name: article-title-optimizer
description: This skill analyzes article content in-depth and generates optimized, marketable titles in the format 'Title: Subtitle' (10-12 words maximum). The skill should be used when users request title optimization, title generation, or title improvement for articles, blog posts, or written content. It generates 5 title candidates using proven formulas, evaluates them against success criteria (clickability, SEO, clarity, emotional impact, memorability, shareability), and replaces the article's title with the winning candidate.
Article Title Optimizer
Overview
This skill transforms article titles into marketable, attention-grabbing headlines that follow the <Title>: <Subtitle> format while maintaining accuracy and avoiding deception. The skill analyzes article content deeply, generates five diverse title candidates using proven copywriting formulas, evaluates each against weighted success criteria, and automatically replaces the original title with the optimal choice.
Workflow
Follow this sequential process to optimize article titles:
Step 1: Read and Analyze the Article
Read the article file provided by the user to understand:
- Core thesis or argument: What is the main point or claim?
- Key findings or insights: What are the most important takeaways?
- Primary audience: Who is this written for? (Technical experts, general public, professionals, etc.)
- Emotional tone: Is it serious, provocative, optimistic, cautionary, analytical?
- Main keywords: What terms are central to the topic and likely search queries?
- Article type: Technical/professional, general interest, news, opinion/commentary, how-to guide
Example analysis for a healthcare AI article:
- Core thesis: AI in radiology has transformative potential but faces serious challenges around bias, transparency, and equity
- Key findings: AI systems show bias against underserved populations, black-box nature creates trust issues, most benefits accrue to wealthy institutions
- Primary audience: Healthcare professionals, policymakers, tech-aware general readers
- Emotional tone: Serious, cautionary, balanced
- Main keywords: AI, radiology, bias, healthcare equity, transparency, trust
- Article type: Long-form analysis/commentary on emerging technology
Step 2: Research Title Best Practices
Before generating candidates, review references/title_best_practices.md which contains:
- Proven title formulas (question, how-to, problem-solution, contrarian, etc.)
- Success criteria and evaluation framework
- Common pitfalls to avoid
- Industry-specific considerations
- Before/after examples
If needed, use web search to research:
- Current trends in article title writing for the specific industry
- Successful titles in similar topic areas
- SEO best practices for the article's subject matter
- Audience preferences for the content type
Note: Research should inform title generation but titles must remain authentic to the article content.
Step 3: Generate 5 Title Candidates
Create five diverse title candidates using different formulas from the reference guide. Each title must:
- Follow the
<Title>: <Subtitle> format
- Be 10-12 words maximum (total for both parts)
- Accurately represent the article content
- Use different approaches/formulas to provide variety
- Avoid deception, clickbait, or misleading claims
CRITICAL CONSTRAINTS - All titles must comply:
- No AI-generated tropes: Avoid obvious AI writing patterns, especially "Algorithm/Algorithmic/Algorithms", "Black-Box/Black Box", and clichéd phrasing like "The X Will See You Now", "Welcome to the Age of X", "The Rise of X"
- No apostrophes: Do not use apostrophes anywhere in the title (not "don't", "can't", "it's", "AI's", etc.)
- No question marks in Title segment: Question marks create visually awkward ?: combinations when rendered. Questions may be used in the Subtitle segment only, or rephrase as statements.
Example candidates for healthcare AI article:
- Statement Format: "Medical AI and Trust: Why Bias Threatens Healthcare Equity"
- Problem-Solution Format: "Opaque AI in Healthcare: Why Explainability Matters Now"
- Contrarian Format: "AI Will Not Replace Radiologists: But Everything Changes"
- Impact Format: "When Medical AI Fails Minorities: The Data Representation Crisis"
- Examination Format: "Navigating Healthcare AI: Trust, Bias, and the Path Forward"
Step 4: Evaluate Each Candidate Against Success Criteria
Score each title candidate (1-10 scale) across six weighted criteria:
Clickability (25% weight): Attention-grabbing power, curiosity gap, use of power words
- High: Creates strong curiosity, specific and compelling
- Low: Generic, boring, or too vague
SEO Effectiveness (20% weight): Search optimization and discoverability
- Keyword placement in first 3-5 words
- Length 50-60 characters ideal
- Natural language, not keyword-stuffed
Clarity/Informativeness (20% weight): How well title communicates content
- High: Reader knows exactly what to expect
- Low: Vague, confusing, or misleading
Emotional Impact (15% weight): Emotional resonance and engagement
- Curiosity, surprise, urgency, relevance to reader concerns
Memorability (10% weight): Likelihood to stick in mind
- Distinctive phrasing, rhythmic flow, concrete language
Social Shareability (10% weight): Likelihood to be shared
- Identity expression, conversation starter, platform fit
Example evaluation for Candidate 1:
- Clickability: 8/10 (trust and bias angle creates curiosity)
- SEO: 8/10 (strong keywords "Medical AI", "Trust", "Bias" well-placed)
- Clarity: 9/10 (very clear what article covers)
- Emotional Impact: 7/10 (trust and equity concerns resonate)
- Memorability: 7/10 (clear and direct phrasing)
- Shareability: 8/10 (addresses question many people have about AI)
- Weighted Score: (8×0.25) + (8×0.20) + (9×0.20) + (7×0.15) + (7×0.10) + (8×0.10) = 8.05
Step 5: Analyze and Select the Winner
After scoring all five candidates:
Calculate weighted scores for each candidate
Identify top 2-3 performers based on quantitative scores
Apply qualitative judgment considering:
- Best fit for article tone and audience
- Authenticity to content
- No red flags (deception, offense, plagiarism)
- Overall "feel" when reading aloud
Select the winning title that:
- Has the highest overall score OR
- Scores highly and best represents the article's unique angle
- Passes all ethical/quality checks
Example selection rationale:
"After evaluation, Candidate 2 ('Opaque AI in Healthcare: Why Explainability Matters Now') scores highest with 8.3/10. It combines strong clickability (the 'Opaque' descriptor is clear and evocative), excellent clarity about the core issue, and solid SEO with well-placed keywords. While Candidate 1 scored well on clarity and Candidate 5 had good structure, Candidate 2 provides the best balance across all criteria. It avoids AI-generated tropes like 'Black-Box' or 'Algorithm', uses fresh language, and authentically represents the article without relying on clichéd phrasing."
Step 6: Replace the Title in the Article
Use the Edit tool to replace the article's current title and ensure that you:-
- Find and replace the first H1 heading in the markdown file
- Preserve all other content
- Confirm successful replacement
Step 7: Present Results to User
Provide the user with:
- The winning title and brief explanation of why it was chosen
- All five candidates with their scores (optional but recommended for transparency)
- Confirmation that the title has been replaced in the file
- Key insights from the evaluation (what made the winner stand out)
Example output format:
✓ Article title optimized successfully!
Winning Title (Score: 8.3/10):
"Opaque AI in Healthcare: Why Explainability Matters Now"
Why this title won:
- Highest overall score across all criteria
- Fresh "Opaque" descriptor avoids overused "Black-Box" trope
- Clear communication of article scope (AI + healthcare + transparency)
- Strong SEO with well-placed keywords
- Excellent balance of curiosity and clarity
- Avoids AI-generated tropes and clichéd phrasing
All candidates evaluated:
1. "Medical AI and Trust: Why Bias Threatens Healthcare Equity" (8.0/10)
2. "Opaque AI in Healthcare: Why Explainability Matters Now" (8.3/10) ← WINNER
3. "AI Will Not Replace Radiologists: But Everything Changes" (7.6/10)
4. "When Medical AI Fails Minorities: The Data Representation Crisis" (7.9/10)
5. "Navigating Healthcare AI: Trust, Bias, and the Path Forward" (7.7/10)
The title has been updated in: /path/to/article.md
Key Principles
Accuracy Over Attraction
While the goal is creating marketable titles, accuracy is non-negotiable:
- Never misrepresent article content
- Avoid clickbait or deceptive techniques
- Ensure promises in title are delivered in content
- Be specific, not vague
Format Compliance
All titles must follow <Title>: <Subtitle> structure with strict constraints:
- Title (main): Hook the reader, create curiosity
- Subtitle: Clarify, provide context, set expectations
- Total length: 10-12 words maximum
- Balance: Neither part should dominate excessively
Mandatory Constraints:
- No AI-generated tropes: Never use "Algorithm/Algorithmic/Algorithms", "Black-Box/Black Box", or clichéd AI-content phrasing like "The X Will See You Now", "Welcome to the Age of X", "The Rise of X", "X: A Game Changer"
- No apostrophes: Avoid contractions and possessives (use "do not" instead of "don't", "AI of the future" instead of "AI's future")
- No question marks in Title segment: Questions create awkward ?: visual combinations. Use questions only in Subtitle, or rephrase as statements
Diverse Candidate Generation
Generate candidates using different formulas to ensure variety:
- Question format (question must be in Subtitle segment only, or use statement form)
- How-to format
- Problem-solution format
- Contrarian/provocative format
- Future/trend format
- Emotional hook format
- Unexpected juxtaposition
Avoid generating five variations of the same approach. Remember: all candidates must comply with the three mandatory constraints (no AI tropes, no apostrophes, no question marks in Title segment).
Evidence-Based Selection
Base the winning title selection on:
- Quantitative scores across six weighted criteria
- Qualitative judgment about fit and authenticity
- Ethical checks for deception, offense, or plagiarism
- Alignment with article tone and target audience
Document the reasoning for transparency.
Common Scenarios
Scenario 1: Technical Article for Expert Audience
User request: "Optimize the title for this technical paper on neural network architectures"
Approach:
- Prioritize clarity and precision over clever wordplay
- Use correct technical terminology
- Emphasize novelty or practical benefit
- Example: "Transformer Attention Mechanisms: Scaling Efficiency in Large Models"
Scenario 2: General Interest Article
User request: "Make this article about climate change more engaging"
Approach:
- Avoid jargon, use accessible language
- Emphasize human impact and relevance
- Create emotional connection
- Example: "Why Your City Will Flood: Climate Change Comes Home"
Scenario 3: How-To Guide
User request: "Create a better title for this tutorial"
Approach:
- Use action-oriented language
- Make the benefit clear
- Be specific about what readers will learn
- Example: "Master API Testing: Build Robust Tests in 30 Minutes"
Scenario 4: Opinion/Commentary
User request: "This opinion piece needs a stronger title"
Approach:
- Signal the viewpoint clearly
- Be provocative within reason
- Create discussion-worthy angle
- Example: "The Silicon Valley AI Ethics Problem: Why Self-Regulation Failed"
Troubleshooting
Issue: All Candidates Score Very Similarly
Solution: Revisit generation step and create more diverse candidates using different formulas. Ensure variety in approach (question vs. statement, provocative vs. informative, etc.)
Issue: No Candidates Meet Quality Bar
Solution: Return to article analysis. May have misunderstood core thesis or audience. Re-read article sections and regenerate candidates based on deeper understanding.
Issue: User Rejects Winning Title
Solution: Ask for specific feedback about what doesn't work. Use that input to either:
- Select the second-place candidate if it addresses concerns
- Generate new candidates with adjusted focus
- Revise winning title while maintaining structure
Issue: Title Length Exceeds 12 Words
Solution: Edit for conciseness:
- Remove filler words (very, really, actually, etc.)
- Use more concise phrasing
- Combine or eliminate redundant concepts
- Ensure both title and subtitle are pulling weight
Resources
references/title_best_practices.md
Comprehensive guide containing:
- Proven title formulas with examples
- Detailed success criteria and evaluation framework
- Common pitfalls to avoid
- Industry-specific considerations
- Before/after transformation examples
When to reference: Always review this before generating candidates to ensure adherence to best practices and proper use of formulas.
1---2name: article-title-optimizer3description: This skill analyzes article content in-depth and generates optimized, marketable titles in the format 'Title: Subtitle' (10-12 words maximum). The skill should be used when users request title optimiz4---5
6---
7name: article-title-optimizer
8description: This skill analyzes article content in-depth and generates optimized, marketable titles in the format 'Title: Subtitle' (10-12 words maximum). The skill should be used when users request title optimization, title generation, or title improvement for articles, blog posts, or written content. It generates 5 title candidates using proven formulas, evaluates them against success criteria (clickability, SEO, clarity, emotional impact, memorability, shareability), and replaces the article's title with the winning candidate.
9---
10
11# Article Title Optimizer
12
13## Overview
14
15This skill transforms article titles into marketable, attention-grabbing headlines that follow the `<Title>: <Subtitle>` format while maintaining accuracy and avoiding deception. The skill analyzes article content deeply, generates five diverse title candidates using proven copywriting formulas, evaluates each against weighted success criteria, and automatically replaces the original title with the optimal choice.
16
17## Workflow
18
19Follow this sequential process to optimize article titles:
20
21### Step 1: Read and Analyze the Article
22
23Read the article file provided by the user to understand:
24- **Core thesis or argument**: What is the main point or claim?
25- **Key findings or insights**: What are the most important takeaways?
26- **Primary audience**: Who is this written for? (Technical experts, general public, professionals, etc.)
27- **Emotional tone**: Is it serious, provocative, optimistic, cautionary, analytical?
28- **Main keywords**: What terms are central to the topic and likely search queries?
29- **Article type**: Technical/professional, general interest, news, opinion/commentary, how-to guide
30
31**Example analysis for a healthcare AI article:**
32- Core thesis: AI in radiology has transformative potential but faces serious challenges around bias, transparency, and equity
33- Key findings: AI systems show bias against underserved populations, black-box nature creates trust issues, most benefits accrue to wealthy institutions
34- Primary audience: Healthcare professionals, policymakers, tech-aware general readers
35- Emotional tone: Serious, cautionary, balanced
36- Main keywords: AI, radiology, bias, healthcare equity, transparency, trust
37- Article type: Long-form analysis/commentary on emerging technology
38
39### Step 2: Research Title Best Practices
40
41Before generating candidates, review `references/title_best_practices.md` which contains:
42- Proven title formulas (question, how-to, problem-solution, contrarian, etc.)
43- Success criteria and evaluation framework
44- Common pitfalls to avoid
45- Industry-specific considerations
46- Before/after examples
47
48If needed, use web search to research:
49- Current trends in article title writing for the specific industry
50- Successful titles in similar topic areas
51- SEO best practices for the article's subject matter
52- Audience preferences for the content type
53
54**Note**: Research should inform title generation but titles must remain authentic to the article content.
55
56### Step 3: Generate 5 Title Candidates
57
58Create five diverse title candidates using different formulas from the reference guide. Each title must:
59- Follow the `<Title>: <Subtitle>` format
60- Be 10-12 words maximum (total for both parts)
61- Accurately represent the article content
62- Use different approaches/formulas to provide variety
63- Avoid deception, clickbait, or misleading claims
64
65**CRITICAL CONSTRAINTS - All titles must comply:**
661. **No AI-generated tropes**: Avoid obvious AI writing patterns, especially "Algorithm/Algorithmic/Algorithms", "Black-Box/Black Box", and clichéd phrasing like "The X Will See You Now", "Welcome to the Age of X", "The Rise of X"
672. **No apostrophes**: Do not use apostrophes anywhere in the title (not "don't", "can't", "it's", "AI's", etc.)
683. **No question marks in Title segment**: Question marks create visually awkward ?: combinations when rendered. Questions may be used in the Subtitle segment only, or rephrase as statements.
69
70**Example candidates for healthcare AI article:**
71
721. **Statement Format**: "Medical AI and Trust: Why Bias Threatens Healthcare Equity"
732. **Problem-Solution Format**: "Opaque AI in Healthcare: Why Explainability Matters Now"
743. **Contrarian Format**: "AI Will Not Replace Radiologists: But Everything Changes"
754. **Impact Format**: "When Medical AI Fails Minorities: The Data Representation Crisis"
765. **Examination Format**: "Navigating Healthcare AI: Trust, Bias, and the Path Forward"
77
78### Step 4: Evaluate Each Candidate Against Success Criteria
79
80Score each title candidate (1-10 scale) across six weighted criteria:
81
821. **Clickability (25% weight)**: Attention-grabbing power, curiosity gap, use of power words
83 - High: Creates strong curiosity, specific and compelling
84 - Low: Generic, boring, or too vague
85
862. **SEO Effectiveness (20% weight)**: Search optimization and discoverability
87 - Keyword placement in first 3-5 words
88 - Length 50-60 characters ideal
89 - Natural language, not keyword-stuffed
90
913. **Clarity/Informativeness (20% weight)**: How well title communicates content
92 - High: Reader knows exactly what to expect
93 - Low: Vague, confusing, or misleading
94
954. **Emotional Impact (15% weight)**: Emotional resonance and engagement
96 - Curiosity, surprise, urgency, relevance to reader concerns
97
985. **Memorability (10% weight)**: Likelihood to stick in mind
99 - Distinctive phrasing, rhythmic flow, concrete language
100
1016. **Social Shareability (10% weight)**: Likelihood to be shared
102 - Identity expression, conversation starter, platform fit
103
104**Example evaluation for Candidate 1:**
105- Clickability: 8/10 (trust and bias angle creates curiosity)
106- SEO: 8/10 (strong keywords "Medical AI", "Trust", "Bias" well-placed)
107- Clarity: 9/10 (very clear what article covers)
108- Emotional Impact: 7/10 (trust and equity concerns resonate)
109- Memorability: 7/10 (clear and direct phrasing)
110- Shareability: 8/10 (addresses question many people have about AI)
111- **Weighted Score**: (8×0.25) + (8×0.20) + (9×0.20) + (7×0.15) + (7×0.10) + (8×0.10) = **8.05**
112
113### Step 5: Analyze and Select the Winner
114
115After scoring all five candidates:
116
1171. **Calculate weighted scores** for each candidate
1182. **Identify top 2-3 performers** based on quantitative scores
1193. **Apply qualitative judgment** considering:
120 - Best fit for article tone and audience
121 - Authenticity to content
122 - No red flags (deception, offense, plagiarism)
123 - Overall "feel" when reading aloud
124
1254. **Select the winning title** that:
126 - Has the highest overall score OR
127 - Scores highly and best represents the article's unique angle
128 - Passes all ethical/quality checks
129
130**Example selection rationale:**
131"After evaluation, Candidate 2 ('Opaque AI in Healthcare: Why Explainability Matters Now') scores highest with 8.3/10. It combines strong clickability (the 'Opaque' descriptor is clear and evocative), excellent clarity about the core issue, and solid SEO with well-placed keywords. While Candidate 1 scored well on clarity and Candidate 5 had good structure, Candidate 2 provides the best balance across all criteria. It avoids AI-generated tropes like 'Black-Box' or 'Algorithm', uses fresh language, and authentically represents the article without relying on clichéd phrasing."
132
133### Step 6: Replace the Title in the Article
134
135Use the Edit tool to replace the article's current title and ensure that you:-
136- Find and replace the first H1 heading in the markdown file
137- Preserve all other content
138- Confirm successful replacement
139
140### Step 7: Present Results to User
141
142Provide the user with:
1431. **The winning title** and brief explanation of why it was chosen
1442. **All five candidates** with their scores (optional but recommended for transparency)
1453. **Confirmation** that the title has been replaced in the file
1464. **Key insights** from the evaluation (what made the winner stand out)
147
148**Example output format:**
149
150```
151✓ Article title optimized successfully!
152
153Winning Title (Score: 8.3/10):
154"Opaque AI in Healthcare: Why Explainability Matters Now"
155
156Why this title won:
157- Highest overall score across all criteria
158- Fresh "Opaque" descriptor avoids overused "Black-Box" trope
159- Clear communication of article scope (AI + healthcare + transparency)
160- Strong SEO with well-placed keywords
161- Excellent balance of curiosity and clarity
162- Avoids AI-generated tropes and clichéd phrasing
163
164All candidates evaluated:
1651. "Medical AI and Trust: Why Bias Threatens Healthcare Equity" (8.0/10)
1662. "Opaque AI in Healthcare: Why Explainability Matters Now" (8.3/10) ← WINNER
1673. "AI Will Not Replace Radiologists: But Everything Changes" (7.6/10)
1684. "When Medical AI Fails Minorities: The Data Representation Crisis" (7.9/10)
1695. "Navigating Healthcare AI: Trust, Bias, and the Path Forward" (7.7/10)
170
171The title has been updated in: /path/to/article.md
172```
173
174## Key Principles
175
176### Accuracy Over Attraction
177While the goal is creating marketable titles, accuracy is non-negotiable:
178- Never misrepresent article content
179- Avoid clickbait or deceptive techniques
180- Ensure promises in title are delivered in content
181- Be specific, not vague
182
183### Format Compliance
184All titles must follow `<Title>: <Subtitle>` structure with strict constraints:
185- **Title (main)**: Hook the reader, create curiosity
186- **Subtitle**: Clarify, provide context, set expectations
187- **Total length**: 10-12 words maximum
188- **Balance**: Neither part should dominate excessively
189
190**Mandatory Constraints:**
1911. **No AI-generated tropes**: Never use "Algorithm/Algorithmic/Algorithms", "Black-Box/Black Box", or clichéd AI-content phrasing like "The X Will See You Now", "Welcome to the Age of X", "The Rise of X", "X: A Game Changer"
1922. **No apostrophes**: Avoid contractions and possessives (use "do not" instead of "don't", "AI of the future" instead of "AI's future")
1933. **No question marks in Title segment**: Questions create awkward ?: visual combinations. Use questions only in Subtitle, or rephrase as statements
194
195### Diverse Candidate Generation
196Generate candidates using different formulas to ensure variety:
197- Question format (question must be in Subtitle segment only, or use statement form)
198- How-to format
199- Problem-solution format
200- Contrarian/provocative format
201- Future/trend format
202- Emotional hook format
203- Unexpected juxtaposition
204
205Avoid generating five variations of the same approach. Remember: all candidates must comply with the three mandatory constraints (no AI tropes, no apostrophes, no question marks in Title segment).
206
207### Evidence-Based Selection
208Base the winning title selection on:
209- **Quantitative scores** across six weighted criteria
210- **Qualitative judgment** about fit and authenticity
211- **Ethical checks** for deception, offense, or plagiarism
212- **Alignment** with article tone and target audience
213
214Document the reasoning for transparency.
215
216## Common Scenarios
217
218### Scenario 1: Technical Article for Expert Audience
219**User request**: "Optimize the title for this technical paper on neural network architectures"
220**Approach**:
221- Prioritize clarity and precision over clever wordplay
222- Use correct technical terminology
223- Emphasize novelty or practical benefit
224- Example: "Transformer Attention Mechanisms: Scaling Efficiency in Large Models"
225
226### Scenario 2: General Interest Article
227**User request**: "Make this article about climate change more engaging"
228**Approach**:
229- Avoid jargon, use accessible language
230- Emphasize human impact and relevance
231- Create emotional connection
232- Example: "Why Your City Will Flood: Climate Change Comes Home"
233
234### Scenario 3: How-To Guide
235**User request**: "Create a better title for this tutorial"
236**Approach**:
237- Use action-oriented language
238- Make the benefit clear
239- Be specific about what readers will learn
240- Example: "Master API Testing: Build Robust Tests in 30 Minutes"
241
242### Scenario 4: Opinion/Commentary
243**User request**: "This opinion piece needs a stronger title"
244**Approach**:
245- Signal the viewpoint clearly
246- Be provocative within reason
247- Create discussion-worthy angle
248- Example: "The Silicon Valley AI Ethics Problem: Why Self-Regulation Failed"
249
250## Troubleshooting
251
252### Issue: All Candidates Score Very Similarly
253**Solution**: Revisit generation step and create more diverse candidates using different formulas. Ensure variety in approach (question vs. statement, provocative vs. informative, etc.)
254
255### Issue: No Candidates Meet Quality Bar
256**Solution**: Return to article analysis. May have misunderstood core thesis or audience. Re-read article sections and regenerate candidates based on deeper understanding.
257
258### Issue: User Rejects Winning Title
259**Solution**: Ask for specific feedback about what doesn't work. Use that input to either:
260- Select the second-place candidate if it addresses concerns
261- Generate new candidates with adjusted focus
262- Revise winning title while maintaining structure
263
264### Issue: Title Length Exceeds 12 Words
265**Solution**: Edit for conciseness:
266- Remove filler words (very, really, actually, etc.)
267- Use more concise phrasing
268- Combine or eliminate redundant concepts
269- Ensure both title and subtitle are pulling weight
270
271## Resources
272
273### references/title_best_practices.md
274Comprehensive guide containing:
275- Proven title formulas with examples
276- Detailed success criteria and evaluation framework
277- Common pitfalls to avoid
278- Industry-specific considerations
279- Before/after transformation examples
280
281**When to reference**: Always review this before generating candidates to ensure adherence to best practices and proper use of formulas.