Install
$ agentstack add skill-onvoyage-ai-gtm-engineer-skills-geo-content-planning ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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, ispillar, aioverviewpresent, source, notes) > - prompts.csv — GEO prompt targets (columns: prompt, tier, citability, competition, priority, querytype, cluster, targetengines, brandmention_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, urlslug, whyit_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.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: onvoyage-ai
- Source: onvoyage-ai/gtm-engineer-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.