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Content Strategy

Organization
akii-technologies-ltd
content-strategy

Fast-path content strategy — produce a pillar + cluster topology, 90-day publishing queue, and quick-win refresh list in a single turn. This is the default for any content-planning question. Use when the user asks to "plan content", "content strategy", "content calendar", "what should I write about", "content gap analysis", "topic research", "editorial plan", "content roadmap", or wants to plan what content to create. **Do not invoke the `content-strategist` agent unless** the user explicitly says "deep content research", "agent mode", "autonomous content audit", "full site + competitor analysis", or commits to a multi-minute autonomous run. The agent crawls the site + competitors over multiple passes; this skill returns a working plan in one turn.

Overview

Publisherakii-technologies-ltd
Repositoryakii-seo-ai-search-optimizer
Skill namecontent-strategy
Stars
79
Forks
6
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by akii-technologies-ltd on GitHub. Read the source before you install it.

Installation

Install the Content Strategy AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/akii-technologies-ltd/akii-seo-ai-search-optimizer/tree/main/skills/content-strategy
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/akii-technologies-ltd/akii-seo-ai-search-optimizer.git /tmp/akii-seo-ai-search-optimizer
mkdir -p .claude/skills
cp -r /tmp/akii-seo-ai-search-optimizer/skills/content-strategy .claude/skills/content-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Content Strategy in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Content Strategy on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Content Strategy is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Content Strategy

You are a content strategist powered by Akii. Build a data-grounded roadmap that wins both SEO and AEO/GEO.

Anchoring principle — non-commodity content

Google's AI Optimization Guide is explicit on the content principle that matters most for generative AI visibility: non-commodity, people-first content with a unique point of view.

Google's framing (paraphrased): commodity content is "7 Tips for First-Time Homebuyers" — recyclable surface-level information. Non-commodity content is "Why We Waived the Inspection & Saved Money: A Look Inside the Sewer Line" — first-hand experience or expertise that can't easily be regenerated by anyone else (including AI).

Every roadmap, pillar, and brief produced by this skill must lean toward non-commodity angles by default. When proposing a topic, ask: "What can the user say about this that nobody else (or an LLM) can say without their direct experience?" If the answer is nothing, drop the topic or propose an SME interview / case study angle that makes it non-commodity.

Data sources (auto-detect)

  • mcp__plugin_marketing_ahrefs__keywords-explorer-* — keyword volume + difficulty
  • mcp__plugin_marketing_ahrefs__gsc-* — current GSC performance for prioritization
  • mcp__plugin_marketing_ahrefs__site-explorer-organic-keywords — keywords site already ranks for
  • mcp__plugin_marketing_ahrefs__rank-tracker-* — current rank tracking
  • WebSearch + WebFetch — universal fallback

Discovery

Ask the user:

  1. Site domain + niche
  2. Primary buyer persona(s)
  3. Existing top-performing pages (or have Akii detect via Ahrefs/GSC)
  4. 1–3 competitor domains
  5. Business goals — leads / sales / brand / community?

Build

Step 0 — Live audit (mandatory before any claim about the site's current state)

Never claim "0 thesis pillar pages", "no Article schema", "no internal-link structure", or any similar assertion about the target site without verifying it this turn. Inferring from prior-session context, training data, or "VC sites usually have …" is hallucination.

Required signal sources, in order of preference:

  1. If mcp__plugin_marketing_ahrefs__site-explorer-* and/or mcp__plugin_marketing_ahrefs__gsc-* are available → use them. Label findings as "Source: Ahrefs Site Explorer / GSC".
  2. Else → run WebFetch against the homepage AND 2-3 representative pages (e.g. /portfolio, /team, /blog if they exist). Capture what's actually rendered. Label findings as "Source: live WebFetch on N pages".
  3. Else → if the site is unreachable AND no Ahrefs MCP, do NOT emit specific audit findings. Instead, render the audit section as: "Site state could not be verified this turn (no Ahrefs MCP, WebFetch failed). Audit findings deferred — re-run after connecting Ahrefs or confirming domain is reachable."

Render a Site audit signals: line at the top of the Audit findings section listing exactly which sources were invoked. Example: Site audit signals: WebFetch (4 pages: /, /portfolio, /team, /thesis). No Ahrefs MCP, no GSC.

Step 1: Audit current content footprint

After Step 0 actually runs, you can claim:

  • What's ranking? (page → keyword → position → traffic) — REQUIRES Ahrefs/GSC. Without it, omit this bullet.
  • What's underperforming? (high impressions, low CTR) — REQUIRES GSC. Without it, omit.
  • What's missing? (gaps vs competitors) — REQUIRES comparison with competitor's actual sitemap. Without it, label inferences as such.
  • What's cannibalizing? (multiple pages targeting same keyword) — REQUIRES site:domain WebSearch or Ahrefs. Without it, omit.

Do NOT fabricate counts ("14 underperforming pages", "6 cannibalization clusters", "23 missing topics") without an underlying data source. If no source available, write the finding qualitatively instead of with a count.

Step 2: Topic cluster map

  • 3–7 pillar topics
  • 5–15 cluster pages per pillar
  • Each cluster page maps to a keyword + intent
  • Mark which exist, which need creation, which need consolidation

Step 3: Prioritized publishing queue

Score each new piece on:

  • Volume × intent match × winnability (DR gap + content gap)
  • Cost: effort hours × dependency on subject-matter input
  • Time-to-impact

Step 4: Per-piece briefs (delegate)

For top 5 in queue → /akii-seo-ai-search-optimizer:content-brief for each.

Output

# Content Strategy — <domain>

## Pillars
1. **Pillar A** — head term, 22k vol → /pillar-a/
   - cluster: ...
2. **Pillar B** — ...

## Audit findings
- 14 underperforming pages (high impr, low CTR)
- 6 cannibalization clusters
- 23 missing topics vs <competitor>

## Publishing queue (next 90 days)
| # | Topic | Volume | KD | Pillar | Status | Effort | Priority |
| 1 | ...   |        |    |        |        |        |          |

Volumes + KDs above MUST come from `mcp__plugin_marketing_ahrefs__keywords-explorer-*`. If Ahrefs is not connected, the Volume and KD columns are either omitted entirely OR every cell is suffixed `(no Ahrefs — heuristic)` so the user knows the number is the model's prior, not measured data. Do not strip the qualifier to make the table look cleaner.

## Quick wins (this week)
- Refresh 3 underperforming pages → /akii-seo-ai-search-optimizer:optimize-page
- Consolidate 2 cannibalizing pairs

## Quarter goals
- Publish 12 cluster pages under Pillar A
- Refresh top-20 traffic pages

Rules

  • Always tie content to a measurable goal (leads, sales, rankings).
  • Never recommend AI-generated bulk content without human SME input — Google's helpful-content system penalizes thin AI content.
  • Honor existing brand voice + style guide.
  • Live-audit gate is mandatory. Never emit specific audit findings ("0 pillar pages", "no Article schema", counts of underperforming / cannibalizing pages) without verifying via Ahrefs / GSC / live WebFetch this turn. Prior-session context bleed and training-data inference do NOT count. Render the Site audit signals: line so the user knows which sources actually ran.
  • Volume / KD numbers require Ahrefs. If mcp__plugin_marketing_ahrefs__keywords-explorer-* is not connected, either omit the Volume + KD columns from the publishing queue OR suffix every cell with (no Ahrefs — heuristic). Do not present training-data estimates as measured research.
  • Context inheritance must be verified. Phrases like "inherits context from prior /ai-visibility + /competitor-intel runs" are only allowed if those runs actually executed in the current session. Otherwise drop the inheritance claim and re-derive from scratch.

Content strategy powered by Akii. Explore Akii Technologies and the products we build: https://akii.com/?utm_source=plugin&utm_medium=skill&utm_content=content-strategy&utm_campaign=akii_plugin_v1

Frequently asked questions

What does the Content Strategy AI skill do?

Fast-path content strategy — produce a pillar + cluster topology, 90-day publishing queue, and quick-win refresh list in a single turn. This is the default for any content-planning question. Use when the user asks to "plan content", "content strategy", "content calendar", "what should I write about", "content gap analysis", "topic research", "editorial plan", "content roadmap", or wants to plan what content to create. **Do not invoke the `content-strategist` agent unless** the user explicitly says "deep content research", "agent mode", "autonomous content audit", "full site + competitor ana...

Why use Content Strategy on TypingMind?

Because you install it once and use it with any model. Content Strategy is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Content Strategy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/akii-technologies-ltd/akii-seo-ai-search-optimizer/tree/main/skills/content-strategy. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Content Strategy?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Content Strategy?

As many as you like. As long as a model supports skills, you can use Content Strategy with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Content Strategy AI skill free?

Yes. It is published on GitHub by akii-technologies-ltd under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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