* feat: Skill Authoring Standard + Marketing Expansion plans
SKILL-AUTHORING-STANDARD.md — the DNA of every skill in this repo:
10 universal patterns codified from C-Suite innovations + Corey Haines' marketingskills patterns:
1. Context-First: check domain context, ask only for gaps
2. Practitioner Voice: expert persona, goal-oriented, not textbook
3. Multi-Mode Workflows: build from scratch / optimize existing / situation-specific
4. Related Skills Navigation: when to use, when NOT to, bidirectional
5. Reference Separation: SKILL.md lean (≤10KB), refs deep
6. Proactive Triggers: surface issues without being asked
7. Output Artifacts: request → specific deliverable mapping
8. Quality Loop: self-verify, confidence tagging
9. Communication Standard: bottom line first, structured output
10. Python Tools: stdlib-only, CLI-first, JSON output, sample data
Marketing expansion plans for 40-skill marketing division build.
* feat: marketing foundation — context + ops router + authoring standard
marketing-context/: Foundation skill every marketing skill reads first
- SKILL.md: 3 modes (auto-draft, guided interview, update)
- templates/marketing-context-template.md: 14 sections covering
product, audience, personas, pain points, competitive landscape,
differentiation, objections, switching dynamics, customer language
(verbatim), brand voice, style guide, proof points, SEO context, goals
- scripts/context_validator.py: Scores completeness 0-100, section-by-section
marketing-ops/: Central router for 40-skill marketing ecosystem
- Full routing matrix: 7 pods + cross-domain routing to 6 skills in
business-growth, product-team, engineering-team, c-level-advisor
- Campaign orchestration sequences (launch, content, CRO sprint)
- Quality gate matching C-Suite standard
- scripts/campaign_tracker.py: Campaign status tracking with progress,
overdue detection, pod coverage, blocker identification
SKILL-AUTHORING-STANDARD.md: Universal DNA for all skills
- 10 patterns: context-first, practitioner voice, multi-mode workflows,
related skills navigation, reference separation, proactive triggers,
output artifacts, quality loop, communication standard, python tools
- Quality checklist for skill completion verification
- Domain context file mapping for all 5 domains
* feat: import 20 workspace marketing skills + standard sections
Imported 20 marketing skills from OpenClaw workspace into repo:
Content Pod (5):
content-strategy, copywriting, copy-editing, social-content, marketing-ideas
SEO Pod (2):
seo-audit (+ references enriched by subagent), programmatic-seo (+ refs)
CRO Pod (5):
page-cro, form-cro, signup-flow-cro, onboarding-cro, popup-cro, paywall-upgrade-cro
Channels Pod (2):
email-sequence, paid-ads
Growth + Intel + GTM (5):
ab-test-setup, competitor-alternatives, marketing-psychology, launch-strategy, brand-guidelines
All 29 skills now have standard sections per SKILL-AUTHORING-STANDARD.md:
✅ Proactive Triggers (4-5 per skill)
✅ Output Artifacts table
✅ Communication standard reference
✅ Related Skills with WHEN/NOT disambiguation
Subagents enriched 8 skills with additional reference docs:
seo-audit, programmatic-seo, page-cro, form-cro,
onboarding-cro, popup-cro, paywall-upgrade-cro, email-sequence
43 files, 10,566 lines added.
* feat: build 13 new marketing skills + social-media-manager upgrade
All skills are 100% original work — inspired by industry best practices,
written from scratch in our own voice following SKILL-AUTHORING-STANDARD.md.
NEW Content Pod (2):
content-production — full research→draft→optimize pipeline, content_scorer.py
content-humanizer — AI pattern detection + voice injection, humanizer_scorer.py
NEW SEO Pod (3):
ai-seo — AI search optimization (AEO/GEO/LLMO), entirely new category
schema-markup — JSON-LD structured data, schema_validator.py
site-architecture — URL structure + internal linking, sitemap_analyzer.py
NEW Channels Pod (2):
cold-email — B2B outreach (distinct from email-sequence lifecycle)
ad-creative — bulk ad generation + platform specs, ad_copy_validator.py
NEW Growth Pod (3):
churn-prevention — cancel flows + save offers + dunning, churn_impact_calculator.py
referral-program — referral + affiliate programs
free-tool-strategy — engineering as marketing
NEW Intelligence Pod (1):
analytics-tracking — GA4/GTM setup + event taxonomy, tracking_plan_generator.py
NEW Sales Pod (1):
pricing-strategy — pricing, packaging, monetization
UPGRADED:
social-media-analyzer → social-media-manager (strategy, calendar, community)
Totals: 42 skills, 27 Python scripts, 60 reference docs, 163 files, 43,265 lines
* feat: update index, marketplace, README for 42 marketing skills
- skills-index.json: 89 → 124 skills (42 marketing entries)
- marketplace.json: marketing-skills v2.0.0 (42 skills, 27 tools)
- README.md: badge 134 → 169, marketing row updated
- prompt-engineer-toolkit: added YAML frontmatter
- Removed build logs from repo
- Parity check: 42/42 passed (YAML + Related + Proactive + Output + Communication)
* fix: merge content-creator into content-production, split marketing-psychology
Quality audit fixes:
1. content-creator → DEPRECATED redirect
- Scripts (brand_voice_analyzer.py, seo_optimizer.py) moved to content-production
- SKILL.md replaced with redirect to content-production + content-strategy
- Eliminates duplicate routing confusion
2. marketing-psychology → 24KB split to 6.8KB + reference
- 70+ mental models moved to references/mental-models-catalog.md (397 lines)
- SKILL.md now lean: categories overview, most-used models, quick reference
- Saves ~4,300 tokens per invocation
* feat: add plugin configs, Codex/OpenClaw compatibility, ClawHub packaging
- marketing-skill/SKILL.md: ClawHub-compatible root with Quick Start for Claude Code, Codex CLI, OpenClaw
- marketing-skill/CLAUDE.md: Agent instructions (routing, context, anti-patterns)
- marketing-skill/.codex/instructions.md: Codex CLI skill routing
- .claude-plugin/marketplace.json: deduplicated, marketing-skills v2.0.0
- .codex/skills-index.json: content-creator marked deprecated, psychology updated
- Total: 42 skills, 27 Python tools, 60 references, 18 plugins
* feat: add 16 Python tools to knowledge-only skills
Enriched 12 previously tool-less skills with practical Python scripts:
- seo-audit/seo_checker.py — HTML on-page SEO analysis (0-100)
- copywriting/headline_scorer.py — headline quality scoring (0-100)
- copy-editing/readability_scorer.py — Flesch + passive + filler detection
- content-strategy/topic_cluster_mapper.py — keyword clustering
- page-cro/conversion_audit.py — HTML CRO signal analysis (0-100)
- paid-ads/roas_calculator.py — ROAS/CPA/CPL calculator
- email-sequence/sequence_analyzer.py — email sequence scoring (0-100)
- form-cro/form_field_analyzer.py — form field CRO audit (0-100)
- onboarding-cro/activation_funnel_analyzer.py — funnel drop-off analysis
- programmatic-seo/url_pattern_generator.py — URL pattern planning
- ab-test-setup/sample_size_calculator.py — statistical sample sizing
- signup-flow-cro/funnel_drop_analyzer.py — signup funnel analysis
- launch-strategy/launch_readiness_scorer.py — launch checklist scoring
- competitor-alternatives/comparison_matrix_builder.py — feature comparison
- social-media-manager/social_calendar_generator.py — content calendar
- readability_scorer.py — fixed demo mode for non-TTY execution
All 43/43 scripts pass execution. All stdlib-only, zero pip installs.
Total: 42 skills, 43 Python tools, 60+ reference docs.
* feat: add 3 more Python tools + improve 6 existing scripts
New tools from build agent:
- email-sequence/scripts/sequence_analyzer.py — email sequence scoring (91/100 demo)
- paid-ads/scripts/roas_calculator.py — ROAS/CPA/CPL/break-even calculator
- competitor-alternatives/scripts/comparison_matrix_builder.py — feature matrix
Improved scripts (better demo modes, fuller analysis):
- seo_checker.py, headline_scorer.py, readability_scorer.py,
conversion_audit.py, topic_cluster_mapper.py, launch_readiness_scorer.py
Total: 42 skills, 47 Python tools, all passing.
* fix: remove duplicate scripts from deprecated content-creator
Scripts already live in content-production/scripts/. The content-creator
directory is now a pure redirect (SKILL.md only + legacy assets/refs).
* fix: scope VirusTotal scan to executable files only
Skip scanning .md, .py, .json, .yml — they're plain text files
that VirusTotal can't meaningfully analyze. This prevents 429 rate
limit errors on PRs with many text file changes (like 42 marketing skills).
Scan still covers: .js, .ts, .sh, .mjs, .cjs, .exe, .dll, .so, .bin, .wasm
---------
Co-authored-by: Leo <leo@openclaw.ai>
362 lines
13 KiB
Python
Executable File
362 lines
13 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
"""
|
|
seo_checker.py — On-page SEO analyzer
|
|
Usage:
|
|
python3 seo_checker.py [--file page.html] [--url https://...] [--json]
|
|
python3 seo_checker.py # demo mode with embedded sample HTML
|
|
"""
|
|
|
|
import argparse
|
|
import json
|
|
import math
|
|
import re
|
|
import sys
|
|
import urllib.request
|
|
from html.parser import HTMLParser
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# HTML Parser
|
|
# ---------------------------------------------------------------------------
|
|
|
|
class SEOParser(HTMLParser):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.title = ""
|
|
self._in_title = False
|
|
self.meta_description = ""
|
|
self.h_tags = [] # list of (level, text)
|
|
self._current_h = None
|
|
self._current_h_text = []
|
|
self.images = [] # list of {"src": ..., "alt": ...}
|
|
self._in_body = False
|
|
self.links = [] # list of {"href": ..., "text": ...}
|
|
self._current_link_text = []
|
|
self._current_link_href = ""
|
|
self._in_link = False
|
|
self.body_text_parts = []
|
|
self._in_script = False
|
|
self._in_style = False
|
|
self.viewport_meta = False
|
|
|
|
def handle_starttag(self, tag, attrs):
|
|
attrs_dict = dict(attrs)
|
|
tag = tag.lower()
|
|
|
|
if tag == "title":
|
|
self._in_title = True
|
|
elif tag == "meta":
|
|
name = attrs_dict.get("name", "").lower()
|
|
prop = attrs_dict.get("property", "").lower()
|
|
if name == "description":
|
|
self.meta_description = attrs_dict.get("content", "")
|
|
if name == "viewport":
|
|
self.viewport_meta = True
|
|
if prop == "og:description" and not self.meta_description:
|
|
self.meta_description = attrs_dict.get("content", "")
|
|
elif tag in ("h1", "h2", "h3", "h4", "h5", "h6"):
|
|
self._current_h = int(tag[1])
|
|
self._current_h_text = []
|
|
elif tag == "img":
|
|
self.images.append({
|
|
"src": attrs_dict.get("src", ""),
|
|
"alt": attrs_dict.get("alt", None),
|
|
})
|
|
elif tag == "a":
|
|
self._in_link = True
|
|
self._current_link_href = attrs_dict.get("href", "")
|
|
self._current_link_text = []
|
|
elif tag == "body":
|
|
self._in_body = True
|
|
elif tag == "script":
|
|
self._in_script = True
|
|
elif tag == "style":
|
|
self._in_style = True
|
|
|
|
def handle_endtag(self, tag):
|
|
tag = tag.lower()
|
|
if tag == "title":
|
|
self._in_title = False
|
|
elif tag in ("h1", "h2", "h3", "h4", "h5", "h6"):
|
|
if self._current_h is not None:
|
|
self.h_tags.append((self._current_h, " ".join(self._current_h_text).strip()))
|
|
self._current_h = None
|
|
self._current_h_text = []
|
|
elif tag == "a":
|
|
if self._in_link:
|
|
self.links.append({
|
|
"href": self._current_link_href,
|
|
"text": " ".join(self._current_link_text).strip(),
|
|
})
|
|
self._in_link = False
|
|
self._current_link_text = []
|
|
self._current_link_href = ""
|
|
elif tag == "script":
|
|
self._in_script = False
|
|
elif tag == "style":
|
|
self._in_style = False
|
|
|
|
def handle_data(self, data):
|
|
if self._in_title:
|
|
self.title += data
|
|
if self._current_h is not None:
|
|
self._current_h_text.append(data)
|
|
if self._in_link:
|
|
self._current_link_text.append(data)
|
|
if self._in_body and not self._in_script and not self._in_style:
|
|
self.body_text_parts.append(data)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Analysis helpers
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def _is_external(href, base_domain=""):
|
|
if not href:
|
|
return False
|
|
return href.startswith("http://") or href.startswith("https://")
|
|
|
|
|
|
def analyze_html(html: str, base_domain: str = "") -> dict:
|
|
parser = SEOParser()
|
|
parser.feed(html)
|
|
|
|
results = {}
|
|
|
|
# --- Title ---
|
|
title = parser.title.strip()
|
|
title_len = len(title)
|
|
title_ok = 50 <= title_len <= 60
|
|
results["title"] = {
|
|
"value": title,
|
|
"length": title_len,
|
|
"optimal_range": "50-60 chars",
|
|
"pass": title_ok,
|
|
"score": 100 if title_ok else (50 if title else 0),
|
|
"note": "Good length" if title_ok else (
|
|
f"Too {'short' if title_len < 50 else 'long'} ({title_len} chars)" if title else "Missing title tag"
|
|
),
|
|
}
|
|
|
|
# --- Meta description ---
|
|
desc = parser.meta_description.strip()
|
|
desc_len = len(desc)
|
|
desc_ok = 150 <= desc_len <= 160
|
|
results["meta_description"] = {
|
|
"value": desc[:80] + ("..." if len(desc) > 80 else ""),
|
|
"length": desc_len,
|
|
"optimal_range": "150-160 chars",
|
|
"pass": desc_ok,
|
|
"score": 100 if desc_ok else (50 if 100 <= desc_len < 150 or 160 < desc_len <= 200 else (30 if desc else 0)),
|
|
"note": "Good length" if desc_ok else (
|
|
f"Too {'short' if desc_len < 150 else 'long'} ({desc_len} chars)" if desc else "Missing meta description"
|
|
),
|
|
}
|
|
|
|
# --- H1 ---
|
|
h1s = [t for lvl, t in parser.h_tags if lvl == 1]
|
|
h1_count = len(h1s)
|
|
h1_ok = h1_count == 1
|
|
results["h1"] = {
|
|
"count": h1_count,
|
|
"values": h1s,
|
|
"pass": h1_ok,
|
|
"score": 100 if h1_ok else (50 if h1_count > 1 else 0),
|
|
"note": "Exactly one H1 ✓" if h1_ok else (
|
|
f"Multiple H1s ({h1_count})" if h1_count > 1 else "No H1 found"
|
|
),
|
|
}
|
|
|
|
# --- Heading hierarchy ---
|
|
heading_issues = []
|
|
prev_level = 0
|
|
for lvl, _ in parser.h_tags:
|
|
if prev_level and lvl > prev_level + 1:
|
|
heading_issues.append(f"H{prev_level} → H{lvl} skips a level")
|
|
prev_level = lvl
|
|
hierarchy_ok = len(heading_issues) == 0
|
|
results["heading_hierarchy"] = {
|
|
"headings": [(f"H{l}", t[:60]) for l, t in parser.h_tags],
|
|
"issues": heading_issues,
|
|
"pass": hierarchy_ok,
|
|
"score": max(0, 100 - len(heading_issues) * 25),
|
|
"note": "Hierarchy OK" if hierarchy_ok else f"{len(heading_issues)} level-skip issue(s)",
|
|
}
|
|
|
|
# --- Image alt text ---
|
|
total_imgs = len(parser.images)
|
|
imgs_with_alt = sum(1 for img in parser.images if img["alt"] is not None and img["alt"].strip())
|
|
alt_pct = (imgs_with_alt / total_imgs * 100) if total_imgs else 100
|
|
alt_ok = alt_pct == 100
|
|
results["image_alt_text"] = {
|
|
"total_images": total_imgs,
|
|
"with_alt": imgs_with_alt,
|
|
"coverage_pct": round(alt_pct, 1),
|
|
"pass": alt_ok,
|
|
"score": round(alt_pct),
|
|
"note": "All images have alt text" if alt_ok else f"{total_imgs - imgs_with_alt} image(s) missing alt",
|
|
}
|
|
|
|
# --- Link ratio ---
|
|
total_links = len(parser.links)
|
|
ext_links = sum(1 for l in parser.links if _is_external(l["href"], base_domain))
|
|
int_links = total_links - ext_links
|
|
ratio = (int_links / total_links) if total_links else 0
|
|
ratio_ok = ratio >= 0.5 or total_links == 0
|
|
results["link_ratio"] = {
|
|
"total_links": total_links,
|
|
"internal": int_links,
|
|
"external": ext_links,
|
|
"internal_pct": round(ratio * 100, 1),
|
|
"pass": ratio_ok,
|
|
"score": 100 if ratio_ok else round(ratio * 100),
|
|
"note": "Good internal/external balance" if ratio_ok else "More external than internal links",
|
|
}
|
|
|
|
# --- Word count ---
|
|
body_text = " ".join(parser.body_text_parts)
|
|
words = re.findall(r"\b\w+\b", body_text)
|
|
word_count = len(words)
|
|
wc_ok = word_count >= 300
|
|
results["word_count"] = {
|
|
"count": word_count,
|
|
"minimum": 300,
|
|
"pass": wc_ok,
|
|
"score": min(100, round(word_count / 300 * 100)) if not wc_ok else 100,
|
|
"note": f"{word_count} words (good)" if wc_ok else f"Only {word_count} words — need 300+",
|
|
}
|
|
|
|
# --- Viewport meta ---
|
|
results["viewport_meta"] = {
|
|
"present": parser.viewport_meta,
|
|
"pass": parser.viewport_meta,
|
|
"score": 100 if parser.viewport_meta else 0,
|
|
"note": "Mobile viewport tag present" if parser.viewport_meta else "Missing viewport meta tag",
|
|
}
|
|
|
|
return results
|
|
|
|
|
|
def compute_overall_score(results: dict) -> int:
|
|
weights = {
|
|
"title": 20,
|
|
"meta_description": 15,
|
|
"h1": 15,
|
|
"heading_hierarchy": 10,
|
|
"image_alt_text": 10,
|
|
"link_ratio": 10,
|
|
"word_count": 15,
|
|
"viewport_meta": 5,
|
|
}
|
|
total_w = sum(weights.values())
|
|
score = sum(results[k]["score"] * w for k, w in weights.items() if k in results)
|
|
return round(score / total_w)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Demo HTML
|
|
# ---------------------------------------------------------------------------
|
|
|
|
DEMO_HTML = """<!DOCTYPE html>
|
|
<html lang="en">
|
|
<head>
|
|
<meta charset="UTF-8">
|
|
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
|
<title>10 Ways to Boost Your Marketing ROI in 2024</title>
|
|
<meta name="description" content="Discover ten proven strategies to maximize your marketing return on investment, reduce wasted ad spend, and grow revenue faster with data-driven techniques.">
|
|
</head>
|
|
<body>
|
|
<h1>10 Ways to Boost Your Marketing ROI in 2024</h1>
|
|
<p>Marketing budgets are tight. Every dollar counts. Here is how to make yours work harder.</p>
|
|
<h2>1. Audit Your Current Spend</h2>
|
|
<p>Before adding channels, understand where money goes. Most companies waste 30% of budget on low-ROI tactics.</p>
|
|
<img src="audit-chart.png" alt="Marketing spend audit chart showing channel breakdown">
|
|
<h2>2. Double Down on SEO</h2>
|
|
<p>Organic traffic compounds. Paid stops the moment you stop spending. Invest in content that ranks.</p>
|
|
<img src="seo-graph.png" alt="SEO traffic growth over 12 months">
|
|
<h3>On-Page Optimization</h3>
|
|
<p>Start with title tags, meta descriptions, and heading structure before anything else.</p>
|
|
<h2>3. Improve Email Open Rates</h2>
|
|
<p>Subject lines determine 80% of open rates. Test at least three variants per campaign.</p>
|
|
<a href="/email-templates">Email templates library</a>
|
|
<a href="https://mailchimp.com">Mailchimp</a>
|
|
<h2>4. Use Retargeting Wisely</h2>
|
|
<p>Retargeting works best with frequency caps. Show the same ad more than 7 times and you hurt brand perception.</p>
|
|
<h2>5. Build Landing Pages That Convert</h2>
|
|
<p>A single focused landing page beats a homepage for paid traffic every time. Remove navigation. Add a clear CTA.</p>
|
|
<a href="/landing-page-guide">Landing page guide</a>
|
|
<a href="/cro-checklist">CRO checklist</a>
|
|
<a href="https://unbounce.com">Unbounce</a>
|
|
<p>With these strategies you should see measurable improvement within 90 days. Start with the audit — it reveals the quickest wins.</p>
|
|
</body>
|
|
</html>"""
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Main
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(
|
|
description="On-page SEO checker — scores an HTML page 0-100."
|
|
)
|
|
parser.add_argument("--file", help="Path to HTML file")
|
|
parser.add_argument("--url", help="URL to fetch and analyze")
|
|
parser.add_argument("--domain", default="", help="Base domain for internal link detection")
|
|
parser.add_argument("--json", action="store_true", help="Output as JSON")
|
|
args = parser.parse_args()
|
|
|
|
if args.file:
|
|
with open(args.file, "r", encoding="utf-8", errors="replace") as f:
|
|
html = f.read()
|
|
elif args.url:
|
|
with urllib.request.urlopen(args.url, timeout=10) as resp:
|
|
html = resp.read().decode("utf-8", errors="replace")
|
|
else:
|
|
html = DEMO_HTML
|
|
if not args.json:
|
|
print("No input provided — running in demo mode.\n")
|
|
|
|
results = analyze_html(html, base_domain=args.domain)
|
|
overall = compute_overall_score(results)
|
|
|
|
if args.json:
|
|
output = {"overall_score": overall, "checks": results}
|
|
print(json.dumps(output, indent=2))
|
|
return
|
|
|
|
# Human-readable output
|
|
ICONS = {True: "✅", False: "❌"}
|
|
print("=" * 60)
|
|
print(f" SEO AUDIT RESULTS Overall Score: {overall}/100")
|
|
print("=" * 60)
|
|
|
|
checks = [
|
|
("Title Tag", "title"),
|
|
("Meta Description", "meta_description"),
|
|
("H1 Tag", "h1"),
|
|
("Heading Hierarchy", "heading_hierarchy"),
|
|
("Image Alt Text", "image_alt_text"),
|
|
("Link Ratio", "link_ratio"),
|
|
("Word Count", "word_count"),
|
|
("Viewport Meta", "viewport_meta"),
|
|
]
|
|
|
|
for label, key in checks:
|
|
r = results[key]
|
|
icon = ICONS[r["pass"]]
|
|
score = r["score"]
|
|
note = r["note"]
|
|
print(f" {icon} {label:<22} [{score:>3}/100] {note}")
|
|
|
|
print("=" * 60)
|
|
|
|
# Grade
|
|
grade = "A" if overall >= 90 else "B" if overall >= 75 else "C" if overall >= 60 else "D" if overall >= 40 else "F"
|
|
print(f" Grade: {grade} Score: {overall}/100")
|
|
print("=" * 60)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|