AEO + SEO Playbook

This playbook is for one job: make SkillBoss easier to discover, compare, cite, and adopt across both traditional search engines and AI answer engines.

The target audiences are:

  1. Humans using OpenClaw, Claude Code, Cursor, Windsurf, and similar coding agents.
  2. Developers and teams evaluating an OpenAI-compatible API for production use.
  3. AI agents themselves discovering SkillBoss through docs, manifests, structured data, and machine-readable files.
ℹ️

Traditional SEO wins rankings. AEO wins citations. SkillBoss needs both because the buyer journey now crosses Google, Perplexity, ChatGPT, Claude, Gemini, and agent-run discovery flows.

North Star

The docs should answer three questions better than any competitor:

  1. How do I start using SkillBoss quickly?
  2. Why should I use SkillBoss instead of direct APIs or another gateway?
  3. How can my human team or my AI agent discover the right model, skill, or integration path?

Primary Query Clusters

ClusterAudienceExample QueriesBest Page Type
Install + setupHuman buyersclaude code setup, openclaw setup, skillboss quickstartInstallation docs, quick start
Alternatives + migrationHuman buyersclaude code alternative, openrouter alternative, openclaw alternativesComparison pages, migration guides
API + technical validationDevelopersopenai compatible api, multi model api, usage api, chat completions apiAPI reference, SDK docs, partner docs
Use-case intentBuildersbest ai model for coding, send email api for ai agents, stripe api for agentsUse-case docs, tutorial docs
Agent discoveryAI agentsllms.txt, agent.json, mcp manifest, tool discoveryFor AI Agents, agent discovery docs, manifests

Content Strategy by Audience

1. OpenClaw / Claude Code / coding-agent users

These users usually search with one of four intents:

  • setup
  • cheaper / faster model access
  • better model catalog
  • alternatives / comparisons

Pages that should carry this demand:

2. API buyers and partner teams

These visitors care about integration speed, compatibility, pricing clarity, and operational trust.

Pages that should carry this demand:

3. AI agents and agent-run evaluation flows

These systems optimize for extractable answers, manifests, structured data, and machine-readable files.

Priority discovery assets:

What Good Pages Must Include

Every strategic docs page should satisfy this checklist:

  • Clear answer in the first 2 paragraphs
  • A title that matches how a real buyer phrases the query
  • A short, literal implementation path
  • Internal links to the next decision page
  • At least one FAQ block when the page targets comparison, setup, or objections
  • Machine-readable metadata that reflects the actual page topic
  • A current date or freshness signal when the page can age quickly

Page Templates We Should Favor

Setup pages

Use for installation and onboarding queries.

  • Lead with the exact setup outcome
  • Include prerequisites
  • Include copy-paste commands
  • Include troubleshooting FAQs
  • Link to pricing, API docs, and agent-specific pages

Comparison pages

Use for X vs Y, alternative, better than, and migration queries.

  • Lead with the decision summary
  • Include an explicit comparison table
  • Separate who should choose SkillBoss vs who should not
  • Link to quick start, pricing, and integration docs

Use-case pages

Use for jobs-to-be-done and high-intent product exploration.

  • Lead with the use case and outcome
  • List the exact APIs/models/skills involved
  • Include a minimal architecture block
  • Link to API reference and install docs

Agent-discovery pages

Use for AI-native visibility.

  • Explain the machine-readable file or manifest first
  • Include direct examples that an agent can lift verbatim
  • Use stable URLs and compact explanations
  • Keep docs internally linked to manifests and model catalogs

Internal Linking Playbook

Links should move users from awareness to activation:

  1. Awareness pages should link to a setup page and a comparison page.
  2. Setup pages should link to pricing, troubleshooting, and one use-case page.
  3. API reference pages should link to quick start, usage, and catalog pages.
  4. Agent discovery pages should link to manifests, API docs, and the main catalog.

Bad pattern:

  • isolated docs pages that rank for a narrow keyword but do not move readers deeper into the product

Good pattern:

  • every page links to the next implementation or purchase decision

Structured Data + Metadata Standards

For docs pages, the baseline should be:

  • canonical URL
  • Open Graph + Twitter metadata
  • TechArticle schema
  • BreadcrumbList schema
  • FAQPage schema whenever the page includes real FAQs
  • keyword metadata aligned to the page intent

For AEO, the most important property is not “more schema everywhere.” It is schema that matches an actually extractable page.

AEO Writing Rules

Use these on any docs page that should be cited by ChatGPT, Perplexity, Claude, Gemini, or Google AI Overviews:

  • Answer first, explain second
  • Keep the first answer block self-contained
  • Use direct language, not marketing filler
  • Put product names and integration terms in natural language headings
  • Use tables for comparisons
  • Use FAQs for objections and edge cases
  • Keep implementation examples current and copy-pasteable
  • Use stable naming for models, routes, and manifests

Quarterly Content Priorities

These are the highest-value docs clusters for SkillBoss SEO/AEO growth:

  1. Claude Code setup, migration, troubleshooting, and alternatives
  2. OpenClaw setup, model choice, cost optimization, and alternatives
  3. OpenAI-compatible API reference and migration pages
  4. AI agent discovery pages around llms.txt, MCP, and manifest-based discovery
  5. High-intent use cases where SkillBoss compresses multiple tools into one integration

Measurement Framework

Track performance in three buckets:

Traditional SEO

  • impressions
  • clicks
  • CTR
  • ranking movement for priority queries
  • organic entries to install / API / pricing pages

AEO / answer engine visibility

  • citations in Perplexity, ChatGPT, Claude, Gemini
  • share of mentions vs direct competitors
  • frequency of being cited on comparison and setup queries

Activation quality

  • visits from docs to /console
  • visits from docs to /catalog
  • visits from docs to /pricing
  • partner inquiries from docs
  • API key creation and usage after docs entry

Editorial Cadence

Weekly

  • refresh stale screenshots or setup commands
  • review broken internal links
  • update one high-intent page in the Claude Code / OpenClaw cluster

Monthly

  • rewrite at least one comparison page and one use-case page
  • audit FAQ quality on top-entry docs pages
  • update internal links from blog pages to activation pages

Quarterly

  • re-evaluate the top query clusters
  • add missing comparison pages
  • refresh titles and descriptions for strategic docs
  • verify machine-readable files still reflect the docs truthfully

Common Failure Modes

Publishing technically correct docs that do not target a real query. Search engines and AI answer engines reward pages that clearly match a user intent, not just pages that exist.

Assuming manifests and llms files are enough on their own. They help agent discovery, but human-readable docs still need clear answers, comparisons, FAQs, and internal links so both humans and AI systems can trust and cite the site.

Start with the pages closest to revenue: quick start, Claude Code setup, OpenClaw integration, API overview, API catalog, pricing-adjacent use cases, and partner quick start.

Write for a human decision-maker first, but structure each section so it can be extracted as a standalone answer. That means concise lead paragraphs, literal headings, tables, FAQs, and stable terminology.

Immediate Next Actions

  1. Keep the docs sidebar free of broken routes.
  2. Add keyword coverage and FAQ schema support at the docs template level.
  3. Prioritize the Claude Code, OpenClaw, API, and partner docs cluster for ongoing refreshes.
  4. Treat docs as both a product surface and a search surface.
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