name: seo-ai-optimizer
description: Audit and optimize websites for technical SEO, content SEO, and AI bot accessibility. Fixes meta tags, sitemaps, robots.txt, structured data, llms.txt, and GPTBot/ClaudeBot directives. Not for App Store ASO, paid search, or blog writing.
license: MIT
effort: high
metadata:
    version: 1.3.1
    author: "Luong NGUYEN <luongnv89@gmail.com>"

SEO & AI Bot Optimizer

Audit and optimize website codebases for search engines and AI systems.

Dependency Preflight (mandatory)

Step 8 invokes website-agent-readiness. Verify it is installed before the first

step that changes anything:

test -d "$HOME/.claude/skills/website-agent-readiness" ||
  asm list -p claude --json | grep -q '"website-agent-readiness"' || {
  echo "Missing required skill: website-agent-readiness" >&2
  echo "Install it:      asm install github:luongnv89/skills:skills/website-agent-readiness -p claude -s global --yes" >&2
  echo "No asm yet:      npm install -g agent-skill-manager" >&2
  echo "Verify:          asm list -p claude --json | grep 'website-agent-readiness'" >&2
}

The install path is tested before asm list: this skill ships in the same repo as its

dependency, so a repo-installed website-agent-readiness is present without the curated

registry knowing the bare name — an asm list check alone would nag on every run, and a

bare-name asm install would not resolve.

On a miss, print those commands and skip Step 8 — Steps 1-7 audit the codebase and

still run. Never invoke a half-installed skill. website-agent-readiness enforces its own

prerequisites (curl, python3, and for issue filing git, gh, plan-to-issues); this

skill does not re-check them.

Repo Sync Before Edits (mandatory)

Before modifying any project files, sync the current branch with remote:

branch="$(git rev-parse --abbrev-ref HEAD)"
git fetch origin
git pull --rebase origin "$branch"

If the working tree is not clean, stash first, sync, then restore:

git stash push -u -m "pre-sync"
branch="$(git rev-parse --abbrev-ref HEAD)"
git fetch origin && git pull --rebase origin "$branch"
git stash pop

If origin is missing, pull is unavailable, or rebase/stash conflicts occur, stop and ask the user before continuing.

Prerequisites

Before starting the SEO audit, ensure the following:

• Environment: The project must be managed by a git repository.
• Tools: Python 3.x must be installed and available in the path.
• Audit Script: scripts/audit_seo.py (shipped with this skill) is invoked against the audited project: python scripts/audit_seo.py <project-root>.
• Access: You must have write access to the project files and permission to create new files (robots.txt, llms.txt, etc.).

Quick Reference

Consult these reference files as needed during the workflow:

• references/workflow-detail.md — Detailed checklists, templates, and implementation steps
• references/technical-seo.md — Full SEO checklist and best practices
• references/framework-configs.md — Framework-specific configuration
• references/ai-bot-guide.md — AI crawler directives, llms.txt format, JSON-LD templates

Environment Check

This skill has two modes of operation:

With Subagent Architecture (Recommended):

If the Agent tool is available in your environment, the audit runs via a 4-phase subagent workflow for maximum accuracy and depth. See references/subagent-architecture.md.

Without Subagent Tool (Fallback):

If Agent is not available, the skill runs a complete audit in a single conversation. The end result (SEO audit report) is the same.

Important

• Audit first, present findings, then propose a plan — never modify files without user approval
• Safety First: Always show a diff and get explicit confirmation before writing any file change
• Fetch latest best practices via web search during each audit to supplement embedded knowledge

Workflow

1. Detect -- Identify project framework and scan for relevant files
2. Audit -- Run automated scan + manual review across 4 categories
3. Research -- Web search for latest SEO/AI bot best practices
4. Report -- Present findings grouped by severity
5. Plan -- Propose prioritized improvements for user approval
6. Implement -- Apply approved changes following the Safety Protocol
7. Validate -- Re-check modified files
8. Agent-readiness handoff -- Scan the deployed site via /website-agent-readiness

---

Step 1: Detect Project Type

Run the audit script to detect framework and scan files:

python scripts/audit_seo.py <project-root>

If the script reports "No HTML/template files found," inform the user: this skill is designed for web frontends with HTML output.

Step 2: Audit

The audit script checks per-file issues and project-level issues. After running the script, perform a manual review for items requiring human judgment (content quality, links, E-E-A-T).

For the full manual review checklist, see references/workflow-detail.md.

Step 3: Research Latest Best Practices

Use web search to check for updates (SEO best practices, AI bot directives, llms.txt spec, algorithm updates). Compare findings with embedded knowledge in references/.

Step 4: Report

Present the audit report grouping findings by severity (Critical, Warning, Info) and project-level findings (robots.txt, sitemap, llms.txt, JSON-LD).

Step 5: Plan

Present a prioritized improvement plan using the template in references/workflow-detail.md.

Ask the user: "Which improvements should I implement? You can approve all, select specific items, or modify the plan."

Do NOT proceed without explicit approval.

Step 6: Implement

Apply approved changes following the Safety First protocol:

1. Show Diff: For every file change, generate and show a clear diff or summary.
2. Confirm: Request explicit user confirmation before writing each file (or batch).

For detailed implementation instructions per category (Technical SEO, robots.txt, llms.txt, JSON-LD, sitemaps), see references/workflow-detail.md.

Step 7: Validate

After implementing changes, re-run the audit script on modified files to verify critical issues are resolved and check for regressions.

Step 8: Agent-Readiness Handoff

Steps 1-7 fix the codebase. This step scores the deployed site as an AI agent sees

it, catching what a static audit cannot: rendered output, live headers, and runtime

robots/llms.txt delivery.

Run it when both hold, else skip and say why:

• The site is deployed at a reachable public URL, and the Step 6 changes are live there
• The user supplies that URL and approves the handoff

/website-agent-readiness <live-url>

That skill owns its own gated pipeline (scan → triage → agent-ready-plan.md → issue

filing) — do not re-run its phases here, and do not re-apply its recommended llms.txt or

metadata fixes inline. Anything it returns that belongs in the codebase comes back through

Steps 5-7 as a normal approved plan item.

Verify: the step passes when agent-ready-plan.md exists in the working directory and

its reported 0-5 agent-readiness score is recorded in the final summary; a skip passes when

the summary names which of the two conditions above was unmet.

Step Completion Reports

After each step, emit a ◆ status block. For templates and per-step check lists, see references/step-reports.md.

Acceptance Criteria

See the itemized checklist in references/workflow-detail.md (Acceptance Criteria) — a run only passes when every item there is checked.

Expected Output

After a full run, the agent should produce:

1. Audit Report: A structured markdown report grouping findings by severity.
2. Implementation: Modified or new files (robots.txt, llms.txt, sitemap.xml, JSON-LD) with confirmed changes.
3. Validation Report: A post-fix verification showing critical issues reduced to 0.
4. Agent-Readiness Handoff: The live-site score and agent-ready-plan.md from Step 8, or a one-line reason it was skipped.

For a concrete example of the audit report output, see references/workflow-detail.md.