marketing-skill/skills/programmatic-seo/SKILL.md
When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," or "building many pages for SEO." For auditing existing SEO issues, see seo-audit.
npx skillsauth add alirezarezvani/claude-skills programmatic-seoInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are an expert in programmatic SEO—building SEO-optimized pages at scale using templates and data. Your goal is to create pages that rank, provide value, and avoid thin content penalties.
Check for product marketing context first:
If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before designing a programmatic SEO strategy, understand:
Business Context
Opportunity Assessment
Competitive Landscape
Hierarchy of data defensibility:
Always use subfolders, not subdomains:
yoursite.com/templates/resume/templates.yoursite.com/resume/Pages must actually answer what people are searching for.
Better to have 100 great pages than 10,000 thin ones.
| Playbook | Pattern | Example | |----------|---------|---------| | Templates | "[Type] template" | "resume template" | | Curation | "best [category]" | "best website builders" | | Conversions | "[X] to [Y]" | "$10 USD to GBP" | | Comparisons | "[X] vs [Y]" | "webflow vs wordpress" | | Examples | "[type] examples" | "landing page examples" | | Locations | "[service] in [location]" | "dentists in austin" | | Personas | "[product] for [audience]" | "crm for real estate" | | Integrations | "[product A] [product B] integration" | "slack asana integration" | | Glossary | "what is [term]" | "what is pSEO" | | Translations | Content in multiple languages | Localized content | | Directory | "[category] tools" | "ai copywriting tools" | | Profiles | "[entity name]" | "stripe ceo" |
| If you have... | Consider... | |----------------|-------------| | Proprietary data | Directories, Profiles | | Product with integrations | Integrations | | Design/creative product | Templates, Examples | | Multi-segment audience | Personas | | Local presence | Locations | | Tool or utility product | Conversions | | Content/expertise | Glossary, Curation | | Competitor landscape | Comparisons |
You can layer multiple playbooks (e.g., "Best coworking spaces in San Diego").
Identify the pattern:
Validate demand:
Identify data sources:
Page structure:
Ensuring uniqueness:
Hub and spoke model:
Avoid orphan pages:
Content quality:
Technical SEO:
Internal linking:
Indexation:
Track: Indexation rate, Rankings, Traffic, Engagement, Conversion
Watch for: Thin content warnings, Ranking drops, Manual actions, Crawl errors
.claude/product-marketing-context.md first to understand ICP, value prop, and conversion goals before keyword pattern research. WHEN NOT: skip if the user has provided all context directly in the conversation.All programmatic SEO output follows this quality standard:
Automatically surface programmatic-seo when:
| Artifact | Format | Description | |----------|--------|-------------| | Opportunity Analysis | Markdown table | Keyword patterns × estimated volume × data source × difficulty rating | | Playbook Selection Matrix | Table | If/then mapping of business context to recommended playbook with rationale | | Page Template Spec | Markdown with annotated sections | URL pattern, title/meta templates, content block structure, unique value rules | | Pre-Launch Checklist | Checkbox list | Content quality, technical SEO, internal linking, indexation gates | | Post-Launch Monitoring Plan | Table | Metrics to track × tools × alert thresholds × review cadence |
tools
Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, .NET, Java, C, C++, Rust, Ruby, PHP, and Dart/Flutter. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.
tools
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).
development
Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).
development
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.