feat: v14.0.0 — 12 community-inspired skills, pm-writers profession, extend pm-cross/operations/engineering
New profession: Writers & Content Creators (pm-writers bundle, skills 156–160) - instagram-post-downloader: Downloads Instagram images/carousels as high-res files + PDF stitch - aeo-optimizer: Restructures articles for AI citation (AEO) — question H2s, answer capsules, trust signal audit - thumbnail-creator: Generates brand-aligned thumbnail candidates via Gemini API with computer vision eval - substack-notes-scraper: Scrapes Substack Notes engagement data to formatted .xlsx - notes-humanizer: Strips AI writing patterns across 3 phases; injects genuine human signals Extended pm-cross (+3 skills, skills 161–163): - sycophancy-challenger: Argues against your idea first, holds position under pushback - last-30-days-research: Multi-platform research (Reddit, X, web) with signal confidence scoring - notebooklm-connector: Automates NotebookLM from Claude Code via Chrome extension Extended pm-operations (+2 skills, skills 164–165): - email-triage: Reads Gmail and surfaces only actionable emails with priority + reply starters - morning-intelligence: 15-question interview → personalised master news brief prompt Extended pm-engineering (+2 skills, skills 166–167): - context-mode: Output filtering + session log for long Claude Code sessions - claude-superpowers: Plan→Isolate→Test→Double-review framework for Claude Code Updated: marketplace.json v14.0.0 (167 skills, 18 professions, 26 bundles) Updated: README.md — title, badges, What's New, All 167 Skills table, install list Credits: skills inspired by Frank & Diana Dovgopol, Gencay (LearnAIwithMe), Karen Spinner (Wondering About AI), Orel (TheIndiepreneur), Joel Salinas (Leadership in Change), Ilia Karelin (Prosper), Ashwin Francis (Cash&Cache), Nate Herk https://claude.ai/code/session_01E4bTUWxx4Zo5rsFpad5X5B
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Mohit Aggarwal
@@ -390,4 +390,142 @@ AEO does not replace SEO — it complements it. A well-structured article optimi
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---
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## Appendix: Answer Capsule Templates by Content Type
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Not all articles have the same kind of content. Use these capsule templates as starting points based on the section type.
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### "What is X?" sections (definition)
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```
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[X] is [concise category or type]. It [what it does or how it works] by [mechanism or method].
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[Why it exists or what problem it solves — 1 sentence.] [One concrete example or real-world application.]
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```
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Target: 55-70 words. Avoid starting with "X is a type of X" — give immediate signal.
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### "How do you do X?" sections (how-to)
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```
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To [achieve outcome], [do step A], then [do step B], then [do step C].
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[The most common mistake or prerequisite — 1 sentence.] [The expected result or timeframe.]
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```
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Target: 50-65 words. Use active verbs throughout. No links.
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### "Why does X matter?" sections (rationale)
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```
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[X] matters because [specific reason 1] and [specific reason 2].
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Without [X], [consequence — ideally quantified or concrete].
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[Who this is most important for, and under what conditions.]
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```
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Target: 55-75 words. Specifics outperform generalities here — name numbers when they exist.
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### "What are the benefits of X?" sections (list rationale)
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```
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The main benefits of [X] are [benefit 1], [benefit 2], and [benefit 3].
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[Benefit 1] means [specific outcome]. [Benefit 2] enables [specific use case].
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Together these make [X] valuable for [audience] who need [outcome].
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```
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Target: 60-80 words. Compress the list into prose — bullet lists inside capsules are less extractable.
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### "Which X should I choose?" sections (comparison/decision)
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```
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Choose [Option A] when [condition A]. Choose [Option B] when [condition B].
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The deciding factor is [key variable]. [One sentence on the most common mistake —
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picking based on the wrong criterion.]
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```
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Target: 50-70 words. Decision capsules are among the highest-cited by AI engines — they answer the user's actual next question.
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### "When should I X?" sections (timing/trigger)
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```
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[X] when [specific trigger condition], typically [timeframe or frequency].
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Early signs that it's time include [signal 1] and [signal 2].
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Waiting too long often results in [consequence].
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```
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Target: 45-65 words. Concise is especially important for timing capsules.
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---
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## Appendix: AEO Scoring Rubric — Detailed Criteria
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Use this when producing the before/after score. Each criterion has a maximum contribution to the /10 score.
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| Criterion | Max score | How to assess |
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| H2s as direct questions | 2 pts | 2 = all H2s are questions; 1 = majority; 0 = few or none |
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| Answer capsules present | 2 pts | 2 = every H2 section has a capsule; 1 = some sections; 0 = none |
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| Capsules within 50-80 words | 1 pt | 1 = all capsules in range; 0 = any over 80 or under 50 |
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| No links inside capsules | 1 pt | 1 = zero links in any capsule; 0 = any links present |
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| Paragraphs ≤3 sentences | 2 pts | 2 = all paragraphs compliant; 1 = majority; 0 = widespread violations |
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| Trust signals present | 2 pts | 2 = 3+ trust signal types; 1 = 1-2 types; 0 = none |
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**Score interpretation:**
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- 8-10: Strong AEO readiness — well-positioned for AI citation
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- 5-7: Partial — likely extracted occasionally but inconsistently
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- 0-4: Low readiness — AI engines will paraphrase at best, skip at worst
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A typical unoptimized article scores 2-4. A well-structured but unoptimized thought leadership piece might score 4-6. After this skill runs, target 8+.
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---
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## Appendix: How Different AI Engines Extract Content
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Understanding how each engine works helps explain the rules behind the skill.
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### ChatGPT (GPT-4 and later) / Bing
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Retrieval-augmented generation with Bing Search integration. When a user asks a question, Bing retrieves pages, then GPT extracts passages. It tends to extract the first plausible answer-shaped block it finds in the page — meaning the capsule directly under the H2 is almost always what gets quoted. It prefers prose over lists for citations (though it reads lists fine).
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**Implication:** Get the capsule under the question-format H2 right. The rest of the section body is bonus context.
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### Perplexity
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Explicitly designed for sourced Q&A. It retrieves 5-10 pages per query and extracts from all of them simultaneously. It shows citations with numbered footnotes. It strongly prefers content that is:
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- Clearly attributed (author name or publication byline visible)
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- Recently published or updated (freshness signal)
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- Structured around the question being asked (heading match)
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**Implication:** Trust signals (author, date) and heading-to-question matching are especially important for Perplexity. Capsules that include specific numbers or named frameworks are more likely to be footnoted.
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### Claude (Anthropic)
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Claude with web search capability (Claude.ai or API with tools) retrieves pages and synthesises across them. Claude prioritises self-contained, complete answers and tends to directly quote capsules that are within the 50-80 word range. Claude is less likely to quote incomplete paragraphs that trail off or rely on surrounding context.
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**Implication:** The self-contained requirement is especially important for Claude citation. If the capsule requires reading the surrounding sentences to make sense, Claude will paraphrase instead of quote.
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### Google Gemini (AI Overviews)
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Integrated into Google Search. Generates AI Overviews for informational queries. Extracts from indexed pages, with preference for pages that already rank well (so SEO and AEO reinforce each other here). Tends to extract bulleted lists and numbered steps for how-to content; extracts definition capsules for "what is" queries.
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**Implication:** For Gemini AI Overviews, structured how-to content with numbered steps in the capsule performs well. Definition capsules should include the category/type as the first word.
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---
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## Appendix: Content Types That Benefit Most from AEO
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Not all content benefits equally. Use this to set expectations with the user about where AEO investment pays off most.
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| Content type | AEO benefit | Reason |
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| Glossary or definition articles | Very high | AI engines are constantly answering "what is X?" queries |
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| How-to guides and tutorials | Very high | Step-by-step content is a primary retrieval target |
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| Comparison articles ("X vs Y") | High | Decision queries are common AI engine inputs |
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| FAQ pages | High | Already in question format — just needs capsule discipline |
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| Research roundups with original data | High | Named statistics are citation anchors |
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| Thought leadership / opinion pieces | Medium | Opinion is less extractable; add definition and how-to sections |
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| News and timely content | Medium | AI engines prefer evergreen; but breaking news gets citation bursts |
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| Case studies | Medium | Specific outcomes are extractable; company-specific context less so |
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| Creative writing / narrative | Low | Not structured for extraction; AEO rules don't apply |
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| Product pages / landing pages | Low | Conversion-focused pages are rarely cited by AI engines |
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---
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*Originally created by Gencay (LearnAIwithMe) — adapted and extended for this library.*
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