Budget Pacer

Budget Pacer

Doctrine

"Every time I touch a winning campaign it crashes" is a scaling story, not a curse: big budget jumps reset learning, and panic edits kill compounding winners. Pacing means the boring version: scale in ~20% steps, no more than once a day, pause what has proven it loses, and let rules carry the discipline your fingers do not have. The loop decides the ceiling: scale only what returns its spend fast enough to fund the next round.

When to use

• An angle has spent 2-3x target cost-per-result and holds. Time to feed it.
• You keep manually raising and lowering budgets on vibes.
• Needs a Meta Ads MCP with write access; everything is proposed as a draft first.

Run it

Budget pacing proposal, draft only, change nothing yet:

1. Read the last 14 days by ad set: spend, results, cost per result.
2. Identify what has EARNED a raise (enough spend to judge, cost per result at or under my target of [$X]) and what has earned a pause (2-3x target spent, no results).
3. Propose:
   - a pause rule: pause any ad set whose cost per result exceeds [$X * 1.5] over a 3-day window,
   - a scaling plan for the winner: +20% budget steps, at most one step per day, with the next review date,
   - a spend guardrail: a rule that alerts me if daily account spend exceeds [$CAP].
4. Show me the rules exactly as they would be created. I will say "create" for the ones I want.

Guardrails

• Drafts until the human says "create". Spend changes are the most sensitive write there is.
• +20% steps, not doublings. A budget doubling is a learning reset wearing a growth costume.
• Pause rules use my numbers ([$X] comes from my loop math), never an invented benchmark.
• If the loop math says the winner still is not profitable at scale, say that instead of scaling it.

Good output looks like

Two or three rules you can read and approve by name, a winner scaling schedule with dates, and no dollar moved without a yes.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: kelpi-ai
• Source: kelpi-ai/meta-ads-skills
• License: MIT
• Homepage: https://kelpi.ai/skills

Install and usage instructions live in the source repository linked above.