SEO Plan Agent Skill

/digital-marketing-pro:seo-plan

Purpose

Generate a comprehensive SEO strategy with industry-specific templates, competitive analysis, content roadmap, and phased implementation plan. Covers both traditional SEO and AI search readiness.

Dispatcher mode (Confirm-Then-Dispatch)

When invoked on a brand that already has recent specialist outputs in ${CLAUDE_PLUGIN_DATA}/{brand}/seo/, this skill operates as an orchestrator — it reads those outputs as inputs, scores the brand across four pillars, and uses the weakest pillar to drive the lead theme of the plan.

Step D0 — detect fresh outputs (≤ 30 days)

Look under ${CLAUDE_PLUGIN_DATA}/{brand}/seo/ for the latest dated subfolder of each:

| Specialist skill | Output folder |

|---|---|

| /digital-marketing-pro:tech-seo-audit | seo/tech-seo-audit/{YYYY-MM-DD}/PLAN.md |

| /digital-marketing-pro:content-decay-scan | seo/content-decay-scan/{YYYY-MM-DD}/PLAN.md |

| /digital-marketing-pro:aeo-audit | seo/aeo-audit/{YYYY-MM-DD}/PLAN.md |

| /digital-marketing-pro:backlink-gap | seo/backlink-gap/{YYYY-MM-DD}/PLAN.md |

| /digital-marketing-pro:gsc-ai-performance | seo/gsc-ai-performance/{YYYY-MM-DD}/PLAN.md |

| /digital-marketing-pro:keyword-cluster | seo/keyword-cluster/{YYYY-MM-DD}/PLAN.md |

| /digital-marketing-pro:seo-drift | seo/seo-drift/{YYYY-MM-DD}/PLAN.md |

Any folder dated within the last 30 days counts as fresh — its PLAN.md becomes a primary input.

Step D1 — confirm before dispatching missing specialists

If some specialists have no fresh output, do not silently re-run them. Print exactly:

The following specialist outputs are missing or stale (>30 days old):
  - tech-seo-audit (last: 2026-05-12 — 23 days old)
  - backlink-gap (no run found)
  - gsc-ai-performance (no run found)

Running these now will use approximately N MCP credits / API calls.

Run them now in this session? (y / N — default N)

• If y — dispatch in this order:
• Parallel batch 1: tech-seo-audit, backlink-gap, aeo-audit, gsc-ai-performance (independent)
• Sequential after: content-decay-scan (depends on tech-seo-audit's URL inventory), keyword-cluster (depends on aeo-audit query set)
• Each specialist runs its own budget guard; surface aborts back to the user
• If N or default — fall through; treat missing pieces as Phase 0 ("Discovery") work in the final plan

Step D2 — pillar scoring (the heart of the dispatcher)

Score each of four pillars 1–10 based on the available specialist outputs:

| Pillar | Sources | What 10 looks like |

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

| Technical | tech-seo-audit / gsc-ai-performance / Core Web Vitals data | Clean crawlability, all CWV pass, schema validates, sitemap accurate |

| Content | content-decay-scan / seo-audit / content-engine outputs | Topic coverage matches search demand, no cannibalisation, freshness ≥ 80% |

| Topical | keyword-cluster / aeo-geo / entity-audit | Clear pillar+spokes structure, entity consistency across Knowledge Graph |

| AI Search | aeo-audit / gsc-ai-performance / aeo-geo | Cited in AI Mode + AI Overviews + ChatGPT + Perplexity for target queries |

The lowest-scoring pillar becomes the LEAD THEME of the next quarter's plan. Everything else is supporting work. This forces focus.

Step D3 — dispatcher output

Produce ${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-plan/{YYYY-MM-DD}/00-pillar-scorecard.md:

Pillar scorecard for {brand} ({date})
=====================================
Technical    : 8 / 10   ✓ healthy
Content      : 6 / 10   ⚠ moderate gaps
Topical      : 4 / 10   ⚠ LEAD THEME — weakest pillar
AI Search    : 7 / 10   ✓ trending up

Lead theme this quarter: Topical authority build-out
(keyword cluster expansion + entity consistency + Knowledge Graph optimisation)

The rest of the plan (sections 1-6 below) is then framed around the lead theme — supporting work for the other 3 pillars stays in the plan but doesn't drive timeline / budget.

Numbered output convention

The full dispatcher run produces, under ${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-plan/{YYYY-MM-DD}/:

00-pillar-scorecard.md      (from Step D2)
01-discovery.md             (business type, audience, competitors — from §1 below)
02-competitive-analysis.md  (competitors + gap synthesis — from §2 + backlink-gap if fresh)
03-architecture.md          (URL hierarchy, internal-link strategy — from §3 + keyword-cluster if fresh)
04-content-strategy.md      (content gaps, calendar, E-E-A-T — from §4 + content-decay-scan if fresh)
05-technical-foundation.md  (hosting, schema, CWV — from §5 + tech-seo-audit if fresh)
06-roadmap.md               (phased 12-month — from §6, framed around lead theme)
07-industry-template.md     (which template applied — from §Industry Templates)
08-kpi-dashboard.md         (metrics + cadence — what gets re-measured next drift)
PLAN.md                     (the deliverable)

Input Required

• Business type: SaaS, ecommerce, local service, publisher/media, agency, or general
• Website URL: Existing site (if any) to assess
• Target audience and markets: Geographic, demographic, and intent profiles
• Competitors: 3-5 competitor URLs for gap analysis
• Budget and timeline: Resource constraints
• KPIs: What success looks like (traffic, rankings, conversions, AI visibility)

Process

1. Discovery

• Business type, target audience, competitors, goals
• Current site assessment (if exists) — crawl health, content inventory, authority signals
• Budget and timeline constraints
• Key performance indicators (KPIs) aligned to business objectives

2. Competitive Analysis

• Identify top 5 competitors
• Analyze their content strategy, schema usage, technical setup
• Identify keyword gaps and content opportunities
• Assess their E-E-A-T signals
• Estimate domain authority and link profiles
• AI visibility comparison — which competitors appear in AI overviews

3. Architecture Design

• Design URL hierarchy and content pillars based on business model
• Plan internal linking strategy (hub/spoke, topic clusters)
• Sitemap structure with quality gates applied
• Information architecture for user journeys
• Navigation and breadcrumb planning

4. Content Strategy

• Content gaps vs competitors
• Page types and estimated counts
• Blog/resource topics and publishing cadence
• E-E-A-T building plan (author bios, credentials, experience signals)
• Content calendar with priorities
• AI-optimized content structure (entity consistency, citation-worthy formatting)

5. Technical Foundation

• Hosting and performance requirements
• Schema markup plan per page type
• Core Web Vitals baseline targets (LCP <2.5s, INP <200ms, CLS <0.1)
• AI search readiness requirements
• Mobile-first considerations
• International SEO setup (if applicable)

6. Implementation Roadmap (4 phases)

Phase 1: Foundation (weeks 1-4)

• Technical setup and infrastructure
• Core pages (home, about, contact, main services/products)
• Essential schema implementation (Organization, LocalBusiness, BreadcrumbList)
• Analytics and tracking setup (GA4, GSC, rank tracking)

Phase 2: Expansion (weeks 5-12)

• Content creation for primary pages
• Blog launch with initial posts
• Internal linking structure buildout
• Local SEO setup (if applicable)
• First E-E-A-T improvements (author pages, credentials)

Phase 3: Scale (weeks 13-24)

• Advanced content development (pillar pages, topic clusters)
• Link building and digital PR outreach
• GEO/AEO optimization for AI search visibility
• Performance optimization (CWV, page speed)
• Schema expansion (FAQ, Product, VideoObject as applicable)

Phase 4: Authority (months 7-12)

• Thought leadership content
• PR and media mentions
• Advanced schema implementation
• Continuous optimization based on data
• Competitive gap monitoring

Industry Templates

SaaS

• Primary pages: features, pricing, integrations, use cases, solutions by role
• Content pillars: product education, industry trends, comparison content, technical guides
• Schema focus: SoftwareApplication, Product, FAQPage (if eligible), HowTo (deprecated — use article format instead)
• Link strategy: integration partner pages, guest posts on tech blogs, product directories

Local Service

• Primary pages: services, service areas, about, contact, testimonials
• Content pillars: service guides, local area content, FAQ content, case studies
• Schema focus: LocalBusiness, Service, Review, BreadcrumbList, GeoCircle
• Link strategy: local directories, chamber of commerce, local press, community involvement

eCommerce

• Primary pages: categories, products, brands, collections, buying guides
• Content pillars: product education, comparison content, buying guides, trend content
• Schema focus: Product, ProductGroup, Offer, AggregateRating, BreadcrumbList, ItemList
• Link strategy: product reviews, affiliate partnerships, manufacturer relationships

Publisher/Media

• Primary pages: sections, topic pages, author pages, about, editorial standards
• Content pillars: news coverage, analysis, opinion, investigative, data journalism
• Schema focus: Article, NewsArticle, Person (authors), Organization, VideoObject
• Link strategy: original research citations, expert sourcing, data exclusives

Agency

• Primary pages: services, industries, case studies, team, methodology
• Content pillars: industry expertise, methodology content, case studies, thought leadership
• Schema focus: Organization, Service, Person (team), Article
• Link strategy: case study features, speaking engagements, industry publications, client co-marketing

Output

Deliverables

• SEO Strategy Document: Complete strategic plan with business context, competitive landscape, and strategic direction
• Competitive Analysis: Keyword gaps, content gaps, authority comparison, AI visibility comparison
• Content Calendar: 12-week content roadmap with topics, formats, keywords, and publishing schedule
• Implementation Roadmap: Phased action plan with milestones, responsibilities, and measurement checkpoints
• Site Architecture Plan: URL hierarchy, content pillar structure, internal linking strategy
• Schema Markup Plan: Per-page-type schema recommendations with JSON-LD templates
• KPI Dashboard Specification: Metrics to track, tools needed, reporting cadence

Agents Used

• seo-specialist — Strategy, competitive analysis, technical planning
• content-creator — Content strategy and calendar planning
• competitive-intel — Competitor analysis and gap identification
• marketing-strategist — Business alignment and KPI framework

Scripts Used

• competitor-scraper.py — Competitor site analysis
• tech-seo-auditor.py — Current site technical assessment
• keyword_cluster.py — Keyword clustering with SERP-overlap + quality scorecard (use via /digital-marketing-pro:keyword-cluster)
• content-scorer.py — Current content quality baseline

Quality scorecard

Every PLAN.md this skill produces must pass these gates before being declared ready:

| Gate | What it checks |

|---|---|

| lead_theme_named | 00-pillar-scorecard.md exists and names exactly one weakest pillar as lead theme |

| specialist_coverage | At least 3 of the 7 specialist sources have fresh outputs (≤30 days) |

| roadmap_phased | Roadmap has explicit Phase 1/2/3/4 dates with owners |

| kpi_attached | 08-kpi-dashboard.md lists ≥3 lagging + ≥3 leading metrics |

| drift_re-measure_scheduled | The KPI dashboard includes a recurring seo-drift cadence (default: quarterly) |

If any gate fails, surface the failure prominently in PLAN.md rather than silently shipping. (The dispatcher is skill-driven — there is no separate orchestrator script; the gate check is part of assembling PLAN.md.)

Chain handoffs

This skill is both a consumer (of specialists) and a producer (of the master plan):

Upstream (specialists this skill reads from):

• /digital-marketing-pro:tech-seo-audit
• /digital-marketing-pro:content-decay-scan
• /digital-marketing-pro:aeo-audit
• /digital-marketing-pro:backlink-gap
• /digital-marketing-pro:gsc-ai-performance
• /digital-marketing-pro:keyword-cluster
• /digital-marketing-pro:seo-drift

Downstream (skills that consume this plan):

• /digital-marketing-pro:content-engine — drafts the content scheduled in 04-content-strategy.md
• /digital-marketing-pro:campaign-plan — turns the roadmap into a sprint plan with owners
• /digital-marketing-pro:performance-report — re-measures against 08-kpi-dashboard.md cadence

Tips & caveats

• The dispatcher's default is not to dispatch. If specialists are missing, the default answer is N — list them as Phase 0 work. Only auto-dispatch on explicit y. This prevents accidental credit / API spend.
• Pillar scoring is opinionated, not measured. A 4/10 Topical pillar means "we don't have a clear authority structure", not "Google said so". The numbers are heuristic. Use them to focus the lead theme, not as KPIs.
• The lead theme should change quarterly. If the same pillar wins lead theme two quarters in a row, either the work isn't moving the needle (escalate) or the scoring is wrong (recalibrate with current data).
• Don't run this on Day 1 of an engagement. Run the specialists first so the dispatcher has fresh inputs. The first seo-plan run on a new brand will mostly be Phase 0 (Discovery) work.
• For YMYL clients, add E-E-A-T as a 5th pillar manually (the standard 4-pillar scoring doesn't separately weight authority signals).
• The 30-day freshness window is a default, not a rule. For high-velocity industries (news, SaaS launches), shorten to 14 days. For slow-moving categories (manufacturing, B2B services), 60 days is fine.

Context efficiency

This skill's primary inputs are the specialist PLAN.md outputs under ${CLAUDE_PLUGIN_DATA}/{brand}/seo/ (see the input table above) — these can sum to ~30-50KB. Don't load them eagerly — pick targeted sections:

• Grep before Read. Find the keyword or section heading first, then Read with offset + limit to pull just that range.
• Walk ${CLAUDE_SKILL_DIR} once. Use a single directory listing to see what's there, then Read only the files that match your current step.
• One source at a time. If the workflow says "consult three reference files," read them sequentially after deciding what you need from each. Bulk-loading all three blows the per-skill 5K-token budget that auto-compaction reserves.
• Strip noise from CSV inputs. If the input is a large CSV, grep the header line first to pick columns, then process row-by-row — do not Read the whole file into context.