile.json budget_range and any saved platform allocations
• Total budget (optional): Overall budget cap for the period. If omitted, pulled from profile.json budget_range
• Alert thresholds (optional): Custom thresholds for overpace (default: >110% of expected pacing) and underspend (default: <70% of expected pacing) flags
• Include efficiency metrics (optional): Whether to pull CPA, ROAS, and conversion data alongside spend. Defaults to yes

Process

1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
2. Extract budget targets: Pull budget_range from profile.json and any saved per-platform allocations from previous budget-optimizer or media-plan runs. If user provided explicit targets, use those as overrides. Calculate the target daily spend rate for each platform (budget / days in period).
3. Pull spend data from connected ad MCPs: Query each connected advertising platform (google-ads, meta-marketing, linkedin-marketing, tiktok-ads) for current-period spend — total spend to date, daily spend breakdown, campaign-level spend distribution, and cost metrics (CPC, CPM, CPA per campaign).
4. Calculate pacing per platform: Execute python "${CLAUDE_PLUGIN_ROOT}/scripts/ad-budget-pacer.py" --budget {total} --period-days {N} --days-elapsed {N} --spend-to-date {amount} with spend data and budget targets to compute days elapsed/remaining, budget consumed vs expected pacing percentage, pacing ratio (actual / expected), daily burn rate (7-day average), and burn rate trend (accelerating/steady/decelerating).
5. Project end-of-period spend: Extrapolate current daily burn rate to end of period for each platform — produce best-case (lowest recent daily spend), expected (7-day average), and worst-case (highest recent daily spend) projections.