Build an organic-traffic operating system for any site or app: a multi-phase, resumable engine that plans and ships a BATCH ROADMAP of landing pages (use-cases, playbooks, /for/ pages, roundups) on top of real keyword research, with a persistent phase tracker. Use when the user says 'SEO machine', 'build organic traffic', 'rank on Google', 'we need traffic', 'SEO roadmap', 'batch of pages', 'pages roadmap', or 'build an SEO engine'. Distinct from `seo-audit` (one-off diagnostic) and `seo-content` (single-article writer): this skill owns the multi-page roadmap, run sequencing, page generation, internal linking, and the persistent phase tracker across the whole run. For a single alternatives or vs/comparison page, see /competitor-alternatives; for programmatic SEO templates and content at scale, see /seo-content; for off-page link building, see /off-page-seo. Resumable — every invocation continues the last run.
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Build an organic-traffic operating system for any site or app: a multi-phase, resumable engine that plans and ships a BATCH ROADMAP of landing pages (use-cases, playbooks, /for/ pages, roundups) on top of real keyword research, with a persistent phase tracker. Use when the user says 'SEO machine', 'build organic traffic', 'rank on Google', 'we need traffic', 'SEO roadmap', 'batch of pages', 'pages roadmap', or 'build an SEO engine'. Distinct from `seo-audit` (one-off diagnostic) and `seo-content` (single-article writer): this skill owns the multi-page roadmap, run sequencing, page generation, internal linking, and the persistent phase tracker across the whole run. For a single alternatives or vs/comparison page, see /competitor-alternatives; for programmatic SEO templates and content at scale, see /seo-content; for off-page link building, see /off-page-seo. Resumable — every invocation continues the last run.
["seo machine","build organic traffic","rank in google","seo roadmap","batch of alternatives pages","batch of pages","pages roadmap","we need traffic"]
SEO Machine
End-to-end engine for building organic search traffic. Ships dozens of programmatic landing pages — alternatives, comparisons, use-cases, playbooks — backed by real keyword research, with a persistent roadmap the user resumes across sessions.
Conversion-first (alternatives + comparisons before blogs). Publish-early (a thin page indexed today beats a perfect page indexed in three weeks). Stack-native (writes into the user's framework — Next.js, Astro, Rails+Inertia, or a portable markdown fallback).
Two modes, auto-detected
Mode
When
What it produces
Initialize
docs/seo-machine.md does not exist
Stack detection → brand context → keyword research → tech audit → roadmap + link inventory
Resume
docs/seo-machine.md exists
Reads the tracker, picks the next pending phase (or one the user names), executes end-to-end through the quality gates
Detection rule on every invocation: check docs/seo-machine.md at repo root (or the path recorded in .seo/config.json). No file → Initialize. File exists → Resume. The user does not need to remember which mode they're in.
Publishing Order (the load-bearing decision rule)
The roadmap orders patterns by conversion intent first, traffic intent second. This is the single most important decision the skill makes — it's why the alternatives + comparison pages ship before the playbooks + blog posts.
Order
Pattern
Why
Cost
1
/alternatives/[competitor] (Pattern A)
Highest conversion intent — the reader is already in market
~4 hours per page
2
/compare/[a]-vs-[b] (Pattern D)
Be the third option in any two-vendor comparison
~3 hours per page
3
/for/[use-case] and /for/[audience] (Pattern B/C)
JTBD without competitor name in query — high TP/volume ratio
~4-5 hours per page
4
/playbooks/[topic] (Pattern E)
Authority + AI-citation surface area + inbound link draw
~2-3 days per page
5
/blog/... (out of scope here)
Lowest conversion intent; defer until ~10 indexed pages exist
—
Why this order matters: alternatives pages convert 5–20× blog posts at 1/10 the search volume. Shipping one alternatives page is worth ten generic blog posts on the same topic. The roadmap should reflect this — Phase 0 (tech audit) → Phases 1–N (alternatives, then comparisons, then use-cases) → late phases (playbooks) → never (blogs, unless explicitly requested by the user).
Striking-distance boosts (pages already ranking pos 5–20 in GSC) jump the queue when they exist — fastest wins per hour of work.
On Activation
Load brand context where present: brand/keyword-plan.md, positioning.md, competitors.md, audience.md, stack.md. Missing files are fine.
Surface what loaded:
Backend Selection
Validate KD/competition with OpenSEO get_keyword_metrics / get_serp_results before generating pages; consume openseo-keyword-clustering outputs when present. Qualitative research uses Exa-stack (or manual) per the shared ordered resolver — record research_backend in .seo/config.json. Full contract: skills/openseo/references/backend-contract.md.
Brand context loaded:
├── Keyword Plan ✓/✗ (seeds the roadmap; ✗ → generate during Initialize)
├── Positioning ✓/✗ (drives /compare and /alternatives angles)
├── Competitors ✓/✗ (target list for /alternatives pages)
├── Audience ✓/✗ (intent buckets for /for/<persona> pages)
└── Stack ✓/✗ (selects references/stacks/<framework>.md)
Progressive enhancement: with zero brand files the skill still works — it derives signal from the repo during Initialize Step 2. With full brand context it skips re-discovery and goes straight to research + roadmap.
Exa recipes: references/exa-recipes.md + references/api-stack-recipes.md. Manual fallback: references/manual-research.md. Ahrefs is an optional paid overlay only (see Exa recipes appendix).
Hard prerequisites
#
Check
Failure mode
1
git rev-parse --is-inside-work-tree succeeds
Stop. Tell the user this skill writes a persistent roadmap; initialize git or run from a repo.
2
A stack is detectable — one of package.json, Gemfile, composer.json, requirements.txt, astro.config.*, next.config.*, nuxt.config.*, gatsby-config.*, _config.yml, config.toml, pyproject.toml
Ask the user what stack they're on before continuing.
3
Research backend resolved (skills/openseo/references/backend-contract.md)
Never refuse to run — fall through to manual mode.
Initialize mode
Goal: end the run with a written docs/seo-machine.md containing keyword research, a phase tracker grouped by pattern, and technical-audit findings — plus .seo/brand.md and .seo/link-inventory.md.
Step 1 — Detect stack + frontend convention
Read references/stacks/detection.md. Identify framework family, routing convention (file-based vs controller-based), component language, and existing marketing pages (git ls-files | grep -iE 'marketing|landing|pages/(home|about|pricing)'). Resolve ambiguity with AskUserQuestion. Persist to .seo/config.json.
Step 2 — Detect brand + product context
Read every signal first, propose .seo/brand.md, then ask only about gaps. Signals: CLAUDE.md, README.md, package.json / Gemfile.lock, tailwind.config.* or design-token CSS, app/views/marketing/* or pages/index.*, pricing page.
If brand/voice-profile.md and brand/positioning.md already exist (mktg-native project), read them and skip 80% of the questions — those files already say who the buyer is and what the brand sounds like.
Otherwise use a single AskUserQuestion (3–4 questions max) to fill gaps. Required to know:
Product one-liner (≤20 words)
Primary persona (e.g. "B2B SaaS founder", "indie agency owner")
Replaces Ahrefs KD with SERP-composition-derived signal
Exa search + per-result company_research_exa
F. Backlink prospecting
Referring-domain proxy via Exa
Exa search + DR proxy (see off-page-seo skill)
G. Content gap
Their indexed keywords − ours, ranked by DR-cap fit
Recipes B + own-site Exa lookup
Then pull cross-API compound recipes from references/api-stack-recipes.md for moves Ahrefs alone can't do — pain-point cluster discovery (/last30days + mktg-x + Exa deep search), OSS competitor teardown (gh + DeepWiki + Exa), outreach prospect discovery (Exa Websets + people-research), newcomer surveillance (Exa Websets cron).
When Exa is unavailable, fall back to references/manual-research.md (paste-from-UI workflow). When the user has paid Ahrefs, layer it on top per the appendix in exa-recipes.md — don't replace.
Cache the raw output to .seo/keyword-research.json. Curate the decision-ready summary into the Keyword Research Appendix section of docs/seo-machine.md.
Step 4 — Technical foundations audit
Run scripts/tech_audit.py (sitemap, robots, meta-tag uniqueness, schema). Whatever it finds becomes Phase 0 in the roadmap. Day-0 crawl shapes Google's understanding of the site for months — retroactive fixes are harder.
Step 5 — Generate the roadmap
Fill assets/roadmap-template.md with:
Site facts (domain, DR, stack, brand colors, fonts) from steps 1–2
Reference data — paths to controllers / page files this skill will edit
Keyword Research Appendix — curated, grouped by pattern
Phase Status Tracker — auto-populated:
Phase 0: technical foundations fixes
Phase 1+: one row per page candidate
Group by pattern. Within a pattern, order by traffic_potential desc → volume desc → KD asc
Striking-distance boosts near the front (fastest wins on existing sites)
Off-page checklist (directories + outreach) tail-end, one phase per category
Write to the configured path (default docs/seo-machine.md). Print the path back and recommend a human review pass before Phase 0.
Step 6 — Generate .seo/link-inventory.md
Every phase reads this file to pick internal links. Use assets/link-inventory-template.md. Pre-populate from existing routes (features, tools, pricing, blog posts). Each phase appends to it as new pages ship.
Step 7 — Hand off
✓ Initialize complete
Roadmap: docs/seo-machine.md
Brand context: .seo/brand.md
Keyword cache: .seo/keyword-research.json
Link inventory: .seo/link-inventory.md
Config: .seo/config.json
Next: review docs/seo-machine.md, then run me again to execute Phase 0.
Do not auto-execute Phase 0. Pattern priorities and competitor lists are decisions worth a human pass.
Resume mode
Goal: pick the next phase from the tracker, execute end-to-end with quality gates, hand back so the user can commit/PR.
Step 1 — Read state
Load docs/seo-machine.md, .seo/brand.md, .seo/link-inventory.md, .seo/config.json. Find the Phase Status Tracker, identify the next pending phase with the lowest number, print it back along with the two phases that follow.
Step 2 — Confirm scope
Single AskUserQuestion:
"Continue with Phase N: [title]?"
Options: "Yes, start Phase N" / "Pick a different phase" / "Re-audit (refresh research)" / "Just show the tracker"
"Different" → list pending phases. "Re-audit" → loop back into Initialize steps 3–5. "Show" → print tracker and stop.
Step 3 — Execute
Pattern → reference mapping:
Phase type
Reference
Phase 0 — technical foundations
references/technical-audit.md
Pattern A — /alternatives/[competitor]
references/patterns/alternatives.md
Pattern B/C — /for/[use-case] or /for/[audience]
references/patterns/use-case.md
Pattern D — /compare/[a]-vs-[b]
references/patterns/compare.md
Pattern E — /playbooks/[topic] long-form
references/patterns/playbooks.md
Striking-distance boost
references/striking-distance.md
Off-page checklist phase
references/off-page.md
Internal-link spine audit
references/quality-bars.md (link-audit section)
For page-generating phases, the flow is always:
Re-research — current competitor pricing, feature changes. Don't trust 60-day-old cached data on commercial-intent terms.
Generate the page payload — output format follows the stack (references/stacks/<framework>.md) or references/stacks/markdown-fallback.md.
Verify against the quality bar (word count, internal links, schema, honesty section on alts). Run scripts/word_count.py and scripts/link_audit.py. If a check fails, fix it — don't ship under-spec work.
Update .seo/link-inventory.md with the new page.
Update the tracker row in docs/seo-machine.md — status completed, PR ref or commit SHA. Same edit batch as the page work so reviewers see both in one diff.
Backlink checklist + Ahrefs referring-domains research
references/quality-bars.md
Verification spec per pattern
scripts/word_count.py
Strip markup → word count
scripts/link_audit.py
Verify internal-link minimums per page
scripts/tech_audit.py
Sitemap.xml + robots.txt + meta-tag scanner
assets/roadmap-template.md
docs/seo-machine.md skeleton
assets/brand-template.md
.seo/brand.md skeleton
assets/link-inventory-template.md
.seo/link-inventory.md skeleton
Outputs
The skill writes to project paths, not brand/. This is why writes: in skills-manifest.json is [] — the manifest declares only brand/*.md writes, and seo-machine's outputs live in the user's repo, not in brand memory.
Output
Mode
Purpose
docs/seo-machine.md
Initialize (write), Resume (update phase row)
Persistent sprint roadmap — Phase Status Tracker + Reference Data + Keyword Research Appendix. Single source of truth across sessions.
.seo/brand.md
Initialize
Product context derived from repo + user answers (one-liner, persona, competitors, voice tags, anti-positioning).
.seo/link-inventory.md
Initialize (create), Resume (append per phase)
Every internal-link target the skill can use. Each phase appends new pages.
.seo/keyword-research.json
Initialize
Cached raw output from Ahrefs / Exa / manual research. Read by every phase, refreshed every 30 days.
.seo/config.json
Initialize
Stack info, research backend choice, project IDs. Persists machine-readable state.
Phase-specific page files
Resume (per phase)
Stack-native page files (e.g. app/controllers/marketing_controller.rb + app/frontend/pages/Alternatives/Show.tsx for Rails+Inertia; app/[pattern]/[slug]/page.tsx for Next.js App Router; etc.). Paths follow references/stacks/<framework>.md.
This follows the Long-Arc Sprint Persistence Pattern documented in AGENTS.md — docs/seo-machine.md is the canonical doc that survives session interruption.
/cmo integration
/cmo routes here under Playbook #9 — SEO Authority Build, Path B (programmatic sprint). On a cold project /cmo first spawns mktg-brand-researcher, mktg-audience-researcher, mktg-competitive-scanner in parallel (foundation), runs keyword-research to populate brand/keyword-plan.md, then hands off here. After every phase, /cmo spawns mktg-content-reviewer + mktg-seo-analyst in one message to score the page batch before the user commits.
See skills/cmo/rules/playbooks.md and skills/cmo/rules/sub-agents.md for the full handoff contract.
