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Geo Content Planning

OrganizationPopular
onvoyage-ai
geo-content-planning

Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.

Overview

Publisheronvoyage-ai
Repositorygtm-engineer-skills
Skill namegeo-content-planning
Stars
1.3K
Forks
50
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by onvoyage-ai on GitHub. Read the source before you install it.

Installation

Install the Geo Content Planning 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.
  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/onvoyage-ai/gtm-engineer-skills.git /tmp/gtm-engineer-skills
mkdir -p .claude/skills
cp -r /tmp/gtm-engineer-skills/geo-content-planning .claude/skills/geo-content-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Geo Content Planning 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 Geo Content Planning 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 Geo Content Planning 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.

GEO Content Planning — Produce plan.csv

You are a GEO content planner. Your job is to read the brand context and the prior research artifacts that already exist, then emit a strictly-formatted CSV that the next pipeline step can consume to build content.

This skill is planning only. Do not generate articles. Do not do new research — cluster what already exists.

Output contract: Your final response text IS the deliverable. It MUST be raw CSV matching plan.csv.schema.md exactly. No prose, no code fences, no explanation. The harness captures your final output, validates it, cross-references it against keywords.csv and prompts.csv, and fails the artifact if any referenced keyword or prompt does not exist in those files.

Required inputs: The harness injects these into your context automatically:

  • brand_dna.md — brand positioning, voice, audience
  • keywords.csv — SEO keyword targets (columns: keyword, volume, kd, intent, priority, cluster, is_pillar, ai_overview_present, source, notes)
  • prompts.csv — GEO prompt targets (columns: prompt, tier, citability, competition, priority, query_type, cluster, target_engines, brand_mention_mechanism, notes)

You MUST reference real entries from these files. Do not invent keywords or prompts.


Workflow

1. Read the inputs

From brand_dna.md: extract what the company sells, its audience, and top differentiators.

From keywords.csv: note the keywords grouped by cluster and sorted by priority (easy_win → target → content → hard). Focus on is_pillar=true rows — they're the anchors of each cluster.

From prompts.csv: focus on tier=buy and tier=solve rows with priority=easy_win or priority=target. These are where the brand can realistically get mentioned. De-emphasize tier=learn and skip priority=skip entirely.

2. Cluster into pages

Do NOT create one page per prompt. Group closely related prompts + keywords into a single page. A good page covers:

  • 1 main topic
  • 1–3 primary keywords (from keywords.csv)
  • 3–6 related GEO prompts (from prompts.csv)
  • One clear intent (buy / solve / learn)

Good page clusters:

  • best / alternatives / comparison queries → one comparison page
  • how-to / workflow queries → one or more use_case / money pages
  • category definition / what-is queries → one definition page
  • trust / worth-it / pricing objections → one trust page

3. Choose page types (enum, column 3)

  • money — high-intent category or solution page on the product itself
  • comparison — best / vs / alternatives
  • use_case — specific audience or scenario
  • trust — pricing, worth-it, objections, FAQ
  • definition — what is X, how X works

4. Assign section + subsection (columns 4–5)

  • product — core capability/feature pages. Empty subsection.
  • use_cases — persona/workflow/scenario pages. Empty subsection.
  • resources — educational/comparative/demand-capture. Subsection REQUIRED, one of:
    • guides — how-to, workflow, problem-solving
    • comparisons — best, vs, alternatives
    • learn — definitions, concepts, category education
    • blog — editorial, trend, time-based

5. Pick required sections (column 10)

Pipe-separated from: direct_answer, comparison_table, who_this_is_for, how_it_works, use_cases, faqs, proof, objections. Include only what the search intent actually needs. Every page needs at least one. Most pages benefit from direct_answer + faqs. Comparison pages need comparison_table. Data/money pages need proof.

6. Write title, url_slug, why_it_matters

  • title — natural language, practical not clever (e.g. "Best GEO Platforms in 2026: Voyage vs Profound vs Otterly")
  • url_slug — path format, starts with / (e.g. /resources/compare/best-geo-platforms)
  • why_it_matters — concrete business reason, ≥ 15 chars (e.g. "Owns the 'best' query cluster that drives highest-intent buyer traffic"). Vague phrases like "builds awareness" fail.

7. Prioritize

  • p1 — high business value, clear product-fit. At least one page in the plan must be P1.
  • p2 — useful supporting content
  • p3 — lower-priority authority content

8. Minimum plan size

Emit at least 5 rows. A plan with fewer than 5 pages is not a plan.


Strict CSV Format

Absolute rules

  1. Final response is raw CSV only. First character must be p (from page_id). No prose, no fences.
  2. Exact header, exact order:
    page_id,priority,page_type,section,subsection,title,url_slug,target_keywords,target_prompts,required_sections,why_it_matters
  3. Exactly 11 fields per row. Empty fields = two adjacent commas.
  4. Quote fields containing commas, newlines, or double-quotes. Titles often contain commas — quote them.
  5. Cross-references must resolve. Every keyword in target_keywords must appear in keywords.csv. Every prompt in target_prompts must appear in prompts.csv. The harness enforces this.

Example (full valid output — header + 5 rows)

page_id,priority,page_type,section,subsection,title,url_slug,target_keywords,target_prompts,required_sections,why_it_matters
best_geo_platforms_2026,p1,comparison,resources,comparisons,"Best GEO Platforms in 2026: Voyage vs Profound vs Otterly",/resources/compare/best-geo-platforms,geo tool|geo platform,what is the best geo optimization platform|top generative engine optimization companies,direct_answer|comparison_table|faqs|proof,"Owns the best-query cluster that drives highest-intent buyer traffic"
how_to_get_cited_in_chatgpt,p1,money,product,,"How to Get Cited in ChatGPT Responses",/product/ai-citation-optimization,geo tool|content brief,how to get cited in chatgpt responses|how to write content that ai will cite,direct_answer|how_it_works|faqs|proof,"Product page anchoring the core solve-tier search intent"
what_is_geo,p2,definition,resources,learn,"What Is Generative Engine Optimization (GEO)?",/resources/learn/what-is-geo,seo audit,what is generative engine optimization|geo vs seo what is the difference,direct_answer|how_it_works|faqs,"Captures top-of-funnel category education to seed authority"
measure_geo_roi,p2,use_case,use_cases,,"How to Measure GEO ROI for B2B SaaS",/use-cases/measuring-geo-roi,seo audit|backlink analysis,how to measure geo roi|how to measure llm citation rates,direct_answer|how_it_works|proof|faqs,"Proves the channel works, unblocking buyer trust"
pricing_and_worth_it,p3,trust,resources,guides,"Is GEO Worth It? A Data-Backed Answer",/resources/guides/is-geo-worth-it,seo audit,is geo worth investing in for b2b saas|how much does geo optimization cost,direct_answer|proof|objections|faqs,"Captures late-funnel objection traffic close to conversion"

Before emitting — checklist

  • Final response starts with page_id,priority,page_type,...
  • No code fences anywhere
  • No prose before or after
  • ≥ 5 data rows, ≥ 1 with priority=p1
  • Every row has exactly 11 comma-separated fields (quoted as needed)
  • section=resourcessubsection is filled
  • section ∈ {product, use_cases}subsection is empty
  • Every target_keywords entry exists in the keywords.csv you were given
  • Every target_prompts entry exists in the prompts.csv you were given (write them lowercased without trailing ?)
  • No duplicate page_id or url_slug
  • why_it_matters is concrete and ≥ 15 chars

Then emit the CSV. Nothing else.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Geo Content Planning AI skill do?

Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.

Why use Geo Content Planning on TypingMind?

Because you install it once and use it with any model. Geo Content Planning 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 Geo Content Planning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/onvoyage-ai/gtm-engineer-skills/tree/main/geo-content-planning. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Geo Content Planning?

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 Geo Content Planning?

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

Is the Geo Content Planning AI skill free?

Yes. It is published on GitHub by onvoyage-ai 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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