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SKILL verified MIT Self-run

Pyramid Principle

skill-stefan-jansen-claude-code-toolkit-pyramid-principle · by stefan-jansen

Hierarchical content structure - answer first, then supporting arguments, then details

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$ agentstack add skill-stefan-jansen-claude-code-toolkit-pyramid-principle

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

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✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Pyramid Principle Skill

Foundation: Barbara Minto's pyramid principle for clear, logical communication

Core Concept: Start with the answer, then provide supporting arguments, then add details.

Why This Works:

  • Reader gets main point immediately (respects their time)
  • Supporting structure makes logical sense
  • Details are contextualized (not lost)
  • Reader can stop at any level and still understand core idea
  • Reduces cognitive load (top-down, not bottom-up)

The Pyramid Structure

                  [ANSWER / Core Message]
                           |
        ┌──────────────────┼──────────────────┐
        |                  |                  |
   [Argument 1]      [Argument 2]      [Argument 3]
        |                  |                  |
    ┌───┼───┐          ┌───┼───┐          ┌───┼───┐
    |   |   |          |   |   |          |   |   |
  [Details] [Details] [Details] [Details] [Details] [Details]

Levels:

  1. Level 1: The answer/conclusion (what they need to know)
  2. Level 2: Major supporting arguments (why answer is true)
  3. Level 3: Evidence and examples (what proves arguments)
  4. Level 4: Details and elaboration (depth as needed)

Core Rules

Rule 1: Answer First

Always start with the conclusion

Don't do this (bottom-up):

We analyzed 10 frameworks. We tested each for 6 months.
We measured productivity, reliability, and ease of use.
Framework X performed best. Therefore, we recommend Framework X.

Do this (top-down):

**We recommend Framework X** because it delivers 30% higher productivity
with proven reliability over 6 months of testing.

Here's why:
1. Productivity: 30% improvement vs alternatives
2. Reliability: Zero critical failures in production
3. Ease of adoption: 2-week learning curve vs 2-month for alternatives

Why: Reader knows the answer immediately. Supporting details provide confidence, but aren't prerequisite to understanding recommendation.

Rule 2: Group Related Ideas

Ideas in each group must be:

  • Related to each other (same category)
  • Support the idea above them
  • At same level of abstraction

Good grouping:

Core Message: "CAF transforms Claude Code into domain-specific agents"
├─ Argument 1: Customization spectrum (out-of-box → CAF → SDK)
├─ Argument 2: Domain transformation examples
└─ Argument 3: Proven patterns and constraints

Bad grouping (mixed levels):

Core Message: "CAF transforms Claude Code into domain-specific agents"
├─ Argument 1: Customization spectrum
├─ Argument 2: File-based persistence (this is a detail, not major argument)
└─ Argument 3: Stefan uses it for ML4T book (this is an example, not argument)

Rule 3: Logical Order

Arguments must follow logical sequence:

Structural order: Parts of something

  • Example: "Framework has 3 components: commands, agents, skills"

Chronological order: Time sequence

  • Example: "Workflow: positioning → research → outline → draft → review"

Comparative order: Ranking or comparison

  • Example: "Benefits ranked: reliability > productivity > ease"

Problem-solution order: Issue then resolution

  • Example: "Problem: Generic AI agents fail. Solution: Domain-specific customization."

Application to Content Types

Application 1: Outlines (Architect Agent)

Structure:

# Outline

## Opening (Level 1: Answer)
- Hook (grab attention)
- Core message (the answer)
- Preview (what's coming)

## Body (Level 2: Arguments)
### Argument 1: [First supporting point]
- Evidence (Level 3)
- Examples (Level 3)
- Details (Level 4)

### Argument 2: [Second supporting point]
- Evidence (Level 3)
- Examples (Level 3)
- Details (Level 4)

### Argument 3: [Third supporting point]
- Evidence (Level 3)
- Examples (Level 3)
- Details (Level 4)

## Closing (Level 1: Reinforce Answer)
- Restate core message
- Call to action

Example for CAF white paper:

Opening: "Transform Claude Code into specialized domain agents"
├─ Argument 1: Customization spectrum (out-of-box → CAF → SDK)
│  ├─ Evidence: What each level provides
│  ├─ Example: Content management workflow
│  └─ Details: When to use each level
├─ Argument 2: Domain transformation mechanism
│  ├─ Evidence: How markdown customization works
│  ├─ Example: Commands, agents, skills
│  └─ Details: Technical architecture
└─ Argument 3: Proven patterns and constraints
   ├─ Evidence: 6 months production use
   ├─ Example: Specific patterns
   └─ Details: How constraints prevent failure
Closing: Reinforce transformation message + CTA

Application 2: Business Communication

Memo structure:

Subject: Recommendation

**Recommendation**: [The answer - one sentence]

**Rationale**: [3-5 supporting arguments]
1. Argument 1
2. Argument 2
3. Argument 3

**Details**: [Evidence for each argument]
[Expand on arguments with data, examples, elaboration]

Why this works: Executive reads first line, gets answer, decides if they need to read more.

Application 3: Technical Explanations

Explain "What is CAF?":

Bottom-up (reader lost):

Claude Code has plugins. Plugins have commands. Commands invoke agents.
Agents use skills. Skills provide patterns. Patterns create frameworks.
Therefore, CAF is a meta-framework for domain-specific agent customization.

Top-down (pyramid):

**CAF transforms Claude Code into domain-specific agents through markdown-based customization.**

How it works:
1. Commands: Encapsulate domain workflows
2. Agents: Provide specialized capabilities
3. Skills: Define behavior patterns

Why it matters:
- Transforms generic AI into domain-expert
- Uses simple markdown (no coding required)
- Proven patterns prevent common failures

Reader benefit: Understands "what it is" immediately, can drill into details if interested.


Common Mistakes

Mistake 1: Burying the Lede

Don't hide the answer:

We conducted extensive research. We analyzed frameworks.
We tested implementations. We gathered feedback.
After 6 months, we discovered that...

Answer first:

**CAF prevents AI chaos through stateless, file-based architecture.**

Evidence from 6 months testing:
- Zero state corruption failures
- 100% reproducible results
- Context preserved across sessions

Mistake 2: Mixed Abstraction Levels

Arguments at different levels:

1. Customization spectrum (high-level concept)
2. File-based persistence (implementation detail)
3. Domain transformation (high-level concept)

Same level:

1. Customization spectrum (what CAF provides)
2. Domain transformation (how it works)
3. Proven patterns (why it's reliable)

Mistake 3: Illogical Order

Random order:

1. Benefits
2. How it works
3. What it is

Logical order:

1. What it is (establish understanding)
2. How it works (explain mechanism)
3. Benefits (show value)

Mistake 4: No Hierarchy

Flat list:

- Point 1
- Point 2
- Point 3
- Point 4
- Point 5
(All at same level, no structure)

Hierarchical:

Core Message
├─ Major Point 1
│  ├─ Supporting detail
│  └─ Example
├─ Major Point 2
│  ├─ Supporting detail
│  └─ Example
└─ Major Point 3
   ├─ Supporting detail
   └─ Example

Quality Checklist

When applying pyramid principle, verify:

  • [ ] Answer/conclusion stated first (Level 1)
  • [ ] 3-5 major supporting arguments identified (Level 2)
  • [ ] Each argument supports answer above it
  • [ ] Evidence/examples provided for arguments (Level 3)
  • [ ] Details elaborated as needed (Level 4)
  • [ ] Arguments grouped logically (related ideas together)
  • [ ] Arguments ordered logically (structural/chronological/comparative/problem-solution)
  • [ ] Each level is at consistent abstraction level
  • [ ] Reader can stop at any level and still understand core idea
  • [ ] No "burying the lede" (answer hidden at end)

Integration with Other Skills

Pyramid + excellent-writing:

  • Pyramid: What structure to use
  • excellent-writing: How to write clearly within that structure

Pyramid + SCQA:

  • Pyramid: Overall hierarchical structure
  • SCQA: How to structure narrative within pyramid (especially opening)

Pyramid + positioning-first:

  • Positioning: What the core message is (Level 1 of pyramid)
  • Pyramid: How to structure arguments supporting that message

References

Foundation: Barbara Minto, "The Pyramid Principle: Logic in Writing and Thinking"

Key insight: "Any intelligent reader can absorb only one thought at a time, and will automatically assume that any sentence that follows a previous one is intended to explain that thought further."

Application: Therefore, organize content to match how readers naturally process information - top-down, hierarchical, answer-first.


Skill Version: 1.0 Created: 2025-10-31 Used by: architect agent (outlines), author agent (optional) Key Innovation: Answer-first hierarchical structure that respects reader's cognitive load

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.