ab-test-plan
FreePlan an A/B test by script: sample size per variant, days to run, stopping rules. "how many visitors per variant"
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Lock one primary goal per brand and judge ideas or drafts against it. "does this fit our goal"
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The strategic filter. One goal is locked per brand; everything gets measured against it before time or budget is committed. Marketing fails quietly by doing good work toward nothing in particular — every piece defensible, the quarter's number missed anyway.
The locked goal lives in the brand workspace, so every session reads the same one:
~/.claude-marketing/brands/{brand-slug}/goal-lock.json
{
"goal": "40 qualified demo bookings per month from organic + email",
"metric": "demo bookings attributed to owned channels",
"target": 40,
"deadline": "2026-12-31",
"locked_at": "2026-08-12",
"history": [
{"checked": "2026-08-14", "item": "podcast idea", "verdict": "OFF"}
]
}
No file → this is the first run: ask for the goal, force it to one sentence with a metric and a deadline, confirm, write the file. If the user names three goals, make them rank — the filter is useless with more than one.
Read the locked goal, read what the user brought, and rule honestly:
# Goal check — {the locked goal}
## What you brought
[One line]
## Verdict: ON GOAL / PARTIAL / OFF GOAL
## Why (2-3 sentences)
[Does this move the goal's metric? How directly? What is the opportunity cost —
what on-goal work does this displace?]
## The fix (if PARTIAL or OFF)
[The specific change that would make it serve the goal — or "park it", with
what to do instead]
## The sharper version (always)
[The same idea, rewritten to pull harder toward the metric]
Append the verdict to history in the state file.
--set on an
existing lock archives the old goal into history with its end date, so the
quarter's record shows one deliberate change rather than a smear.No reviews yet. Tell others what you thought.
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Plan an A/B test by script: sample size per variant, days to run, stopping rules. "how many visitors per variant"
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Write ad copy variants to each platform's specs, policy-checked and in brand voice. "write ad copy for Meta"
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Add a custom MCP integration: scaffold the server, write .mcp.json, test it. "add a new MCP server"
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Run a one-time AEO audit of six AI answer engines, scored per surface. "check our AI search visibility"
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Plan AEO/GEO strategy to get cited by AI: content, entities, schema, 90-day plan. "how do we get cited by AI"
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Build the agency dashboard across all client brands: health, pacing, risk. "how are all our clients doing"
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