From FORSVN
Audits and plans search visibility across six modes: technical SEO, AI/answer-engine optimization, programmatic SEO, competitor comparison pages, full SEO strategy, and app store optimization. Use to diagnose traffic drops or plan search growth.
How this skill is triggered — by the user, by Claude, or both
Slash command
/forsvn:optimize-seo [url or mode][url or mode]This skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
*Communication — Horizontal. Covers the full SEO surface: technical foundations, AI/agent engine optimization, programmatic page generation, app store optimization, and competitor comparison content.*
agents/_template.mdagents/ai-presence-agent.mdagents/ai-structure-agent.mdagents/aso-competitive-agent.mdagents/aso-keyword-agent.mdagents/aso-listing-agent.mdagents/aso-reviews-agent.mdagents/authority-agent.mdagents/comparison-page-agent.mdagents/content-quality-agent.mdagents/crawl-agent.mdagents/critic-agent.mdagents/foundations-agent.mdagents/prioritization-agent.mdagents/programmatic-quality-agent.mdagents/programmatic-template-agent.mdreferences/_shared/before-starting-check.mdreferences/_shared/evidence-classes.mdreferences/_shared/execution-policy.mdreferences/_shared/hook-archetypes.mdCommunication — Horizontal. Covers the full SEO surface: technical foundations, AI/agent engine optimization, programmatic page generation, app store optimization, and competitor comparison content.
Core Question: "How do we get found — by both search engines and AI models?"
Why this skill exists, when NOT to use it, 10-item quality gate summary, six routes by mode:
references/playbook.md[PLAYBOOK].
SEO mixes hard technical constraints (CWV thresholds, character limits, schema validation) with strategic judgment. Platform specs are constraints; strategic recommendations are defaults with deviation context. Specific > Vague > Comprehensive > Generic — every recommendation names exact page, exact change, expected impact.
Before delivering, all must hold:
references/_shared/platform-intelligence/[platform].md (mapped per agent in references/platform-search.md). Generic "post on LinkedIn" is not sufficient — recommendation references §1/§2/§3/§4 of the platform-intelligence catalog by section.Per references/_shared/before-starting-check.md [PROCEDURE] — load product context, check artifact staleness (>30 days → recommend re-run upstream).
| Artifact | Source | Required? |
|---|---|---|
icp-research.md | research-icp | Recommended — audience search behavior drives strategy |
campaign-plan.md | plan-campaign | Optional — pillars inform topic clusters |
product-context.md | research-icp | Optional — positioning context |
Canonical Pre-Dispatch: references/_shared/pre-dispatch-protocol.md [PROCEDURE].
Needed dimensions: mode (audit / ai / programmatic / competitor / aso), site or property, audience, geographic + language scope.
Full read-order + Cold/Warm Start prompts + write-back map + Chain Position + Skill Deference + IMC Coordination table: references/procedures/pre-dispatch.md [PROCEDURE].
Per references/_shared/mode-resolver.md [PROCEDURE] — auto-downgrade ≤3 sentences, no prior artifacts; --fast skips Layer 2 (no prioritization, no critic), runs single-agent. --fast does NOT skip Cold Start or Critical Gates 1-4.
Session execution profile (single-vs-multi): inherit per references/_shared/execution-policy.md.
Route-collapse default (multi-route deep override): a ≤3-sentence single-scope ask (one mode's keywords, no prior artifacts) auto-resolves to that mode's minimal Route (A/B/C/D/F) + critic — never Route E "Full SEO" — without needing --fast. Cross-mode asks, or an upward override ("full strategy", "thorough"), use the full multi-mode orchestration.
15 sub-agents across two layers (13 Layer 1 domain agents — crawl / foundations / content-quality / authority / ai-structure / ai-presence / programmatic-template / programmatic-quality / comparison-page / aso-keyword / aso-listing / aso-reviews / aso-competitive — + Layer 2 prioritization → critic). Full table with per-agent focus + per-route composition: references/agent-manifest.md [PROCEDURE].
Diagnose first, then enter the right mode. Modes can run sequentially. Start with Technical Audit if never audited — no point optimizing for AI citations if crawlers can't reach content (Critical Gate 2).
| Situation | Mode | Route |
|---|---|---|
| Technical issues / traffic dropped / never audited | Technical Audit | Route A |
| Want citations from ChatGPT / Perplexity / AI search | AI SEO (AEO) | Route B |
| Structured data, want to generate pages at scale | Programmatic SEO | Route C |
| Rank for competitor comparison queries | Competitor Pages | Route D |
| Comprehensive SEO strategy | Full SEO (Technical + AI) | Route E |
| Distribute via app stores / listings (App Store, Play Store, G2, Capterra, Product Hunt) | ASO | Route F |
Per-route Layer 1 + Layer 2 composition: references/agent-manifest.md § "Per-route composition". Route E produces TWO artifacts (seo-audit.md + seo-ai.md). Full pre-writing object schema, 8-step Multi-Agent Dispatch flow, Single-Agent Fallback, prioritization mechanics (Quick Wins → Strategic Investments → Low-Hanging Fruit → Backlog; P1-P4 phasing; dependency mapping), critic gate mechanics (10-item rubric, binary PASS/FAIL, max 2 rewrite cycles, 11-row Rewrite Routing Table), --fast execution path: references/procedures/dispatch-mechanics.md [PROCEDURE].
Route B control surface. Bing backs ChatGPT/Perplexity/Copilot — confirm Bing readiness before AI-citation tactics for those products (references/platform-intelligence/bing-readiness.md), then score extractability (distinct from on-page) with references/geo-citation-readiness-checklist.md.
Route C selectors. Pick the archetype from the 12-playbook taxonomy (references/programmatic-template-playbooks.md + the design/defensibility rules in references/programmatic-seo.md); for a proprietary-data play, run the build-vs-pitch-direct classifier in references/linkable-asset-playbook.md.
Output path: docs/forsvn/artifacts/marketing/seo-[mode].md (mode ∈ {audit, ai, programmatic, competitor, aso}). On re-run, rename existing to seo-[mode].v[N].md and create new with incremented version.
Frontmatter (REQUIRED): skill: optimize-seo, mode, version (int), date, status.
Body sections (REQUIRED): Diagnosis / Findings / Priority Actions / Implementation Plan / Dependencies / Metrics to Track / Next Step.
Full template + finding format (Issue / Impact / Evidence / Fix / Priority) + per-mode metrics defaults: references/format-conventions.md [PROCEDURE].
17 patterns (9 SEO-specific + 4 retrieval-layer + 4 cross-cutting marketing-stack) with detection rules, bad/good examples, and per-pattern agent ownership verified against critic-agent.md Rewrite Routing: references/anti-patterns.md [ANTI-PATTERN].
Most common in practice: "Consider improving" (gate 3 hedge-language), "Do SEO" without diagnosis (no mode chosen), Ignoring third-party presence for AI SEO (gate 8 — third-party drives ~6.5x more AI citations than owned), AI-SEO work before technical crawl/index fixes (#13 — retrieval-layer optimization on uncrawlable pages is wasted work).
Every run ends with explicit status:
research-icp or proceed with explicit scope reductionEnd-to-end Route A walkthrough (Pre-Dispatch → parallel Layer 1 → merge → prioritization → critic PASS → deliver → FAIL handling → --fast variant): references/examples/seo-walkthrough.md [EXAMPLE].
references/playbook.md [PLAYBOOK]references/format-conventions.md [PROCEDURE]references/anti-patterns.md [ANTI-PATTERN]references/procedures/{pre-dispatch, dispatch-mechanics}.md + references/agent-manifest.md [PROCEDURE]references/examples/seo-walkthrough.md [EXAMPLE]references/{technical-audit, technical-crawler-checklist, ai-seo, retrieval-layer-seo, live-serp-remediation, programmatic-seo, programmatic-template-playbooks, geo-citation-readiness-checklist, linkable-asset-playbook, competitor-pages, schema-reference, aso, platform-search}.md. Shared: references/_shared/evidence-classes.md (canonical: skills/marketing/_shared/evidence-classes.md, shared with monitor-aeo).references/platform-intelligence/bing-readiness.md (Route B). See also Route B/C hooks under Routing Logic.references/_shared/platform-intelligence/{tiktok, reels, shorts, linkedin, x, youtube}.md — canonical at top-level references/platform-intelligence/ (D13). Agent-to-section map in references/platform-search.md.references/_shared/{before-starting-check, manifest-spec, mode-resolver, pre-dispatch-protocol}.mdagents/ — see Agent Manifest above. critic-agent.md holds the canonical 10-item quality gate + 11-row Rewrite Routing Table.npx claudepluginhub hungv47/meta-skills --plugin forsvnOptimizes content for traditional search engines (SEO) and AI visibility (AEO/GEO) including featured snippets, AI Overviews, and generative AI citations. Use for audits, schema markup, site architecture, and AI search readiness.
Builds a phased, quarter-by-quarter SEO roadmap for a domain based on competitive position, content gaps, technical debt, and AI Search readiness. Use when asked for an overall SEO plan or strategy.
Runs comprehensive SEO audits across 24 sub-skills: site/technical audits, Core Web Vitals, schema, sitemaps, E-E-A-T content quality, image optimization, AI overviews (GEO), hreflang, backlinks, local/maps, and drift monitoring.