Blog Generation

Blog Generation

One job, done well: produce a single excellent, on-brand blog post per run, optimized to rank on Google and get cited by AI search, and never repeat what you have already written. Built to run as a recurring task (for example, one post a day) or on demand for any business in any vertical: a dentist, a jeweler, a B2B SaaS, a DTC brand.

The whole game is captured in two ideas. First, AI search visibility is SEO done well: unique, genuinely useful, people-first content with a clear point of view, structured so a machine can extract a clean answer. There is no secret AEO hack. Second, the engine has memory: a single blog-strategy.md file, saved in persistent storage, holds the brand's context plus a running log of every post. That log is what stops it from ever repeating itself.

The memory contract (the most important rule in this skill). The log lives in a real file that survives between runs. On the FIRST run it does not exist, so you create it. On EVERY run after that it already exists, so you read it into context before doing anything, then append the new post to it before you finish. Same brand, same file path, every time. If you ever write a post without first reading the log, or finish a run without appending to it, the engine is broken: it will loop and repeat topics. Read-the-log-first and append-the-log-last are non-skippable.

Requirements

• Hyper MCP connected. https://app.hyperfx.ai/mcp
• A brand strategy doc (blog-strategy.md) in persistent files. If it does not exist yet, the engine builds one on the first run (Step 0). This is what lets it write in the brand's real voice and avoid repeats.
• Recommended toolkits, enabled at https://app.hyperfx.ai/apps: Firecrawl (read the brand's site), HyperSEO (validate topics, see what ranks and what AI cites), Google Search Console (mine real signals and measure). Without them you can still draft, but flag that topic and ranking calls are unvalidated.

How to run the tools in this skill

Every tool in this skill is named by its canonical tool name. Run it with the call your surface gives you:

If a tool is not found: in Hyper chat, find its toolkit id with discover_toolkits and pass it to enable_toolkit. On an MCP client or the CLI, tell the user which integration to connect in Hyper.

Tool surface

Out of scope: defer to other skills

The run (do this every time the task fires)

To run it daily, read the task-management skill, then create a Task: tasks_create(name="Daily blog post: <brand>", action={"type": "agent", "instructions": "Run the blog-generation skill for <brand>. The strategy doc is /files/<brand-slug>/blog-strategy.md."}, trigger={"type": "schedule", "schedule": {"kind": "cron", "expression": "0 9 * * *", "timezone": "<the user's time zone>"}}, thread_policy="new_each_run").

Step 0 (first run only): build the strategy doc. If blog-strategy.md does not exist, create it before writing anything. First read /files/<brand-slug>/brand-context.md with files_read; if it exists, copy its positioning, audience, voice and proof into the Brand brief. Only if it does not exist, read the brand's site (firecrawl_urls_scrape on homepage, about, best existing posts, product/pricing) and fill the Brand brief using the method in references/brand-voice-and-quality.md. Seed the Topic backlog with 8 to 15 candidate topics (validate with HyperSEO where available). Then continue to Step 1. If anything critical is unknown (real proof assets, the brand's actual positioning): in a chat, ask the user. In a scheduled run, do not ask: skip the claim, write the open question into the strategy doc, and send it with notify_user at the end of the run.

Step 1: load your memory (read the log). Open the brand's blog-strategy.md from its saved file path and read ALL of it into context: the Brand brief (the contract every draft honors) and the entire Published log (everything already written). This happens on every run after the first, with no exceptions. You cannot pick a fresh topic without it.

Step 2: plan today's post. Pick ONE topic that is not in the Published log and is genuinely distinct from it (see "Picking a fresh topic" below). Write a one-line plan capturing exactly these four things, and record it in the strategy doc:

• Title / topic: the working title and the primary query it targets.
• Where it is coming from: the source or trigger (a backlog item, a GSC gap, a customer question, a keyword gap, a news hook, a piece of the brand's own expertise or data).
• What it is going to do: the archetype (listicle, comparison, how-to, what-is, alternatives, pillar, pain/diagnostic, original research, case study, glossary) from references/blog-archetypes.md.
• The research it is going to do: the specific checks for this post (SERP read, AI Mode check (hyperseo_ai_overviews_get), sources to pull, the brand proof to feature).

Step 3: research. Run the plan. Validate the target with hyperseo_search_volume_get, hyperseo_keyword_difficulty_get, hyperseo_intents_search and hyperseo_ai_search_volume_get (each takes keywords=[...]). Study what wins (hyperseo_serp_results_get(keyword=...)) and the sources that Google AI Mode cites (hyperseo_ai_overviews_get(keyword=...)). Read the top pages and find the angle they all miss. Pull the real facts, stats, and named sources you will cite. Never fabricate.

Step 4: write the post. Build to the archetype spec in references/blog-archetypes.md, in the brand's voice from the Brand brief. That one file holds what the post needs: the type's structure, schema and AI-citation lever, the AI tells to strip, and the gate of Step 5.

Step 5: run the quality gate. Pass every item in the pre-publish gate at the end of references/blog-archetypes.md before the post is done: on-brand voice, no AI tells, no fabrication, answer-first structure, on-page and schema, baseline captured. If anything fails, fix it.

Step 6: update your memory (append to the log). Append the finished post as a new row in the Published log in blog-strategy.md (date, title, slug, archetype, target query, source, link), and save the file back to the same path. Remove the topic from the backlog and add any new ideas the research surfaced. This append is exactly what the next run reads to avoid repeating you. Never finish a run without it.

Step 7: deliver. Save the post to /files/<brand-slug>/posts/<slug>.md with files_create, and show it with sandbox_files_display(path="/files/<brand-slug>/posts/<slug>.md"). To publish, call connections_info(toolkit_id=<the brand's CMS toolkit>) for the site, then: WordPress.com wordpress_posts_create(site=..., title=..., content=..., status="publish"); self-hosted WordPress wordpress_org_posts_create(title=..., content=..., status="publish"); Ghost ghost_posts_create(title=..., html=..., status="published"); Wix wix_posts_create_and_publish(title=..., html=...); Webflow webflow_collection_items_create(collection_id=..., field_data={...}), then webflow_publish_site(site_id=...). Put the live URL in the log's Link column. Set the expectation that ranking moves in days to weeks and AI citations in weeks.

Picking a fresh topic (so it never loops)

Each run must produce something new. To choose:

1. Exclude everything in the Published log and anything that merely rewords it (same intent under a different title is a repeat).
2. Prefer the highest-priority unblocked backlog item that fits the brand and has real demand.
3. Vary the shape. If the last few posts were listicles, write a how-to, a pain/diagnostic, or an original-data piece. A healthy blog mixes archetypes.
4. Pull from live signal where available: GSC queries the brand ranks for on page two (google_search_console_performance_get), keyword gaps (defer to seo-research), recurring customer questions, or a timely news hook in the brand's space.
5. Lean on the brand's own substance. The most citable, least repeatable posts use the brand's proprietary data, real customer outcomes, or first-hand expertise. Reach for these often.

The strategy doc (blog-strategy.md) — the engine's memory

One Markdown file per brand, saved at a stable path in persistent storage (for example /files/<brand-slug>/blog-strategy.md) and reused at that SAME path on every run. Create it in Step 0, read it in Step 1, append to it in Step 6. The Published log section is the part that prevents repeats; it only ever grows. Template:

markdownCopy code
# Blog Strategy: [Business name]

## Brand brief
- Business: [what they do, one sentence]
- Sells: [products / services]
- Audience / ICP: [the specific customer]
- Category + one-liner: "[Brand] is a [category] for [audience] that [core value]."
- Voice: [tone, reading level, point of view]
- Words we use / words we avoid: [...]
- Proof assets: [real numbers, customers, credentials, data, stories]
- Primary site: [url]
- Target topics / seed keywords: [themes]
- Publishing: [CMS toolkit id, site, cadence]

## Topic backlog (planned, prioritized)
| Priority | Working title | Archetype | Target query | Source / angle | Status |
| --- | --- | --- | --- | --- | --- |
| 1 | ... | ... | ... | ... | planned |

## Published log (do NOT repeat anything here)
| Date | Title | Slug | Archetype | Target query | Source | Link |
| --- | --- | --- | --- | --- | --- | --- |

Non-negotiables (true on every run)

• Unique and people-first beats every hack. If a model could already write the post from common knowledge, or ten pages already say it, do not publish it. Lead with the brand's real angle.
• Answer first, then explain. Open the post and every section with the direct answer. AI extracts it; Google rewards it.
• On-brand and human, or it backfires. Off-brand, AI-tell-ridden, salesy content erodes trust and AI engines deprioritize it. The brand's real voice is the asset.
• Specific and verifiable, never vague or invented. Numbers, names, dates, real sources. Never fabricate a stat, quote, customer, or credential.
• One new post per run, always logged. The log is what makes the engine an engine instead of a loop.

Also handles: optimizing an existing post

The same references cover improving a page that already exists (rewrite a weak title and lead for a high-impression, low-CTR page, add structure and schema, sharpen the brand's recommendation context). Use references/on-page-and-technical.md, and log the change in the strategy doc.

References

• references/blog-archetypes.md: authoritative per-type specs for 10 blog types, each with structure, length, schema, AI-citation lever, and pitfalls. Listicles get the fullest treatment; then the AI tells to strip and the pre-publish quality gate.
• references/blog-playbook.md: answer-first structure; copy-paste content-block templates; the proven GEO writing rules; topic clusters; improving an existing post.
• references/brand-voice-and-quality.md: extract a voice profile from the brand's site; positioning clarity; the substance rules.
• references/ai-citation-playbook.md: the Princeton GEO factor order; E-E-A-T and author/entity signals; off-page mentions; per-engine notes; the honest Google stance.
• references/on-page-and-technical.md: on-page checklist; JSON-LD schema and deprecations; crawlability / AI-bot / server-rendering gates; how to measure impact.