feat(examples): add content-generator example demonstrating Prompt Dependency Resolution

This example demonstrates the full workflow of generating InfoTech primers
using MarkiTect's Prompt Dependency Resolution infrastructure.

Features demonstrated:
- Artifact creation and storage with content-based addressing
- PromptTemplate with @{macro} resolution across multiple spaces
- Automatic dependency tracking and graph construction
- Provenance tracing from outputs back to inputs
- Visualization export (Mermaid format)
- Incremental execution with change detection

Files added:
- generate_primers.py: Complete working example
- README.md: Quick start guide and architecture overview
- TUTORIAL.md: Comprehensive 500+ line tutorial
- templates/generate-primer.md: Template with macros
- artifacts/topics/: ETL and Microservices topic definitions
- artifacts/guidelines/: Authoring rules and research protocol
- prepdr/: Original manual system (preserved for reference)

Example output:
- Generates 2 primers (ETL, Microservices)
- Creates 8 artifacts across 4 information spaces
- Records 8 dependency edges in SQLite database
- Exports dependency graph visualization

Run with: cd examples/content-generator && python generate_primers.py

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

examples/content-generator/prepdr/AuthoringRules.md

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+AuthoringRules
+
+*How to write effective primers*
+
+## Primer Authoring Rules
+
+**Status:** Draft
+**Intended Audience:** Human authors and AI systems generating or validating primers
+**Purpose:** Ensure primers are precise, stable, and suitable as shared context for humans and AI agents
+
+---
+
+## 1. What a Primer Is (Normative)
+
+An **InfoTechPrimer** is a **short, structured reference document** that establishes a **shared understanding** of a specific IT term, standard, method, or concept.
+
+A primer:
+
+* Defines **what the topic is**
+* Explains **where it fits**
+* Clarifies **scope boundaries**
+* Points to **authoritative sources**
+
+A primer does **not**:
+
+* Teach step-by-step usage
+* Advocate tools or vendors
+* Explore implementation details beyond what is normatively defined
+
+---
+
+## 2. Target Audience
+
+Primers are written for:
+
+* Humans with solid general IT knowledge
+* Readers who are *not specialists* in the specific topic
+* AI systems that consume structured context for reasoning and coding
+
+Authors must assume:
+
+* Conceptual literacy
+* Familiarity with basic IT terminology
+* No prior deep knowledge of the topic
+
+---
+
+## 3. Required Structure (Mandatory)
+
+Every primer **MUST** contain the following sections **in this order**:
+
+1. **Definition**
+2. **Context**
+3. **Core Concepts**
+4. **Scope and Non-Scope**
+5. **Practical Implications**
+6. **Formal Standards and Authoritative Sources**
+7. **Related Concepts**
+
+No section may be omitted.
+Empty sections are not allowed.
+
+---
+
+## 4. Section Authoring Rules
+
+### 4.1 Definition
+
+**Purpose:** Establish an unambiguous baseline meaning.
+
+Rules:
+
+* 2–4 sentences maximum
+* Declarative, precise language
+* No metaphors, examples, or analogies
+* No historical narrative
+
+Good:
+
+> “OAuth 2.0 is an authorization framework that enables a third-party application to obtain limited access to an HTTP service on behalf of a resource owner.”
+
+Bad:
+
+> “OAuth is basically a way to let apps log in without sharing passwords.”
+
+---
+
+### 4.2 Context
+
+**Purpose:** Position the concept within the IT landscape.
+
+Rules:
+
+* Describe the domain(s) the concept belongs to
+* Explain *why it exists*, not *how to use it*
+* Historical notes allowed only if they clarify intent or constraints
+
+Include:
+
+* Typical environments
+* Architectural level (protocol, pattern, framework, etc.)
+
+---
+
+### 4.3 Core Concepts
+
+**Purpose:** Identify the irreducible ideas that define the topic.
+
+Rules:
+
+* Bullet points only
+* Each bullet describes one concept
+* No nested lists
+* Avoid redundancy with Definition
+
+Think: *“What must be true for this concept to exist?”*
+
+---
+
+### 4.4 Scope and Non-Scope
+
+**Purpose:** Prevent conceptual drift and misuse.
+
+Rules:
+
+* Explicitly list inclusions and exclusions
+* Use parallel structure
+* Address common misconceptions
+
+Format:
+
+```markdown
+**In Scope**
+- ...
+
+**Out of Scope**
+- ...
+```
+
+This section is **critical** for AI agent correctness.
+
+---
+
+### 4.5 Practical Implications
+
+**Purpose:** Describe consequences of adopting or interacting with the concept.
+
+Rules:
+
+* Focus on effects, not instructions
+* No step-by-step guidance
+* Include tradeoffs where relevant
+
+Examples of acceptable content:
+
+* Design constraints
+* Operational complexity
+* Security or scalability implications
+
+---
+
+### 4.6 Formal Standards and Authoritative Sources
+
+**Purpose:** Anchor the primer in canonical truth.
+
+Rules:
+
+* Prefer primary sources
+* Include direct links
+* Avoid blogs unless widely recognized and necessary
+
+Acceptable sources:
+
+* RFCs
+* W3C Recommendations
+* ISO / IEC standards
+* NIST publications
+* Official specifications
+* Foundational academic papers
+
+At least **one** authoritative source is required.
+
+---
+
+### 4.7 Related Concepts
+
+**Purpose:** Enable semantic navigation.
+
+Rules:
+
+* Short descriptions only (one line per concept)
+* No deep explanations
+* Avoid circular definitions
+
+Example:
+
+> **OpenID Connect** – An identity layer built on top of OAuth 2.0.
+
+---
+
+## 5. Language and Style Rules
+
+Mandatory:
+
+* Present tense
+* Declarative sentences
+* Neutral, technical tone
+
+Avoid:
+
+* First-person language (“we”, “you”)
+* Rhetorical questions
+* Marketing language
+* Informal phrasing
+* Emojis
+
+---
+
+## 6. Length Constraints
+
+A primer should typically be:
+
+* **600–1,000 words total**
+* Short enough to be read in one sitting
+* Long enough to define boundaries clearly
+
+Exceeding this range requires justification.
+
+---
+
+## 7. Stability and Versioning
+
+Primers are intended to be **stable reference artifacts**.
+
+Rules:
+
+* Do not chase trends
+* Avoid speculative content
+* Update only when:
+
+  * Standards change
+  * Definitions evolve materially
+  * Authoritative sources are superseded
+
+When updating:
+
+* Preserve conceptual continuity
+* Avoid rewriting without necessity
+
+---
+
+## 8. AI Optimization Rules (Explicit)
+
+Authors **SHOULD**:
+
+* Use consistent terminology
+* Avoid synonyms for core terms once defined
+* Prefer explicit over implicit assumptions
+* State constraints clearly
+
+Authors **MUST NOT**:
+
+* Rely on context outside the document
+* Assume tool- or framework-specific defaults
+* Leave ambiguity where standards are explicit
+
+---
+
+## 9. Validation Criteria (Checklist)
+
+A primer is valid if:
+
+* [ ] All required sections are present
+* [ ] Definition is precise and unambiguous
+* [ ] Scope boundaries are explicit
+* [ ] At least one authoritative source is linked
+* [ ] No tutorial or marketing content exists
+* [ ] Language follows declarative style rules
+
+---
+
+## 10. Non-Goals
+
+InfoTechPrimers are **not**:
+
+* Documentation replacements
+* Training material
+* Opinionated best-practice guides
+* Tool comparisons
+
+Those belong elsewhere.
+
+---
+
+### Version Note
+
+This is **Primer Authoring Rules v0.1**.
+Expect tightening, not loosening, as real primers are written and validated.
+
+
+
+xxx