git:20260330.d093d29 to git:20260424.732e31c

83 added, 201 removed. Audit A to A.

---

name: geo-content-planning

- description: Reads existing brand DNA, keyword research, and GEO prompt targets, then produces a content architecture showing what pages to create, their types, URLs, sections, and priority order.

+ 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

- You are a GEO content planner. Your job is to read the brand and research files that already exist, then produce a concise content plan showing what pages should be created to cover the most important SEO keywords, GEO prompts, and Reddit-style user questions.

- This skill is planning only.

- Do:

- - read existing research

- - group related prompts and keywords into content pieces

- - identify coverage gaps

- - recommend what content to create first

- Do not:

- - redo keyword or prompt research unless a critical input is missing

- - write full articles

- - produce long strategy memos

- - overcomplicate the workflow

- ## Use This Skill When

- Use this skill when the user asks to:

- - turn GEO research into a content plan

- - organize content based on prompts or keywords

- - decide what pages to create

- - design content structure

- - fill content gaps from brand research

- ## Expected Inputs

- Look for these files in the user's project or workspace:

- - `brand_dna.md`

- - `keyword_research.md`

- - `geo_prompt_targets.md`

- - `reddit_query_mining.md` (optional but useful)

+ # GEO Content Planning — Produce plan.csv

- If one file is missing, continue with the rest. State what is missing and lower confidence where needed.

+ 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.

- ## Output

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

- Save one Markdown file in the user's project directory:

+ > **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.

- - `content_architecture.md`

+ > **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.

- This file should be concise and practical. It should answer:

- - what content should exist

- - which site section each page belongs to

- - which prompts/keywords each page covers

- - what sections each page needs

- - what should be built first

+ ---

## Workflow

- ### 1. Read the brand context

- Extract:

- - what the company sells

- - who it is for

- - what makes it different

- - which competitors matter most

- This determines which content angles are worth creating.

- ### 2. Read the research files

- From `keyword_research.md`, extract:

- - core SEO keywords

- - comparison keywords

- - use-case keywords

- - trust or decision-stage topics

+ ### 1. Read the inputs

- From `geo_prompt_targets.md`, extract:

- - highest-priority prompts

- - buy vs solve vs learn prompt types

- - the prompts where the brand can realistically be mentioned

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

- From `reddit_query_mining.md`, extract:

- - real user wording

- - pain points

- - objections

- - comparison language

+ 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.

- ### 3. Cluster into content pieces

+ 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.

- Do not create one page per prompt.

+ ### 2. Cluster into pages

- Create one content piece for each cluster of closely related prompts and keywords. A good page usually covers:

+ 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

- - several related GEO prompts

- - one clear intent

- Good cluster examples:

- - best / alternatives / comparison queries

- - how-to / workflow / problem-solving queries

- - use-case-specific queries

- - trust / worth-it / objection queries

- - category definition / glossary queries

- ### 4. Choose page types

- Use simple page types only:

- - **Money page** - high-intent category or solution page

- - **Comparison page** - best, vs, alternatives

- - **Use case page** - for a specific audience or scenario

- - **Trust page** - pricing, worth it, objections, FAQ

- - **Definition page** - what is X, how X works

- If a page does not clearly support a keyword or prompt cluster, do not include it.

- ### 4A. Assign section and subsection

- Every planned page must be assigned to the site's frontend structure.

- Use these top-level sections:

- - `Product`

- - `Use Cases`

- - `Resources`

- Assign them with these rules:

- - `Product` for core capability, feature, or solution pages

- - `Use Cases` for persona-, workflow-, or scenario-based pages

- - `Resources` for educational, comparative, or broad demand-capture content

- If a page is in `Resources`, assign one subsection:

- - `Guides`

- - `Comparisons`

- - `Learn`

- - `Blog`

+ - 1–3 primary keywords (from `keywords.csv`)

+ - 3–6 related GEO prompts (from `prompts.csv`)

+ - One clear intent (buy / solve / learn)

- Assign subsections with these rules:

+ 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

- - `Guides` for how-to, workflow, and problem-solving pages

- - `Comparisons` for best, vs, alternatives, and competitor pages

- - `Learn` for definitions, concepts, and category education

- - `Blog` only for editorial, trend, or time-based posts

+ ### 3. Choose page types (enum, column 3)

- Do not assign a subsection to `Product` or `Use Cases` unless the user explicitly asks for it.

+ - `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

- ### 5. Define required sections

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

- For each planned page, include only the sections needed to satisfy the search intent.

+ - `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

- Common section types:

- - direct answer

- - comparison table

- - who this is for

- - how it works

- - use cases

- - FAQs

- - proof / evidence

- - objections / limits

+ ### 5. Pick required sections (column 10)

- Do not force all sections onto every page.

+ 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. Identify gaps

+ ### 6. Write title, url_slug, why_it_matters

- Call out:

- - prompt clusters with no good destination page yet

- - important competitor comparisons not covered

- - missing proof points or data needed to support claims

- - missing trust content near conversion

+ - `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

- Use a simple priority system:

- - **P1** - high business value and clear fit with existing product strengths

- - **P2** - useful supporting content

- - **P3** - lower-priority authority content

- Prioritize pages that:

- - cover buy and solve prompts

- - support commercial or high-intent keywords

- - let the brand appear in comparisons

- - match a real differentiator from the brand research

- ## Deliverable Format

- Write `content_architecture.md` in this structure:

- ```markdown

- # Content Architecture — [Brand Name]

- > Generated [date]

- > Input files: [list the files used]

- ## Content Priorities

- - P1: [short summary]

- - P2: [short summary]

- - P3: [short summary]

+ - `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

- ## Planned Content

+ ### 8. Minimum plan size

- |---|---|---|---|---|---|---|---|---|---|

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

- ## Gaps To Fill

+ ---

- - [missing comparison or topic]

- - [missing trust page]

- - [missing proof/data needed]

+ ## Strict CSV Format

- ## Recommended Build Order

+ ### Absolute rules

- 1. [first page]

- 2. [second page]

- 3. [third page]

+ 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.

- ## Notes

+ ### Example (full valid output — header + 5 rows)

- - Cluster prompts into pages instead of creating one page per prompt.

- - Use Reddit wording where it improves the title, H2s, FAQs, or comparison framing.

```

- ## Rules

+ 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"

+ ```

- 1. Be concise. The output is a build plan, not a strategy essay.

- 2. One page should cover a cluster, not a single query.

- 3. Keep page titles and URLs practical, not clever.

- 4. Every page must map back to real prompts, keywords, or objections from the input files.

- 5. Favor pages that can realistically get the brand mentioned in AI answers.

- 6. If the brand lacks proof for a claim, mark it as an evidence gap instead of pretending the content is ready.

- 7. Every page must include a `Section`, and `Resources` pages must also include a `Subsection`.

+ ### Before emitting — checklist

- ## Final Message To User

+ - [ ] 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` ⟹ `subsection` 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

- After saving the file, tell the user:

- - where it was saved

- - the top 3 pages to build first

- - the biggest content gaps you found

- - whether they want you to turn one of the planned pages into a brief or full draft next

+ Then emit the CSV. Nothing else.