Add deep research prompting analysis

analyses/deep_research_prompting_analysis.md

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+### 1. Executive Summary
+
+- 1 new primary framework identified: Deep Research Prompting (DRP).
+- Adds capabilities for structural archetyping (Typological Stack, Lens-Driven Analysis) and complex iteration (ReAct, Recursive Criticism).
+- Expected impact: "foundational" for moving standard prompt workflows into research-grade, strategist-level pipelines.
+
+### 2. Document-Level Framework Extraction
+
+#### 2.1 PromptResearch/Deep Research Prompt Engineering_.md
+
+- **Framework Name**: Deep Research Prompting (DRP)
+- **Core Innovation**: Moving beyond basic queries to designing prompts as instruments of epistemic control, structuring the analytical and cognitive workflow.
+- **Key Components / Sub-Modules**: Typological Stack, Lens-Driven Analysis, Constraint-Directed Inquiry, Counterfactual Exploration, CoT, ReAct, Recursive Criticism.
+- **Complexity Level**: Advanced
+- **Primary Contribution**: Provides a taxonomy of advanced prompting patterns aimed at eliciting insight generation rather than mere summarization.
+- **Intended Use Cases**: Complex research, strategic analysis, insight generation, policy analysis.
+- **Prerequisites / Dependencies**: Large LLMs capable of multi-step reasoning.
+
+### 3. Normalized Framework Catalog
+
+- **Name**: Deep Research Prompting (DRP)
+- **Type**: Orchestration pattern / Cognitive scaffolding
+- **Core Mechanisms**:
+  - Typological Stacking (multi-persona simulation)
+  - Lens-Driven Analysis (theoretical application)
+  - Explicit Constraints
+  - CoT / ReAct / RCI loops
+- **Input / Output Contract**: Expects high-level research questions; produces structured, multi-dimensional analysis and insights.
+- **Typical Integration Point in PEW**: Prompt design and multi-agent orchestration.
+- **Complexity Tier**: Advanced
+
+### 4. Integration Mapping to Existing Workbench
+
+#### 4.1 Extensions of Existing Frameworks
+
+- **PALS Extension**: Enhances the Cognitive and Trust & Epistemics layers by providing concrete structural patterns (e.g., Typological Stacks) for directing attention and reasoning.
+- **Context Engineering 2.0**: The DRP constraints map directly onto the CxEP post-conditions and invariants.
+- **Role Prompting**: Directly extends Role Prompting with the "Typological Stack" pattern (simulating multiple interacting functions within a persona).
+
+#### 4.2 New Modules and Services
+
+- **New Services**: "Typological Stack Composer", "Lens-Driven Analysis Router"
+- **Data Models**: New fields in the PRP schema to define "Analytical Lens" and "Counterfactual Variables".
+- **Workflow Slots**: During the initial prompt design phase and within ReAct/RCI loops in the execution engine.
+
+### 5. Proposed Workbench Architecture Updates
+
+- **Core Engine Changes**: Add native support for ReAct and Recursive Criticism (RCI) loops within the execution engine.
+- **Integration Layer**: Create a "Lens Application Engine" that maps specific theoretical frameworks to incoming prompts.
+- **User Interface Additions**: Add a "Typological Stack Builder" to the Role Prompting workspace and a "Lens Selector" to the prompt builder.
+- **Advanced Workflow Engine**: Support for recursive prompt execution (RCI loops).
+
+### 6. Implementation Roadmap
+
+- **Phase 1: Foundation (0–2 months)**
+  - **Goals**: Implement basic Constraint-Directed Inquiry and Typological Stack patterns.
+  - **Deliverables**: Typological Stack Builder UI, constraint validation in CxEP.
+  - **Technical Risks**: Prompt length limits with complex typological stacks.
+  - **Dependencies**: Existing PALS and Role Prompting workspaces.
+
+- **Phase 2: Intermediate (2–6 months)**
+  - **Goals**: Deploy the Lens-Driven Analysis routing and basic CoT scaffolding.
+  - **Deliverables**: Lens Selector UI, pre-built lens library, automated CoT injection.
+  - **Technical Risks**: Lens abstraction might be too vague for certain models.
+  - **Dependencies**: Phase 1 completion.
+
+- **Phase 3: Advanced (6–12+ months)**
+  - **Goals**: Implement full ReAct and RCI (Recursive Criticism and Improvement) loops.
+  - **Deliverables**: Recursive execution engine, ReAct tool integration, automated self-refinement pipelines.
+  - **Technical Risks**: Infinite loops in recursive prompting, high API costs.
+  - **Dependencies**: Advanced Workflow Engine overhaul.
+
+### 7. Success Metrics and Evaluation
+
+- **Quantitative Metrics**:
+  - Prompt quality improvements: Increase in "Insight Generation" scores vs. "Summarization" scores on a standardized test set.
+  - RCI loop efficiency: Number of iterations to reach passing state.
+- **Qualitative Metrics**:
+  - Researcher satisfaction with Lens-Driven Analysis outputs.
+  - Novel insights generated via Counterfactual Exploration patterns.
+
+### 8. Research-to-Practice Translation
+
+- **Recommended Starter Workflows**: Start with the Typological Stack Builder to define complex personas, then apply a specific Analytical Lens to a dataset.
+- **Suggested Personas**: Researchers (using Lens-Driven Analysis), Strategists (using Counterfactual Exploration).
+- **Collaboration**: Open repository of Analytical Lenses and Typological Stack templates.