40-next-content-plan

Generates a data-driven next-period content plan using a 70/20/10 mix from prior audit results.

569|224|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/minhnv0807/ai-business-skills --skill 40-next-content-plan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: 40-next-content-plan
Source: https://github.com/minhnv0807/ai-business-skills/tree/main/skills/vi/40-next-content-plan
Command: npx skills add https://github.com/minhnv0807/ai-business-skills --skill 40-next-content-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Planning next month's content without data leads to guesswork and repeating past mistakes. This Skill turns your previous content audit and marketing report into a structured plan that scales proven winners, optimizes variants, and limits risky new experiments.

Core Features & Use Cases

  • Data-grounded planning: Every change in the plan must trace back to a metric from the prior period's audit (skill 39) or marketing report (skill 07).
  • 70/20/10 content mix: Allocates 70% of output to proven formats, 20% to optimized variants of winners, and 10% to a maximum of 2 testable new hypotheses.
  • Winner replication and hypothesis testing: Produces tables for cloning winners into 2-3 variants and defining falsifiable hypotheses with KPIs and conclusion criteria.
  • Use Case: After running a monthly content audit, ask for next month's plan and receive a Markdown file with the period review, content mix, winner replication table, hypothesis tests, a 4-week overview calendar, and team assignments.

Quick Start

Use the next content plan skill to build next month's content plan from my latest content audit and marketing report.

Frequently Asked Questions about 40-next-content-plan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a content plan based on past performance data?

Run a content audit first to identify what worked, then feed those results into this planning workflow. It produces a plan where every change traces back to a specific metric, using a 70/20/10 split between proven formats, optimized variants, and new experiments.

What is the 70/20/10 content mix rule?

The 70/20/10 rule allocates 70% of content output to proven winning formats, 20% to optimized variants of those winners such as new hooks or channels, and 10% to entirely new hypotheses. This balances reliable performance with controlled experimentation.

How many new content experiments should I test per month?

Limit new hypotheses to a maximum of 2 per planning cycle. Testing more than that spreads data too thin to draw valid conclusions about which change actually drove results.

What inputs are required before building a next content plan?

You need a completed content audit from the prior period, and ideally the prior marketing report, plus new-period KPI targets and any upcoming campaigns or capacity changes. Without audit data, the plan cannot be built and the audit step must run first.

Should I drop content formats that underperformed last month?

Not automatically. Distinguish between losers caused by a wrong angle, which should be dropped, and losers caused by poor execution, which deserve one retry after fixing the execution issue.