复制安装命令
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
Codex-first SEO analysis suite with 1 orchestrator skill, 26 specialist workflows, 24 TOML agent...
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
Codex-first SEO analysis suite with 1 orchestrator skill, 26 specialist workflows, 24 TOML agent profiles, MCP/API extensions, deterministic headless runners, and premium audit report generation.
Codex SEO is a Codex-native port of AgriciDaniel/claude-seo, synchronized to upstream main at a9cf338 and adapted for Codex skills, Codex plugins, TOML agents, shared cache artifacts, and repeatable local/API execution.
It covers technical SEO, on-page analysis, content quality, E-E-A-T, schema markup, image optimization, sitemap architecture, Core Web Vitals, GEO/AEO for AI search, backlinks, local SEO, maps intelligence, Google APIs, semantic clustering, SXO, drift monitoring, e-commerce SEO, hreflang, FLOW prompts, DataForSEO, Firecrawl, and Gemini/nanobanana image workflows.
v1.9.6-codex.5.v1.9.6-codex.5.codex, codex-cli, codex-skills, seo, ai-seo, ai-search, technical-seo, generative-engine-optimization, core-web-vitals, schema-markup, local-seo, ecommerce-seo, content-strategy, google-search-console, dataforseo, mcp, python, automation, marketing-automation, open-source.curl -fsSL https://raw.githubusercontent.com/AgriciDaniel/codex-seo/v1.9.6-codex.5/install.sh | bash
Windows:
irm https://raw.githubusercontent.com/AgriciDaniel/codex-seo/v1.9.6-codex.5/install.ps1 | iex
git clone https://github.com/AgriciDaniel/codex-seo.git
cd codex-seo
bash install.sh
Windows:
git clone https://github.com/AgriciDaniel/codex-seo.git
cd codex-seo
powershell -ExecutionPolicy Bypass -File .\install.ps1
The installer copies the skill suite into ~/.codex/skills/, installs TOML agents into ~/.codex/agents/, creates a Python virtualenv at ~/.codex/skills/seo/.venv/, installs core runtime dependencies, attempts optional capability groups, and verifies the runtime.
CODEX_HOME=~/.codex \
CODEX_SEO_REPO=https://github.com/AgriciDaniel/codex-seo \
CODEX_SEO_REF=v1.9.6-codex.5 \
bash install.sh
| Variable | Purpose |
|---|---|
CODEX_HOME | Alternate Codex home. Defaults to ~/.codex. |
CODEX_SEO_REPO | Git URL, fork URL, or local repository path. |
CODEX_SEO_REF | Branch, tag, or commit. Defaults to v1.9.6-codex.5. |
CODEX_SEO_SKIP_PLAYWRIGHT_BROWSER=1 | Skip Chromium install for visual/PDF workflows. |
CODEX_SEO_PLAYWRIGHT_WITH_DEPS=1 | Ask Playwright to install system dependencies where supported. |
Restart Codex after installation. Then ask naturally; a /seo command is not required:
Do a full SEO check on https://example.com following best practices.
Review this page for schema, Core Web Vitals, image SEO, and AI search readiness.
Create an SEO strategy and content roadmap for a local dental clinic.
Command-style prompts also work:
/seo audit https://example.com
/seo technical https://example.com
/seo schema https://example.com
/seo dataforseo serp "best seo tools"
Codex SEO is designed as a Codex-first routing layer: the user can ask naturally, the orchestrator selects the right specialist workflow, and deterministic runners write repeatable artifacts instead of relying on invisible chat-only output.
%%{init: {"theme":"base","themeVariables":{"background":"#05080d","primaryColor":"#07131c","primaryTextColor":"#f5fbff","primaryBorderColor":"#00d7e6","lineColor":"#00d7e6","secondaryColor":"#06222a","tertiaryColor":"#ff9f1c","edgeLabelBackground":"#05080d","fontFamily":"Inter, ui-sans-serif, system-ui, sans-serif"}}}%%
flowchart LR
user["User prompt<br/>natural language or /seo"] --> orchestrator["skills/seo/SKILL.md<br/>main orchestrator"]
orchestrator --> cache[".seo-cache<br/>shared evidence"]
orchestrator --> skills["26 specialist<br/>SEO workflows"]
skills --> agents["24 TOML agents<br/>parallel analysis slices"]
skills --> scripts["scripts/<br/>deterministic runners"]
scripts --> output["output/<br/>Markdown, JSON, HTML, PDF"]
cache --> skills
class user,orchestrator accent
class cache,scripts data
class output output
classDef default fill:#07131c,stroke:#00d7e6,color:#f5fbff,stroke-width:1.4px
classDef accent fill:#10151a,stroke:#ff9f1c,color:#fff7ed,stroke-width:2px
classDef data fill:#06222a,stroke:#21e6c1,color:#ecfeff,stroke-width:1.5px
classDef output fill:#15101a,stroke:#ff9f1c,color:#fff7ed,stroke-width:1.8px
| Prompt | Purpose |
|---|---|
/seo audit <url> | Full site audit with specialist routing and premium report support |
/seo page <url> | Deep single-page SEO analysis |
/seo technical <url> | Crawlability, indexability, security, JavaScript, CWV |
/seo content <url> | E-E-A-T, helpfulness, readability, AI citation readiness |
/seo schema <url> | Structured data detection, validation, and JSON-LD generation |
/seo images <url> | Alt text, image weight, formats, metadata, image SERP opportunities |
/seo sitemap <url> | XML sitemap discovery, quality gates, generation guidance |
/seo geo <url> | AI Overviews, ChatGPT, Perplexity, llms.txt, citability |
/seo performance <url> | Core Web Vitals, Lighthouse-oriented performance signals |
/seo visual <url> | Screenshots, mobile rendering, above-the-fold analysis |
/seo plan <business-type> | Strategic SEO roadmap and content plan |
/seo programmatic <url> | Programmatic SEO risk and scale planning |
/seo competitor-pages <url> | Comparison and alternatives page opportunities |
/seo hreflang <url> | International SEO, locale validation, content parity |
/seo local <url> | Local SEO, GBP signals, NAP, citations, reviews |
/seo maps <command> | Geo-grid, GBP audit, review intelligence, local maps signals |
/seo google <command> | GSC, PageSpeed, CrUX, Indexing API, GA4 workflows |
/seo backlinks <url> | Backlink profile summary and source-tier detection |
/seo cluster <keyword> | SERP-based topic clustering and hub-spoke planning |
/seo sxo <url> | Search Experience Optimization, intent/page-type fit |
/seo drift baseline <url> | Capture an SEO baseline before changes |
/seo drift compare <url> | Compare current SEO signals against a baseline |
/seo ecommerce <url> | Product SEO, marketplace visibility, product schema |
/seo flow <stage> | FLOW framework prompts for Find, Leverage, Optimize, Win |
/seo dataforseo <command> | Live SERP, keyword, backlink, content, and AI visibility data |
/seo firecrawl <command> | JS-rendered crawling and site mapping via Firecrawl |
/seo image-gen <use-case> | OG images, hero images, product visuals, infographics |
Full command details live in docs/COMMANDS.md.
%%{init: {"theme":"base","themeVariables":{"background":"#05080d","primaryColor":"#07131c","primaryTextColor":"#f5fbff","primaryBorderColor":"#00d7e6","lineColor":"#00d7e6","secondaryColor":"#06222a","tertiaryColor":"#ff9f1c","edgeLabelBackground":"#05080d","fontFamily":"Inter, ui-sans-serif, system-ui, sans-serif"}}}%%
flowchart TD
request["Audit request"] --> detect["Detect site type<br/>business model and context"]
detect --> core["Core audit specialists"]
core --> technical["Technical"]
core --> content["Content"]
core --> schema["Schema"]
core --> sitemap["Sitemap"]
core --> geo["GEO / AI search"]
core --> images["Images"]
core --> performance["Performance"]
core --> visual["Visual"]
detect --> conditional["Conditional specialists"]
conditional --> local["Local / Maps"]
conditional --> backlinks["Backlinks"]
conditional --> google["Google APIs"]
conditional --> ecommerce["E-commerce"]
conditional --> drift["Drift"]
technical --> report["Unified SEO report"]
content --> report
schema --> report
sitemap --> report
geo --> report
images --> report
performance --> report
visual --> report
local --> report
backlinks --> report
google --> report
ecommerce --> report
drift --> report
report --> artifacts["SUMMARY.json<br/>FULL-AUDIT-REPORT.md<br/>ACTION-PLAN.md<br/>optional HTML/PDF"]
class request,detect accent
class core,conditional data
class report,artifacts output
classDef default fill:#07131c,stroke:#00d7e6,color:#f5fbff,stroke-width:1.4px
classDef accent fill:#10151a,stroke:#ff9f1c,color:#fff7ed,stroke-width:2px
classDef data fill:#06222a,stroke:#21e6c1,color:#ecfeff,stroke-width:1.5px
classDef output fill:#15101a,stroke:#ff9f1c,color:#fff7ed,stroke-width:1.8px
%%{init: {"theme":"base","themeVariables":{"background":"#05080d","primaryColor":"#07131c","primaryTextColor":"#f5fbff","primaryBorderColor":"#00d7e6","lineColor":"#00d7e6","actorBkg":"#07131c","actorBorder":"#00d7e6","actorTextColor":"#f5fbff","actorLineColor":"#21e6c1","signalColor":"#21e6c1","signalTextColor":"#f5fbff","labelBoxBkgColor":"#10151a","labelTextColor":"#f5fbff","noteBkgColor":"#10151a","noteTextColor":"#f5fbff","activationBkgColor":"#06222a","activationBorderColor":"#ff9f1c","fontFamily":"Inter, ui-sans-serif, system-ui, sans-serif"}}}%%
sequenceDiagram
participant Before as Baseline
participant Runner as Drift runner
participant After as Current page
participant Cache as .seo-cache
participant Report as Drift report
Before->>Runner: Capture titles, metas, canonicals, schema, headings
Runner->>Cache: Store baseline snapshot
After->>Runner: Re-check current SEO signals
Cache->>Runner: Load prior snapshot
Runner->>Report: Write changed, missing, and regressed signals
scripts/run_skill_workflow.py standardizes output for every user-invokable workflow.scripts/run_api_smoke_suite.py runs all supported workflows in one pass.| Extension | Skill | Setup | Notes |
|---|---|---|---|
| DataForSEO | seo-dataforseo, seo-maps, seo-ecommerce, seo-cluster | ./extensions/dataforseo/install.sh | Live SERP, keyword, backlinks, on-page, content, business data, AI visibility |
| Google APIs | seo-google, seo-performance | python scripts/google_auth.py --setup | PageSpeed, CrUX, GSC, URL Inspection, Indexing API, GA4 |
| Firecrawl | seo-firecrawl | ./extensions/firecrawl/install.sh | JS-rendered crawl, scrape, site map |
| Banana / Gemini | seo-image-gen | ./extensions/banana/install.sh | AI image generation through nanobanana-mcp |
Optional integrations enrich the same workflow surface. If credentials or MCP servers are missing, wrappers return setup_required or mcp_configured states with no fabricated live data.
%%{init: {"theme":"base","themeVariables":{"background":"#05080d","primaryColor":"#07131c","primaryTextColor":"#f5fbff","primaryBorderColor":"#00d7e6","lineColor":"#00d7e6","secondaryColor":"#06222a","tertiaryColor":"#ff9f1c","edgeLabelBackground":"#05080d","fontFamily":"Inter, ui-sans-serif, system-ui, sans-serif"}}}%%
flowchart LR
codex["Codex SEO workflows"] --> local["Local evidence<br/>HTML, robots, sitemaps, screenshots"]
codex --> dfs["DataForSEO MCP<br/>SERP, keywords, backlinks, maps"]
codex --> google["Google APIs<br/>GSC, PageSpeed, CrUX, GA4"]
codex --> firecrawl["Firecrawl MCP<br/>JS crawl and site maps"]
codex --> banana["Gemini / nanobanana<br/>SEO image assets"]
local --> artifacts["Reports and .seo-cache"]
dfs --> artifacts
google --> artifacts
firecrawl --> artifacts
banana --> artifacts
class codex accent
class local,dfs,google,firecrawl,banana data
class artifacts output
classDef default fill:#07131c,stroke:#00d7e6,color:#f5fbff,stroke-width:1.4px
classDef accent fill:#10151a,stroke:#ff9f1c,color:#fff7ed,stroke-width:2px
classDef data fill:#06222a,stroke:#21e6c1,color:#ecfeff,stroke-width:1.5px
classDef output fill:#15101a,stroke:#ff9f1c,color:#fff7ed,stroke-width:1.8px
Demo readiness:
python scripts/demo_readiness.py --target https://example.com --live-apis --workflows --json
One low-depth DataForSEO proof:
python scripts/demo_readiness.py --target https://example.com --live-apis --live-serp --serp-keyword "seo tools" --json
Run a single workflow:
python scripts/run_skill_workflow.py --skill seo-technical https://example.com --json
python scripts/run_skill_workflow.py --skill seo-google https://example.com --json
python scripts/run_skill_workflow.py --skill seo-dataforseo https://example.com --json
Run the full smoke suite:
python scripts/run_api_smoke_suite.py https://example.com --json
Verify environment:
python scripts/verify_environment.py --target https://example.com --json
Bootstrap a clean runtime:
python scripts/bootstrap_environment.py --venv .venv --json
Artifacts are written to output/. Shared project cache is written to .seo-cache/. Both are ignored by git.
%%{init: {"theme":"base","themeVariables":{"background":"#05080d","primaryColor":"#07131c","primaryTextColor":"#f5fbff","primaryBorderColor":"#00d7e6","lineColor":"#00d7e6","secondaryColor":"#06222a","tertiaryColor":"#ff9f1c","edgeLabelBackground":"#05080d","fontFamily":"Inter, ui-sans-serif, system-ui, sans-serif"}}}%%
flowchart LR
cli["run_skill_workflow.py<br/>single workflow"] --> json["JSON result"]
cli --> markdown["Markdown report"]
cli --> cacheWrite[".seo-cache update"]
suite["run_api_smoke_suite.py<br/>all workflows"] --> json
suite --> outputRoot["output/api-smoke-*"]
verify["verify_environment.py"] --> readiness["ready / setup_required<br/>capability status"]
markdown --> outputRoot
json --> outputRoot
cacheWrite --> cache[".seo-cache"]
class cli,suite,verify accent
class cacheWrite,readiness data
class json,markdown,outputRoot,cache output
classDef default fill:#07131c,stroke:#00d7e6,color:#f5fbff,stroke-width:1.4px
classDef accent fill:#10151a,stroke:#ff9f1c,color:#fff7ed,stroke-width:2px
classDef data fill:#06222a,stroke:#21e6c1,color:#ecfeff,stroke-width:1.5px
classDef output fill:#15101a,stroke:#ff9f1c,color:#fff7ed,stroke-width:1.8px
The repository separates Codex-facing instructions, deterministic runtime code, optional provider setup, and validation contracts. That keeps the skill system usable in chat, installable as a suite, and testable from CI/API workflows.
%%{init: {"theme":"base","themeVariables":{"background":"#05080d","primaryColor":"#07131c","primaryTextColor":"#f5fbff","primaryBorderColor":"#00d7e6","lineColor":"#00d7e6","secondaryColor":"#06222a","tertiaryColor":"#ff9f1c","edgeLabelBackground":"#05080d","fontFamily":"Inter, ui-sans-serif, system-ui, sans-serif"}}}%%
flowchart TB
manifest[".codex-plugin/plugin.json"] --> skillsRoot["skills/"]
skillsRoot --> orchestrator["seo/SKILL.md<br/>routing and orchestration"]
skillsRoot --> specialists["seo-*/SKILL.md<br/>specialist workflows"]
agentsDir["agents/seo-*.toml"] --> specialists
scriptsDir["scripts/<br/>deterministic runners"] --> specialists
extensionsDir["extensions/<br/>optional MCP setup"] --> specialists
references["skills/seo/references/<br/>thresholds and shared contracts"] --> specialists
specialists --> cacheDir[".seo-cache/<br/>cross-skill memory"]
specialists --> outputDir["output/<br/>reports and artifacts"]
testsDir["tests/<br/>contract and smoke coverage"] --> manifest
testsDir --> skillsRoot
testsDir --> scriptsDir
class manifest,orchestrator accent
class skillsRoot,specialists,agentsDir,scriptsDir,extensionsDir,references,testsDir data
class cacheDir,outputDir output
classDef default fill:#07131c,stroke:#00d7e6,color:#f5fbff,stroke-width:1.4px
classDef accent fill:#10151a,stroke:#ff9f1c,color:#fff7ed,stroke-width:2px
classDef data fill:#06222a,stroke:#21e6c1,color:#ecfeff,stroke-width:1.5px
classDef output fill:#15101a,stroke:#ff9f1c,color:#fff7ed,stroke-width:1.8px
codex-seo/
├── .codex-plugin/plugin.json # Codex plugin manifest
├── skills/
│ ├── seo/SKILL.md # Main orchestrator
│ └── seo-*/SKILL.md # 26 specialist workflows
├── agents/ # 24 Codex TOML agent profiles
├── scripts/ # Deterministic runners and API helpers
├── extensions/
│ ├── dataforseo/ # DataForSEO MCP setup and docs
│ ├── firecrawl/ # Firecrawl MCP setup and docs
│ └── banana/ # Gemini/nanobanana image generation setup
├── hooks/ # Quality-gate hooks
├── schema/ # Schema.org templates
├── docs/ # Architecture, commands, installation, MCP, demo
└── tests/ # Contract and workflow tests
Design principles:
skills/ is the source of truth.skills/seo/SKILL.md routes natural-language SEO requests.~/.config/codex-seo/ or ~/.codex/settings.json.claude-seo config/cache paths are read only as migration fallback.More detail: docs/ARCHITECTURE.md.
Local release gate:
python -m pytest tests/
bash -n install.sh uninstall.sh
python -m compileall -q scripts hooks
python scripts/run_api_smoke_suite.py https://example.com --json
PowerShell parse check:
$files = Get-ChildItem -Recurse -Filter *.ps1
foreach ($f in $files) {
$tokens = $null
$errs = $null
[System.Management.Automation.Language.Parser]::ParseFile($f.FullName, [ref]$tokens, [ref]$errs) > $null
if ($errs.Count) { $errs; exit 1 }
}
Current GitHub CI runs:
--help checks for runner scriptspython -m pytest tests/Codex SEO writes new local credentials and state to Codex-specific paths:
~/.codex/settings.json for MCP server configuration~/.config/codex-seo/ for API configs and cost ledgers~/.cache/codex-seo/ for runtime caches.seo-cache/ inside the active project for cross-skill summariesLegacy ~/.config/claude-seo/ and ~/.cache/claude-seo/ paths are read only as migration fallback. Do not commit .seo-cache/, output/, .mcp.json, .env, OAuth tokens, service accounts, or provider keys.
0600 file permissions.scripts/dataforseo_costs.py.bash uninstall.sh
Windows:
powershell -ExecutionPolicy Bypass -File .\uninstall.ps1
Use CONTRIBUTING.md for local setup and validation, CODE_OF_CONDUCT.md for project standards, SECURITY.md for vulnerability reporting, and CREDITS.md for project credits. Agent-facing project context is also available in llms.txt.
claude-seo - original Claude Code SEO skill suiteclaude-blog - blog creation and optimization skill ecosystemclaude-ads - paid advertising audit skill suiteflow - evidence-led SEO framework for AI searchwp-mcp-ultimate - WordPress MCP serverSpecial thanks to avalonreset for making the Codex conversion possible and for creating the initial Codex SEO version that this repository builds on.
Original project and concept by AgriciDaniel in claude-seo. This Codex port preserves upstream SEO capabilities and adapts the runtime for Codex skills, TOML agents, plugin discovery, cache sharing, MCP extension setup, and API-safe wrappers.
Codex SEO is released under the MIT License. FLOW prompt references retain their upstream attribution and licensing notices where included.
name: seo-sxo
description: >
Search Experience Optimization: reads Google SERPs backwards to detect page-type
mismatches, derives user stories from search intent signals, and scores pages
from multiple persona perspectives. Identifies why well-optimized pages fail
to rank by analyzing what Google rewards for each keyword. Use when user says
"SXO", "search experience", "page type mismatch", "SERP analysis", "user story",
"persona scoring", "why isn't my page ranking", "intent mismatch", or "wireframe".
user-invokable: true
argument-hint: "<url> [keyword]"
license: MIT
metadata:
author: AgriciDaniel
original_author: "Florian Schmitz (Pro Hub Challenge)"
version: "1.9.6"
category: seoStep 0 -- Check shared data cache:
Before gathering, check .seo-cache/ for reusable context from related SEO skills.
Reference: ../seo/references/shared-data-cache.md for schemas and dependency map.
Check these cache files when present:
.seo-cache/site-meta.json for domain, business type, industry, and crawl context
.seo-cache/audit-scores.json for prior full-audit priorities
.seo-cache/pages/{url-slug}/page-analysis.json for page-level context when a URL is provided
If found: parse and use clearly valid fields (note "Using cached [X] from [date]")
If missing, corrupt, or irrelevant: continue with fresh evidence
If the user says "refresh" or "re-run": ignore cache reads and overwrite on write
SXO bridges the gap between SEO (what Google rewards) and UX (what users need). Traditional SEO audits check technical health. SXO asks: "Does this page deserve to rank for this keyword based on what Google is actually rewarding in the SERP?"
A page can score 95/100 on technical SEO and still fail to rank because it is the wrong page type for the keyword. If Google shows 8 product pages and 2 comparison pages for your keyword, your blog post will never break through -- no matter how well-optimized it is.
| Command | Purpose |
|---|---|
/seo sxo <url> | Full SXO analysis (auto-detect keyword from page) |
/seo sxo <url> <keyword> | Full SXO analysis for a specific keyword |
/seo sxo wireframe <url> | Generate IST/SOLL wireframe with concrete placeholders |
/seo sxo personas <url> | Persona-only scoring (skip SERP analysis) |
scripts/fetch_page.py (SSRF-safe)scripts/parse_html.py to extract: title, H1, meta description,
headings hierarchy, word count, schema markup, CTAs, media elementsRead references/page-type-taxonomy.md for classification rules.
This is the core SXO insight. Compare target page type against SERP consensus.
Mismatch severity levels:
| Target Type | SERP Expects | Severity | Recommendation |
|---|---|---|---|
| Blog Post | Product Pages | CRITICAL | Create dedicated product page |
| Blog Post | Comparison | HIGH | Restructure as comparison with matrix |
| Product | Informational | HIGH | Add educational content layer |
| Landing Page | Tool/Calculator | HIGH | Build interactive tool component |
| Service Page | Local Results | MEDIUM | Add location signals + local schema |
| Any type match | - | ALIGNED | Focus on content depth and UX |
Classification rules:
references/page-type-taxonomy.mdRead references/user-story-framework.md for the full framework.
From SERP signals, derive user stories:
For each signal cluster, generate a user story:
As a [persona derived from signal],
I want to [goal derived from query intent],
because [emotional driver from ad copy / PAA tone],
but I'm blocked by [barrier derived from PAA questions / related searches].
Generate 3-5 user stories covering the primary intent angles.
Compare the target page against SERP expectations across 7 dimensions:
| Dimension | What to Compare | Score |
|---|---|---|
| Page Type | Target type vs SERP dominant type | 0-15 |
| Content Depth | Word count, heading depth, topic coverage | 0-15 |
| UX Signals | CTA clarity, above-fold content, mobile layout | 0-15 |
| Schema Markup | Present vs expected structured data types | 0-15 |
| Media Richness | Images, video, interactive elements vs SERP norm | 0-15 |
| Authority Signals | E-E-A-T markers, social proof, credentials | 0-15 |
| Freshness | Last updated, date signals, content recency | 0-10 |
Total: 0-100 SXO Gap Score (lower = larger gap, higher = better alignment)
Read references/persona-scoring.md for methodology.
Only execute when /seo sxo wireframe is invoked.
Read references/wireframe-templates.md for templates.
If DataForSEO MCP tools are available:
google_organic_serp for precise SERP data (positions, features, snippets)keyword_data for search volume and competition metricsThe SXO score is separate from the main SEO Health Score.
| Finding | Hand Off To |
|---|---|
| E-E-A-T gaps in persona scoring | /seo content for deep E-E-A-T audit |
| Missing schema types | /seo schema for generation |
| Local intent detected in SERP | /seo local for GBP analysis |
| Content depth gaps | /seo page for deep page analysis |
| Technical issues found during fetch | /seo technical for full audit |
| Image/media gaps | /seo images for optimization |
## SXO Analysis: [URL]
### Target Keyword: [keyword]
### 1. SERP Landscape
- Dominant page type: [type] ([confidence]% consensus)
- SERP features: [list]
- Content depth norm: [word count range]
- Schema expectation: [types]
### 2. Page-Type Alignment
- Your page type: [type]
- SERP expects: [type]
- Verdict: [ALIGNED | MISMATCH (severity)]
- Impact: [explanation]
### 3. User Stories (derived from SERP signals)
[3-5 user stories with source signals]
### 4. Gap Analysis (SXO Score: XX/100)
[7-dimension breakdown table]
### 5. Persona Scores
[4-7 persona cards with 4-dimension scores]
### 6. Priority Actions
[Ranked list: fix mismatch first, then weakest persona gaps]
### 7. Limitations
[What could not be assessed, data source notes]
| Error | Action |
|---|---|
| URL fetch fails | Report error, suggest checking URL accessibility |
| No keyword provided or detected | Ask user to provide target keyword |
| WebSearch returns <5 results | Proceed with available data, note limited sample |
| SERP has no organic results (all ads) | Note highly commercial SERP, analyze ad copy only |
| Target page is JavaScript-rendered | Note limitation, use available HTML content |
| DataForSEO cost exceeds threshold | Fall back to WebSearch, notify user |
Before delivering results, verify:
scripts/fetch_page.py (not raw curl/fetch)After completing all work, write a concise JSON summary to .seo-cache/ when the workflow produced durable findings.
Use the schemas and naming rules in ../seo/references/shared-data-cache.md; include at least cache_type, analyzed_at, source URL/domain, key findings, issues, recommendations, and tool limitations. Add .seo-cache/ to .gitignore if it is missing.
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