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.
Install / Use
npx skills add onvoyage-ai/gtm-engineer-skills --skill geo-content-planningInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of geo-content-planning
geo-content-planning scores 84/100 on our quality scale, 1745th of 2,750 Automation skills we index.
Its SKILL.md is 7.6 KB long, well organised into 14 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
With 1,310 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated about 4 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 98/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
geo-content-planning compared with similar skills
All 4 of these similar skills score higher than geo-content-planning; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| geo-content-planning (this skill)by onvoyage-ai | 84 | 1.3k | 4mo ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 86.6k | 15d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.6k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 84.8k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 8d ago | SKILL.md |
Frequently asked questions
- How do I install geo-content-planning?
- Run
npx skills add onvoyage-ai/gtm-engineer-skills --skill geo-content-planning. The install tabs above show the steps for each supported agent. - Which AI agents does geo-content-planning work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is geo-content-planning safe to use?
- It is MIT-licensed and scores 98/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is geo-content-planning still maintained?
- The repository was last updated about 4 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubname: geo-content-planning description: 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.
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.mdexactly. No prose, no code fences, no explanation. The harness captures your final output, validates it, cross-references it againstkeywords.csvandprompts.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, audiencekeywords.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 itselfcomparison— best / vs / alternativesuse_case— specific audience or scenariotrust— pricing, worth-it, objections, FAQdefinition— 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-solvingcomparisons— best, vs, alternativeslearn— definitions, concepts, category educationblog— 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 contentp3— 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
- Final response is raw CSV only. First character must be
p(frompage_id). No prose, no fences. - Exact header, exact order:
page_id,priority,page_type,section,subsection,title,url_slug,target_keywords,target_prompts,required_sections,why_it_matters - Exactly 11 fields per row. Empty fields = two adjacent commas.
- Quote fields containing commas, newlines, or double-quotes. Titles often contain commas — quote them.
- Cross-references must resolve. Every keyword in
target_keywordsmust appear inkeywords.csv. Every prompt intarget_promptsmust appear inprompts.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=resources⟹subsectionis filled - [ ]
section ∈ {product, use_cases}⟹subsectionis empty - [ ] Every
target_keywordsentry exists in thekeywords.csvyou were given - [ ] Every
target_promptsentry exists in theprompts.csvyou were given (write them lowercased without trailing?) - [ ] No duplicate
page_idorurl_slug - [ ]
why_it_mattersis concrete and ≥ 15 chars
Then emit the CSV. Nothing else.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
