spawn-blogs

name	spawn-blogs
description	Given the product and the existing page inventory, identify missing blog topics and generate new blog posts that capture search/AI intent using the query-fanout pattern. Use this skill whenever the user asks to "spawn blogs", "generate blog posts", "expand the blog", "build out a content cluster", "write blog ideas", "cover more search intents", "query fanout for blogs", or wants new long-form content that supports existing pillars. Output is one new post per topic in the project's existing post format (markdown, MDX, component, or CMS migration note), with frontmatter shape mirrored from an existing post.
argument-hint	[optional: pillar name or topic seed]
license	MIT

Overgrow — Spawn Blogs (Query Fanout)

This skill plans and drafts net-new blog posts that close gaps in the site's semantic pillars. It uses the query-fanout pattern: one seed intent is expanded into a fan of related sub-intents that modern search and AI systems decompose queries into, then each sub-intent becomes a post.

Prerequisites

1. Read .overgrow/inventory.md. If missing, run init first.
2. Read .overgrow$audit.md if present — thin pillars and orphan topics are prime spawn targets.
3. Parse $ARGUMENTS: if a pillar name or topic seed is given, scope to it. If not, propose up to 3 candidate pillars to expand and ask the user directly to clarify what you cannot infer. which to run. Once chosen, proceed for that pillar.

Reference knowledge

Before planning topics or drafting, read from the plugin's knowledge/ directory:

• knowledge/query-fanout.md — the 15-facet query fan-out taxonomy (DEFN, ENTITY, COMPARE, etc.). Use it to build the candidate sub-intent set. This SKILL.md's "Query-fanout pattern" section is a summary; query-fanout.md is the authoritative list.
• knowledge/geo.md — SEO + GEO master reference. Pay particular attention to the sections on content structure, AI extraction / RAG chunking, and answer-engine citation patterns. Post structure below is distilled from this file.
• knowledge/pages.md — H-tag and AI-overview formatting rules. Apply directly when drafting headings and the TL;DR lead.

If any of those files are not reachable, fall back to the summaries in this SKILL.md and continue.

Query-fanout pattern

Given a seed intent (e.g. "observability for PostgreSQL"), produce a fan of sub-intents covering the natural ways users and AI systems decompose the topic. A complete fan covers:

• Definitional — "what is X", "X explained", "X vs Y" disambiguation
• Comparative — "X vs Y", "X vs Z", "alternatives to X", "best X for "
• How-to / procedural — "how to do X with Y", step-by-step guides
• Why / justification — "why X matters", "benefits of X", "when to use X"
• Problem / symptom — "fix X error", "X not working", "X slow"
• Role-based — "X for ", "X for ", "X for "
• Integration — "X with ", "connect X to Y", "X + Y workflow"
• Migration — "migrate from X to Y", "move off X"
• Cost / pricing — "how much does X cost", "X pricing explained", "is X worth it"
• Trends / forward-looking — "future of X", "X in ", "X trends"

You do not need every branch for every pillar — pick the 5-10 branches that are both relevant and missing from existing content (per the inventory).

How to choose topics

For the chosen pillar:

1. List existing pages in that pillar from the inventory. These are off-limits — don't duplicate.
2. Generate candidate sub-intents using the fanout branches above. Aim for 15-25 raw candidates.
3. Filter: keep only candidates that
   • Are not already covered by an existing page.
   • Have clear audience overlap with the product.
   • Can be answered with real substance (not filler).
   • Map to a search query a human or LLM would actually issue.
4. Rank by a rough intent-to-conversion score: bottom-of-funnel (comparison, pricing, migration, "alternatives to") > middle (how-to, integration, role-based) > top (definitional, trends). Keep a mix — top-of-funnel builds GEO pillar authority even when conversion is lower.
5. Pick the top N (default 5, or whatever the user requested).

Blog post structure (GEO-first)

Every post the skill drafts uses this structure — it's tuned for both classic SEO ranking and AI-overview / chatbot citation.

1. Title (H1, 50-65 chars): leads with the primary keyword phrased as the user would search.
2. Meta description (120-158 chars): direct answer + why the post is worth reading.
3. Slug: lowercase, hyphen-separated, under ~60 chars.
4. Definitional lead (TL;DR) — 2-4 sentences directly under the H1 answering the query. This is the block LLMs extract.
5. Why it matters / context — 1-2 short paragraphs giving stakes.
6. Body sections — H2 per major question, H3 per sub-point. Every H2 reads like a natural-language sub-query (continues the fanout inside the post).
7. Comparison or decision block — table, list, or decision tree wherever the sub-intent is comparative. AI systems love structured blocks.
8. Step-by-step section — for how-to intents, a numbered list with code/config/config-example if relevant.
9. FAQ (3-6 Qs) — the long-tail sub-queries you didn't fully cover in the body. These double as FAQPage schema fodder.
10. Callouts for evidence — named sources, data, dates. Avoid bare claims.
11. Internal links — at least 2 outbound to other pages on the site (pillar hub + 1-2 supporting). Use descriptive anchor text, never "click here". Do not invent routes — only link to routes that appear in .overgrow/inventory.md.
12. CTA — one soft CTA at the end tied to the product (try, book, download), matched to the post's intent stage.

Output

Before writing anything, read the Authoring conventions section of .overgrow/inventory.md and open one existing post in the target blog directory to mirror its frontmatter shape exactly (key names, order, required fields, tag format, author field, etc.). Do not invent frontmatter keys.

Pick the output format from the detected convention:

• Markdown / MDX blog (the common case — Astro content collections, Next.js MDX, Nuxt Content, Hugo, Jekyll, Gatsby, Docusaurus): write .md or .mdx at the blog content root, using the inventory's recorded extension. Frontmatter matches an existing post's shape 1:1 — if existing posts use description not excerpt, use description; if they use publishedAt not date, use publishedAt; if they add author, add author.
• Component-based blog (rare — e.g. each post is a .tsx / .astro route with prose components): mirror the pattern of an existing post component, including layout wrapper, MDX-component use, and metadata export.
• CMS-driven blog (Contentful, Sanity, Payload, WordPress, etc.): do not write a file. Append a migration note to .overgrow/content-plan.md under ## CMS migrations with the full post body plus field-by-field mapping to the CMS model.

If no existing posts exist yet, fall back to this default frontmatter (and flag in content-plan that the project should standardize):

---
title: <title>
description: <meta description>
slug: <slug>
date: <YYYY-MM-DD>
pillar: <pillar name>
intent: <definitional | comparative | how-to | why | problem | role | integration | migration | cost | trends>
keywords: [<primary>, <secondary1>, <secondary2>]
draft: true
---

<body — following the structure above>

Use the project's draft gating idiom: if existing posts use draft: true, use it; if they use published: false, use that; if the project has no draft mechanism, add a TODO: review before shipping comment at the top of the body.

Then update .overgrow/content-plan.md (create if missing) with an entry per spawned post:

## <Pillar>

- [ ] <slug> — <title> — intent: <branch> — status: drafted <YYYY-MM-DD>

Leaving posts gated (via the project's existing draft mechanism or a TODO comment) is intentional — the user should run audit and humanize before publishing.

Writing guidelines

• Write for a real reader first, then optimize for keyword/entity coverage.
• Keep paragraphs short (2-3 sentences).
• Every claim with a number needs a source or a caveat.
• Do not fabricate case studies, customer quotes, benchmarks, or partner names. If the product team hasn't given you real examples, write illustrative ones and mark them <!-- placeholder: replace with real example -->.
• Follow the project's voice if a brand voice doc exists (check AGENTS.md, BRAND.md, VOICE.md, style-guide.md). Otherwise default to clear, active, jargon-light.
• Do not run the humanize pipeline inline — that's a separate skill. But avoid the banned vocabulary listed in humanize/reference/word-lists.md from the start so there's less to clean.

What this skill does NOT do

• Does not generate landing or product pages (that's spawn-pages).
• Does not add internal links across existing pages (that's spawn-internal-links). It only adds outbound links from the new posts it drafts.
• Does not publish. Posts ship gated behind the project's existing draft mechanism (or a TODO comment if none exists) and land in the repo for review.
• Does not invent facts, customers, or stats.
• Does not invent frontmatter keys. If an existing post is available, its shape is the source of truth — copy it exactly.