pascalandy/ContentAnalysis

ContentAnalysis

Content-adaptive wisdom extraction -- dynamic sections built from what the content actually contains, not static templates.

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Routing

Load references/ROUTER.md to determine which sub-skill handles this request.

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The Problem

Traditional content extraction follows a fixed template: IDEAS, QUOTES, HABITS, FACTS, REFERENCES. Every piece of content gets the same headers regardless of what it actually contains. A programming interview gets a "HABITS" section. A geopolitical analysis gets "FACTS" that are really just opinions. The output feels mechanical and misses the real gems because the sections were decided before the content was even read.

• Static sections miss domain-specific wisdom -- a security talk has threat model insights, not generic "ideas"
• Forced categories create padding -- filling a HABITS section when the content has none
• Uniform tone reads like a committee report -- compressed info nuggets instead of genuine observations
• No depth control -- the same exhaustive output whether you want a quick hit or a deep dive

The fundamental issue: the extraction format should serve the content, not the other way around.

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The Solution

ContentAnalysis detects what wisdom domains actually exist in the content and builds custom sections around them. A programming interview gets "Programming Philosophy" and "Developer Workflow Tips." A business podcast gets "Contrarian Business Takes" and "Money Philosophy." A security talk gets "Threat Model Insights" and "Defense Strategies."

Core capabilities:

1. Dynamic section detection -- Reads the content first, identifies wisdom domains, then builds sections around what is actually there
2. Five depth levels -- From Instant (one killer section) to Comprehensive (10-15 sections with themes and connections)
3. Conversational voice -- Bullets that sound like someone telling a friend about it, not a book report
4. Quality standards -- Every bullet earns its place; no padding, no inventory lists, no committee language
5. Closing sections -- One-Sentence Takeaway, If You Only Have 2 Minutes, References and Rabbit Holes (depth-dependent)

The sections adapt because the content dictates them.

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What's Included

| Component | Path | Purpose | |-----------|------|---------| | Skill router | references/ROUTER.md | Minimal routing table that dispatches requests to the right sub-skill | | ExtractWisdom skill | references/ExtractWisdom/MetaSkill.md | Dynamic content extraction methodology, tone rules, depth levels, quality standards | | Extract workflow | references/ExtractWisdom/workflows/Extract.md | Step-by-step extraction workflow |

Summary:

• Sub-skills: 1 (ExtractWisdom)
• Workflows: 1 (Extract)
• Dependencies: None (works standalone)

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What Makes This Different

This sounds similar to the original extract_wisdom which also pulls insights from content. The difference:

The original extract_wisdom uses static sections -- IDEAS, QUOTES, HABITS, FACTS, REFERENCES -- for every piece of content. ContentAnalysis reads the content first, figures out what wisdom domains are present, and builds sections around what it finds. A talk about AI agents gets "Self-Modifying Software" and "The Agent Spectrum" instead of generic IDEAS. The tone follows a conversational voice standard (Level 3) that produces bullets people actually want to read, not compressed information nuggets. Depth levels let you choose between a 30-second skim and a comprehensive deep dive.

• Dynamic sections adapted to each piece of content, not static templates
• Five depth levels from Instant to Comprehensive
• Conversational tone that reads like someone telling you about it
• Every bullet passes the "Would I tweet this?" test
• Section names read like magazine headlines, not category labels

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Invocation Scenarios

| Trigger | What Happens | |---------|--------------| | "extract wisdom from [URL]" | Routes to ExtractWisdom -- Full-depth extraction with 5-12 dynamic sections | | "analyze this video" | Routes to ExtractWisdom -- Content scan, section detection, extraction with closing sections | | "extract wisdom (fast)" | Routes to ExtractWisdom -- Fast-depth: 3 sections, 3 bullets each, no closing sections | | "extract wisdom at comprehensive level" | Routes to ExtractWisdom -- Maximum depth: 10-15 sections plus Themes and Connections | | "key takeaways from this podcast" | Routes to ExtractWisdom -- Full extraction with emphasis on actionable insights | | "what did I miss in this article" | Routes to ExtractWisdom -- Full extraction focused on non-obvious insights |

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Example Usage

Full Extraction (Default)

User: "extract wisdom from [YouTube URL about AI agents]"

AI responds:
# EXTRACT WISDOM: Building AI Agents That Actually Work
> A deep dive into agent engineering with [speaker] -- from self-modifying
> software to the economics of building with AI

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## The Death of 80% of Apps

- He wasn't trying to build self-modifying software. He just let the agent
  see its own source code and it started fixing itself.
- Most apps are just a UI on a database. Agents can generate those on the fly.
  The app store as we know it is already dead.
- ...

## Money Stops Mattering

- Past a certain point, money stops mattering. A cheeseburger is a cheeseburger
  no matter how rich you are.
- Every VC is offering hundreds of millions. He genuinely doesn't care.
- ...

[... more dynamic sections ...]

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## One-Sentence Takeaway

The best agents aren't programmed -- they're given access to their own source
code and a reason to improve.

## If You Only Have 2 Minutes

- Self-modifying software happened by accident, not design
- 80% of current apps will be replaced by agent-generated UIs
- ...

## References & Rabbit Holes

- **Claude Code** -- The agent framework he built everything on
- **MCP protocol** -- The tool integration layer that makes agents practical

Fast Extraction

User: "extract wisdom (fast) from this podcast episode"

AI responds:
# EXTRACT WISDOM: [Title]
> [One-line description]

## [Dynamic Section 1]
- [3 tight bullets]

## [Dynamic Section 2]
- [3 tight bullets]

## [Dynamic Section 3]
- [3 tight bullets]

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Configuration

No configuration required. The skill works out of the box with sensible defaults (Full depth level). All extraction uses built-in Level 3 conversational voice standards.

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Customization

Recommended Customization

No customization needed -- the skill adapts dynamically to each piece of content.

Optional Customization

| Customization | Where | Impact | |--------------|-------|--------| | Default depth level | Invoke with depth keyword | Changes from Full to another level per request | | Section preferences | Modify ExtractWisdom SKILL.md | Always-include or always-exclude section types |

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Credits

• Original concept: Daniel Miessler -- developed as the next generation of extract_wisdom within the PAI system
• Inspired by: The limitations of static content extraction templates

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Related Work

• Fabric extract_wisdom -- The original static-section content extractor that inspired this dynamic approach

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Changelog

1.0.0

• Initial release
• Dynamic section detection based on content analysis
• Five depth levels: Instant, Fast, Basic, Full, Comprehensive
• Level 3 conversational voice standard
• Closing sections: One-Sentence Takeaway, If You Only Have 2 Minutes, References and Rabbit Holes
• Comprehensive-level Themes and Connections synthesis