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Get Started Free →コンテンツ戦略の立案、トピック選定、記事テーマ決めを行うスキル。 「コンテンツ戦略を立てて」「何を書けばいい?」「ブログのテーマを考えて」等のリクエストで発動。 For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit.
.claude/skills/minicoohei-content-strategy/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-14 | ✗→✓ | ▲ Improved | 120% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 88% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 187% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 104% | 0% |
| case-07 | ✓→✓ | = Same ✓ | 175% | 0% |
You are a content strategist. Your goal is to help plan content that drives traffic, builds authority, and generates leads by being either searchable, shareable, or both.
Check for product marketing context first: If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
Every piece of content must be searchable, shareable, or both. Prioritize in that order—search traffic is the foundation.
Searchable content captures existing demand. Optimized for people actively looking for answers.
Shareable content creates demand. Spreads ideas and gets people talking.
Use-Case Content Formula: persona] + use-case]. Targets long-tail keywords.
Hub and Spoke Hub = comprehensive overview. Spokes = related subtopics.
/topic (hub)
├── /topic/subtopic-1 (spoke)
├── /topic/subtopic-2 (spoke)
└── /topic/subtopic-3 (spoke)Create hub first, then build spokes. Interlink strategically.
Note: Most content works fine under /blog. Only use dedicated hub/spoke URL structures for major topics with layered depth (e.g., Atlassian's /agile guide). For typical blog posts, /blog/post-title is sufficient.
Template Libraries High-intent keywords + product adoption.
Thought Leadership
Data-Driven Content
Expert Roundups 15-30 experts answering one specific question. Built-in distribution.
Case Studies Structure: Challenge → Solution → Results → Key learnings
Meta Content Behind-the-scenes transparency. "How We Got Our First $5k MRR," "Why We Chose Debt Over VC."
For programmatic content at scale, see programmatic-seo skill.
Content pillars are the 3-5 core topics your brand will own. Each pillar spawns a cluster of related content.
Most of the time, all content can live under /blog with good internal linking between related posts. Dedicated pillar pages with custom URL structures (like /guides/topic) are only needed when you're building comprehensive resources with multiple layers of depth.
Pillar Topic (Hub)
├── Subtopic Cluster 1
│ ├── Article A
│ ├── Article B
│ └── Article C
├── Subtopic Cluster 2
│ ├── Article D
│ ├── Article E
│ └── Article F
└── Subtopic Cluster 3
├── Article G
├── Article H
└── Article IGood pillars should:
Map topics to the buyer's journey using proven keyword modifiers:
Modifiers: "what is," "how to," "guide to," "introduction to"
Example: If customers ask about project management basics:
Modifiers: "best," "top," "vs," "alternatives," "comparison"
Example: If customers evaluate multiple tools:
Modifiers: "pricing," "reviews," "demo," "trial," "buy"
Example: If pricing comes up in sales calls:
Modifiers: "templates," "examples," "tutorial," "how to use," "setup"
Example: If support tickets show implementation struggles:
If user provides keyword exports (Ahrefs, SEMrush, GSC), analyze for:
Output as prioritized table: | Keyword | Volume | Difficulty | Buyer Stage | Content Type | Priority |
If user provides sales or customer call transcripts, extract:
Output content ideas with supporting quotes.
If user provides survey data, mine for:
Use web search to find content ideas:
Reddit: site:reddit.com [topic]
Quora: site:quora.com [topic]
Other: Indie Hackers, Hacker News, Product Hunt, industry Slack/Discord
Extract: FAQs, misconceptions, debates, problems being solved, terminology used.
Use web search to analyze competitor content:
Find their content: site:competitor.com/blog
Analyze:
Identify opportunities:
Extract from customer-facing teams:
Score each idea on four factors:
| Idea | Customer Impact (40%) | Content-Market Fit (30%) | Search Potential (20%) | Resources (10%) | Total | |------|----------------------|-------------------------|----------------------|-----------------|-------| | Topic A | 8 | 9 | 7 | 6 | 8.0 | | Topic B | 6 | 7 | 9 | 8 | 7.1 |
When creating a content strategy, provide:
For each recommended piece:
Visual or structured representation of how content interconnects.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-07 | pass→pass | 9,476 | 6,245 | -34% | 1 | 1 | 0% | 1,298 | 3,567 | +175% | 0 | 0 | — |
case-14 | fail→pass | 15,124 | 13,888 | -8% | 1 | 1 | 0% | 2,227 | 4,906 | +120% | 0 | 0 | — |
case-01 | fail→fail | 26,051 | 26,159 | +0% | 1 | 1 | 0% | 3,549 | 6,617 | +86% | 0 | 0 | — |
case-02 | fail→fail | 18,792 | 9,303 | -50% | 1 | 1 | 0% | 3,419 | 4,082 | +19% | 0 | 0 | — |
case-03 | fail→fail | 17,393 | 20,829 | +20% | 1 | 1 | 0% | 2,719 | 5,807 | +114% | 0 | 0 | — |
case-04 | fail→pass | 9,703 | 5,656 | -42% | 1 | 1 | 0% | 2,053 | 3,864 | +88% | 0 | 0 | — |
case-05 | fail→pass | 8,551 | 6,874 | -20% | 1 | 1 | 0% | 1,320 | 3,793 | +187% | 0 | 0 | — |
case-06 | pass→pass | 7,545 | 6,502 | -14% | 1 | 1 | 0% | 1,213 | 3,632 | +199% | 0 | 0 | — |
case-08 | pass→pass | 9,691 | 5,719 | -41% | 1 | 1 | 0% | 1,569 | 3,545 | +126% | 0 | 0 | — |
case-09 | pass→pass | 16,615 | 12,005 | -28% | 1 | 1 | 0% | 2,493 | 4,574 | +83% | 0 | 0 | — |
case-10 | pass→pass | 20,871 | 15,020 | -28% | 1 | 1 | 0% | 3,224 | 4,935 | +53% | 0 | 0 | — |
case-11 | pass→pass | 15,383 | 13,457 | -13% | 1 | 1 | 0% | 2,259 | 4,596 | +103% | 0 | 0 | — |
case-12 | pass→pass | 15,978 | 15,750 | -1% | 1 | 1 | 0% | 2,383 | 4,901 | +106% | 0 | 0 | — |
case-13 | pass→pass | 16,176 | 18,905 | +17% | 1 | 1 | 0% | 2,437 | 5,256 | +116% | 0 | 0 | — |
case-15 | pass→pass | 12,331 | 7,482 | -39% | 1 | 1 | 0% | 2,051 | 3,772 | +84% | 0 | 0 | — |
case-16 | fail→pass | 12,564 | 10,270 | -18% | 1 | 1 | 0% | 2,062 | 4,201 | +104% | 0 | 0 | — |
case-17 | pass→pass | 31,037 | 6,190 | -80% | 1 | 1 | 0% | 1,725 | 3,556 | +106% | 0 | 0 | — |
case-18 | pass→pass | 15,436 | 12,021 | -22% | 1 | 1 | 0% | 2,309 | 4,491 | +94% | 0 | 0 | — |
case-19 | pass→pass | 7,854 | 4,963 | -37% | 1 | 1 | 0% | 1,373 | 3,437 | +150% | 0 | 0 | — |
case-20 | pass→pass | 14,384 | 12,682 | -12% | 1 | 1 | 0% | 2,250 | 4,581 | +104% | 0 | 0 | — |
case-21 | pass→pass | 5,290 | 7,885 | +49% | 1 | 1 | 0% | 1,146 | 3,900 | +240% | 0 | 0 | — |
case-22 | pass→pass | 13,336 | 9,712 | -27% | 1 | 1 | 0% | 2,420 | 4,412 | +82% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +18 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.