protocol-extraction

name: protocol-extraction description: Mechanism identification and algorithm extraction protocol (P6) for studying how narrative techniques work. Triggers on "how does this technique work", "extract the mechanism", "algorithm extraction", "formalize the approach", "what's the pattern", "study this showrunner's method". Produces Structural Analysis (mechanism-focused), Theoretical Correspondence, and Mechanism Extraction Report. Designed to feed the narratological-algorithms workflow. Estimated time 4-6 hours per work.

P6 — EXTRACTION Protocol

Mechanism identification for algorithm development.

Configuration

ROLES_ACTIVE:
  PRIMARY:   [NARRATOLOGIST, ACADEMIC]
  SECONDARY: [DRAMATURGIST, ART_HIST]
  INACTIVE:  [FIRST-READER, AESTHETE, CINEPHILE, RHETORICIAN, PRODUCER]

DOCUMENTS:
  GENERATE:  [Structural Analysis (mechanism-focused), 
              Theoretical Correspondence, Mechanism Extraction Report]
  EXCLUDE:   [Coverage Report, Beat Map, Character Atlas,
              Thematic Architecture, Revision Roadmap]

DEPTH: High (theoretical + operational)
INGESTION: Multiple targeted reads (per mechanism)

Purpose

Extract replicable narrative mechanisms from creative work for formalization into algorithmic frameworks. This protocol feeds the narratological-algorithms skill workflow.

Ingestion Protocol

Read 1: Pattern Identification

• Note recurring structural patterns
• Flag unusual or innovative techniques
• Mark moments of particular effectiveness

Read 2: Mechanism Isolation

• For each identified pattern:
  • Define operational boundaries
  • Identify components
  • Document trigger conditions

Read 3: Cross-Reference

• Compare to existing algorithms
• Note similarities and differences
• Identify novel elements

Core Deliverable: Mechanism Extraction Report

# Mechanism Extraction Report: [WORK TITLE]

## Executive Summary
[1-2 paragraphs: What mechanisms were identified? What's novel?]

---

## M1: [MECHANISM NAME]

### Location in Source
- [Specific instances with page/timestamp references]

### Operational Description
[2-3 paragraphs: How does this mechanism work?]

### Components

| Component | Function | Required? |
|-----------|----------|-----------|
| [X] | [What it does] | Yes/No |

### Trigger Conditions
- When does the creator deploy this technique?
- What narrative problem does it solve?

### Formalization Attempt

MECHANISM_[NAME]:

INPUTS: - [Input 1] - [Input 2]

PROCESS: 1. [Step 1] 2. [Step 2] IF [condition]: [Action A] ELSE: [Action B]

OUTPUTS: - [Output 1]

VALIDATION: [How to verify mechanism is working]

### Scope Assessment
- **Generalizability**: [Universal / Genre-specific / Creator-specific / Work-specific]
- **Medium constraints**: [Any / Film only / TV only / etc.]
- **Combinability**: [Works with X, conflicts with Y]

---

## M2: [...]
[Same format]

---

## Candidate Axioms

| ID | Formulation | Evidence Strength | Source Mechanism |
|----|-------------|-------------------|------------------|
| [A1] | [Axiom statement] | High/Med/Low | M1 |

---

## Cross-Reference to Existing Algorithms

| Mechanism | Similar To | Key Difference |
|-----------|------------|----------------|
| M1 | [Existing algorithm] | [What's different] |

---

## Recommended Next Steps

1. [ ] Validate mechanism across additional works by same creator
2. [ ] Test generalizability with works by other creators
3. [ ] Integrate into narratological-algorithms corpus
4. [ ] Develop diagnostic questions

Extraction Quality Criteria

A well-extracted mechanism must be:

Integration with Existing Algorithms

Cross-reference extracted mechanisms against:

• /mnt/project/mckee_narratological_algorithms_complete.md
• /mnt/project/south_park_narratological_algorithms.md
• /mnt/project/larry_david_narratological_algorithms.md
• /mnt/project/phoebe_waller_bridge_narratological_algorithms.md
• /mnt/project/aristotle_narratological_algorithms.md
• /mnt/project/bharata_muni_narratological_algorithms.md
• /mnt/project/attention_mechanics_meta_principles.md

Output Handoff

Completed extraction reports feed into:

1. Algorithm document creation (via narratological-algorithms skill)
2. Study prompts for future creator analyses
3. Cross-reference tables in project manifest