* 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>
428 lines
14 KiB
Python
Executable File
428 lines
14 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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conversion_audit.py — CRO audit for HTML pages
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Usage:
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python3 conversion_audit.py --file page.html
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python3 conversion_audit.py --url https://example.com
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python3 conversion_audit.py --json
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python3 conversion_audit.py # demo mode
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"""
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import argparse
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import json
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import re
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import sys
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import urllib.request
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from html.parser import HTMLParser
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# ---------------------------------------------------------------------------
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# HTML Parser
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# ---------------------------------------------------------------------------
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class CROParser(HTMLParser):
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def __init__(self):
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super().__init__()
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self._depth = 0
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self._above_fold_depth = 3 # approximate first screenful
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self._above_fold_elements = 0
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self._total_elements = 0
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self.buttons = [] # {"text": str, "position": int}
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self.links_as_cta = [] # a tags with CTA-like classes/text
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self.form_fields = 0
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self.forms = 0
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# Social proof
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self.testimonial_markers = 0
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self.logo_images = 0
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self.social_numbers = [] # "X customers", "X reviews", etc.
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# Trust signals
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self.ssl_mentions = 0
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self.guarantee_mentions = 0
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self.privacy_mentions = 0
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# Viewport meta
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self.viewport_meta = False
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# Tracking state
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self._in_body = False
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self._above_fold_done = False
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self._body_element_count = 0
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self._in_script = False
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self._in_style = False
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self._current_tag = None
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self._current_text = []
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self._element_position = 0 # rough position counter
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# Full text (for regex scans)
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self.full_text = []
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def handle_starttag(self, tag, attrs):
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attrs_dict = dict(attrs)
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tag_lower = tag.lower()
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if tag_lower == "script":
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self._in_script = True
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return
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if tag_lower == "style":
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self._in_style = True
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return
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if tag_lower == "body":
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self._in_body = True
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return
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if tag_lower == "meta":
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if attrs_dict.get("name", "").lower() == "viewport":
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self.viewport_meta = True
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if not self._in_body:
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return
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self._element_position += 1
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# Buttons
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if tag_lower == "button":
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self._current_tag = "button"
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self._current_text = []
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elif tag_lower == "input":
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input_type = attrs_dict.get("type", "text").lower()
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if input_type == "submit":
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val = attrs_dict.get("value", "Submit")
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self.buttons.append({"text": val, "position": self._element_position})
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elif input_type not in ("hidden", "submit"):
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self.form_fields += 1
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elif tag_lower == "textarea" or tag_lower == "select":
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self.form_fields += 1
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elif tag_lower == "form":
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self.forms += 1
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elif tag_lower == "a":
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cls = attrs_dict.get("class", "").lower()
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href = attrs_dict.get("href", "")
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cta_classes = {"btn", "button", "cta", "call-to-action", "signup", "register"}
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if any(c in cls for c in cta_classes):
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self._current_tag = "a_cta"
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self._current_text = []
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elif tag_lower == "img":
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src = attrs_dict.get("src", "").lower()
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alt = attrs_dict.get("alt", "").lower()
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cls = attrs_dict.get("class", "").lower()
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if any(kw in src or kw in alt or kw in cls
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for kw in ("logo", "partner", "client", "badge", "seal", "award", "cert")):
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self.logo_images += 1
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def handle_endtag(self, tag):
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tag_lower = tag.lower()
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if tag_lower == "script":
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self._in_script = False
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elif tag_lower == "style":
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self._in_style = False
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elif tag_lower == "button" and self._current_tag == "button":
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text = " ".join(self._current_text).strip()
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self.buttons.append({"text": text, "position": self._element_position})
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self._current_tag = None
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self._current_text = []
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elif tag_lower == "a" and self._current_tag == "a_cta":
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text = " ".join(self._current_text).strip()
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self.links_as_cta.append({"text": text, "position": self._element_position})
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self._current_tag = None
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self._current_text = []
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def handle_data(self, data):
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if self._in_script or self._in_style:
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return
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text = data.strip()
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if not text:
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return
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if self._current_tag in ("button", "a_cta"):
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self._current_text.append(text)
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if self._in_body:
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self.full_text.append(text)
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# ---------------------------------------------------------------------------
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# Text-based signal detection
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# ---------------------------------------------------------------------------
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TESTIMONIAL_PATTERNS = [
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r'\b(testimonial|review|quote|said|says|told us|customer story)\b',
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r'[""][^""]{20,}[""]', # quoted text
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r'\b\d[\d,]+ (reviews?|customers?|users?|clients?|companies)\b',
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r'\bstar[s]?\b.{0,10}\b(rating|review)\b',
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r'\b(trustpilot|g2|capterra|clutch)\b',
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]
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TRUST_PATTERNS = {
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"ssl": [r'\b(ssl|https|secure|encrypted|tls|256.bit)\b'],
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"guarantee": [r'\b(guarantee|guaranteed|money.back|refund|risk.free|no.risk)\b'],
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"privacy": [r'\b(privacy|gdpr|data protection|we never share|no spam|unsubscribe)\b'],
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}
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CTA_TEXT_PATTERNS = [
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r'\b(get started|sign up|try free|start free|buy now|order now|get access|'
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r'download|schedule|book|claim|join|subscribe|register|contact us|learn more|'
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r'get quote|request demo|start trial|get demo)\b',
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]
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def scan_text_signals(full_text: str) -> dict:
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text_lower = full_text.lower()
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testimonials = sum(
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len(re.findall(p, text_lower, re.IGNORECASE))
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for p in TESTIMONIAL_PATTERNS
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)
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trust = {}
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for key, patterns in TRUST_PATTERNS.items():
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trust[key] = sum(len(re.findall(p, text_lower, re.IGNORECASE)) for p in patterns)
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cta_text_count = sum(
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len(re.findall(p, text_lower, re.IGNORECASE))
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for p in CTA_TEXT_PATTERNS
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)
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return {
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"testimonial_signals": min(testimonials, 20),
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"trust": trust,
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"cta_text_count": cta_text_count,
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}
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# ---------------------------------------------------------------------------
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# Scoring
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# ---------------------------------------------------------------------------
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def score_category(value, thresholds: list) -> int:
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"""thresholds: [(min_value, score), ...] sorted asc. Returns score for first match."""
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for min_val, score in sorted(thresholds, reverse=True):
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if value >= min_val:
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return score
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return 0
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def audit(html: str) -> dict:
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parser = CROParser()
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parser.feed(html)
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full_text = " ".join(parser.full_text)
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text_signals = scan_text_signals(full_text)
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all_ctas = parser.buttons + parser.links_as_cta
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total_cta_count = len(all_ctas) + text_signals["cta_text_count"]
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# --- CTA ---
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cta_score = score_category(total_cta_count, [(0, 0), (1, 50), (2, 75), (3, 90), (5, 100)])
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cta_above_fold = len([c for c in all_ctas if c["position"] <= 5])
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if cta_above_fold >= 1:
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cta_score = min(100, cta_score + 10)
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# --- Forms ---
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if parser.forms == 0:
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form_score = 60 # not all pages need forms
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form_note = "No form detected (OK if not a lead gen page)"
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elif parser.form_fields <= 3:
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form_score = 100
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form_note = f"{parser.form_fields} field(s) — minimal friction"
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elif parser.form_fields <= 5:
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form_score = 70
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form_note = f"{parser.form_fields} field(s) — consider trimming"
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else:
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form_score = max(10, 100 - (parser.form_fields - 3) * 10)
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form_note = f"{parser.form_fields} field(s) — too many, high friction"
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# --- Social proof ---
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social_signals = text_signals["testimonial_signals"] + parser.logo_images
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social_score = score_category(social_signals, [(0, 0), (1, 40), (2, 65), (4, 85), (6, 100)])
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# --- Trust signals ---
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trust = text_signals["trust"]
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trust_total = sum(min(1, v) for v in trust.values()) # 0-3
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trust_score = score_category(trust_total, [(0, 20), (1, 60), (2, 80), (3, 100)])
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# --- Viewport meta ---
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viewport_score = 100 if parser.viewport_meta else 0
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# --- Overall ---
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weights = {
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"cta": 0.30,
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"social_proof": 0.25,
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"trust_signals": 0.20,
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"forms": 0.15,
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"viewport_mobile": 0.10,
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}
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scores = {
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"cta": cta_score,
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"social_proof": social_score,
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"trust_signals": trust_score,
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"forms": form_score,
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"viewport_mobile": viewport_score,
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}
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overall = round(sum(scores[k] * weights[k] for k in weights))
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return {
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"overall_score": overall,
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"categories": {
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"cta_buttons": {
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"score": cta_score,
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"button_count": len(parser.buttons),
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"cta_link_count": len(parser.links_as_cta),
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"cta_text_count": text_signals["cta_text_count"],
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"above_fold_ctas": cta_above_fold,
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"weight": "30%",
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},
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"social_proof": {
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"score": social_score,
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"testimonial_signals": text_signals["testimonial_signals"],
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"logo_badge_images": parser.logo_images,
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"total_signals": social_signals,
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"weight": "25%",
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},
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"trust_signals": {
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"score": trust_score,
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"ssl_mentions": trust["ssl"],
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"guarantee_mentions": trust["guarantee"],
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"privacy_mentions": trust["privacy"],
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"weight": "20%",
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},
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"forms": {
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"score": form_score,
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"form_count": parser.forms,
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"field_count": parser.form_fields,
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"note": form_note,
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"weight": "15%",
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},
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"viewport_mobile": {
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"score": viewport_score,
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"viewport_meta_present": parser.viewport_meta,
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"weight": "10%",
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},
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},
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}
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# ---------------------------------------------------------------------------
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# Demo HTML
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# ---------------------------------------------------------------------------
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DEMO_HTML = """<!DOCTYPE html>
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<html>
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Get Your Free Marketing Audit</title>
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</head>
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<body>
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<header>
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<img src="logo.png" alt="Acme Corp logo" class="logo">
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<a href="#form" class="btn cta">Get Free Audit</a>
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</header>
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<section class="hero">
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<h1>Stop Wasting Your Ad Budget</h1>
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<p>Join 12,400 marketers who cut wasted spend by 35% in 30 days.</p>
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<button>Start Free Trial</button>
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</section>
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<section class="social-proof">
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<h2>What Our Customers Say</h2>
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<blockquote>"This tool saved us $50,000 in the first quarter." — Sarah M., CMO</blockquote>
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<blockquote>"Best investment we made in 2023." — James T., Head of Growth</blockquote>
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<p>Rated 4.9/5 on G2 with 2,400+ reviews</p>
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<p>Trusted by 500+ companies worldwide</p>
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<img src="google-partner.png" alt="Google Partner badge" class="badge">
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<img src="trustpilot.png" alt="Trustpilot certified" class="badge">
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</section>
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<section id="form">
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<h2>Get Your Free Audit</h2>
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<form>
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<input type="text" name="name" placeholder="Your name">
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<input type="email" name="email" placeholder="Work email">
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<button type="submit">Get My Free Audit</button>
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</form>
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<p>🔒 SSL secured. We never share your data. Unsubscribe anytime.</p>
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<p>30-day money-back guarantee. No risk.</p>
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|
</section>
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|
</body>
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|
</html>"""
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|
|
|
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|
# ---------------------------------------------------------------------------
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# Main
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def main():
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parser = argparse.ArgumentParser(
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|
description="CRO audit — analyzes an HTML page for conversion signals."
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|
)
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parser.add_argument("--file", help="Path to HTML file")
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|
parser.add_argument("--url", help="URL to fetch and analyze")
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|
parser.add_argument("--json", action="store_true", help="Output as JSON")
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|
args = parser.parse_args()
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|
|
|
if args.file:
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|
with open(args.file, "r", encoding="utf-8", errors="replace") as f:
|
|
html = f.read()
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|
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")
|
|
|
|
result = audit(html)
|
|
|
|
if args.json:
|
|
print(json.dumps(result, indent=2))
|
|
return
|
|
|
|
cats = result["categories"]
|
|
overall = result["overall_score"]
|
|
|
|
print("=" * 62)
|
|
print(f" CRO AUDIT RESULTS Overall Score: {overall}/100")
|
|
print("=" * 62)
|
|
|
|
rows = [
|
|
("CTA Buttons", "cta_buttons"),
|
|
("Social Proof", "social_proof"),
|
|
("Trust Signals", "trust_signals"),
|
|
("Forms", "forms"),
|
|
("Mobile Viewport", "viewport_mobile"),
|
|
]
|
|
|
|
for label, key in rows:
|
|
c = cats[key]
|
|
score = c["score"]
|
|
weight = c["weight"]
|
|
bar_len = round(score / 10)
|
|
bar = "█" * bar_len + "░" * (10 - bar_len)
|
|
icon = "✅" if score >= 70 else ("⚠️ " if score >= 40 else "❌")
|
|
print(f" {icon} {label:<18} [{bar}] {score:>3}/100 (weight {weight})")
|
|
|
|
print()
|
|
# Detail callouts
|
|
cta = cats["cta_buttons"]
|
|
print(f" CTAs: {cta['button_count']} buttons, {cta['cta_link_count']} CTA links, "
|
|
f"{cta['cta_text_count']} CTA text phrases, {cta['above_fold_ctas']} above fold")
|
|
|
|
sp = cats["social_proof"]
|
|
print(f" Social Proof: {sp['testimonial_signals']} testimonial signals, "
|
|
f"{sp['logo_badge_images']} logos/badges")
|
|
|
|
ts = cats["trust_signals"]
|
|
print(f" Trust: SSL({ts['ssl_mentions']}) Guarantee({ts['guarantee_mentions']}) "
|
|
f"Privacy({ts['privacy_mentions']})")
|
|
|
|
fm = cats["forms"]
|
|
print(f" Forms: {fm['form_count']} form(s), {fm['field_count']} field(s) — {fm['note']}")
|
|
|
|
print()
|
|
grade = "A" if overall >= 85 else "B" if overall >= 70 else "C" if overall >= 55 else "D" if overall >= 40 else "F"
|
|
print("=" * 62)
|
|
print(f" Grade: {grade} Score: {overall}/100")
|
|
print("=" * 62)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|