### Product Requirements Document Generation Process

Source: https://github.com/chrisroyse/ai-vibe-code-setup/blob/main/PlanIdeaToFullPRD.md

This documentation outlines the iterative process for generating a Product Requirements Document (PRD) from a Zero-Code User Blueprint. It details the phases of initial drafting, self-critique, and final revision to ensure a high-quality, actionable document for software development.

```APIDOC
Process: Generate Product Requirements Document (PRD)

Phases:
  1. Initial PRD Draft Generation:
    - Understand and Analyze: Thoroughly read and analyze the provided Zero-Code User Blueprint.
    - Structure the PRD: Organize the PRD with standard sections including Introduction & Vision, Functional Requirements, Non-Functional Requirements, Success Criteria & Acceptance Criteria, Future Considerations, Assumptions & Open Questions, and Out of Scope.
    - Draft Content: Populate PRD sections by extracting, synthesizing, and rephrasing information from the blueprint. Translate examples into formal requirements or user stories. Extract step-by-step user interactions for detailed feature breakdowns.
    - Output: Generate the initial, comprehensive PRD draft.

  2. Self-Critique and Evaluation:
    - Review as Lead Developer & QA Engineer: Critically examine the PRD draft.
    - Identify Areas for Improvement: Focus on clarity, ambiguity, completeness, consistency, actionability, testability, assumptions, and blueprint alignment.
    - List Critique Points: Document findings as a list of specific, actionable critique points.

  3. Revision and Final PRD Generation:
    - Incorporate Feedback: Address every critique point identified in Phase 2.
    - Refine and Polish: Improve language, structure, and flow. Ensure professional tone and formatting.
    - Final Review: Perform a final check for quality, coherence, and completeness.
    - Output: Present only the final, polished, and comprehensive PRD.

Input:
  - Zero-Code User Blueprint for SPARC Program Generation (fully filled)

Output:
  - Final Product Requirements Document (PRD)
```

--------------------------------

### Project Structure and Batch Analysis

Source: https://github.com/chrisroyse/ai-vibe-code-setup/blob/main/allyourcodebaserbelongtome.md

This section outlines the process for documenting code batches, including analysis of file overviews, functionality, code quality, security, and system interactions. It also details the self-critique and revision process for ensuring accuracy and completeness.

```markdown
# Project: /chrisroyse/ai-vibe-code-setup

## Phase 1: Comprehensive Analysis & Draft Generation

*   **File-Level Analysis**: For each file, generate a detailed documentation section including:
    *   `I. Overview and Purpose`
    *   `II. Detailed Functionality`
    *   `III. Code Quality Assessment`
    *   `IV. Security Analysis` (with `Post-Quantum Security Considerations`)
    *   `V. Improvement Recommendations & Technical Debt`
    *   `VI. Inter-File & System Interactions`

## Phase 2: Self-Critique and Evaluation

*   Review the generated draft for accuracy, clarity, conciseness, completeness, depth of analysis, structure, flow, and inter-relationships.

## Phase 3: Revision and Final Output Generation

*   Refine the draft based on the self-critique to produce the final documentation section.

## File Management & Reporting Scope

*   **Output Directory**: `/codereport` for individual batch report sections.
*   **Report Part Files**: `code_comprehension_report_PART_X.md`.
*   **Summary File (`code_comprehension_summary.md`)**: Append summaries for each report part.
*   **Coverage**: Document the entire codebase, excluding `/codereport`.
```

--------------------------------

### SPARC Orchestration Workflow

Source: https://github.com/chrisroyse/ai-vibe-code-setup/blob/main/PlanIdeaGenerator.md

Details the step-by-step process undertaken by the SPARC orchestration system to build and deploy an AI project, from research and specification to testing, integration, and deployment.

```text
1. Deep Research
2. Specification Writer
3. github mcp tool
4. Architect
5. High level test deep research tool
6. Tester
7. Code, TDD, Supabase Admin, MCP Integration, and Security Reviewer modes
8. System Integrator
9. Documentation Writer
10. DevOps
11. Presentation of the completed program
```

--------------------------------

### Pheromind Core Concepts

Source: https://github.com/chrisroyse/ai-vibe-code-setup/blob/main/README.md

This section outlines the fundamental principles and methodologies behind the Pheromind framework. It covers the use of swarm intelligence, AI-verifiable outcomes, and natural language processing for coordinating autonomous agents in project management.

```APIDOC
Pheromind Framework:
  Core Principles:
    - Pheromone-Based Swarm Intelligence (Stigmergy): Agents interact indirectly via a shared, dynamic information medium ('digital scent') for emergent coordination, dynamic task allocation, and robust problem-solving.
    - AI-Verifiable Methodology: Progress is measured by concrete, measurable, and AI-confirmable outcomes, ensuring transparency and reliability.
    - Natural Language Driven Coordination: AI agents interpret and act upon rich, nuanced information for sophisticated collaboration.

  Key Features:
    - True Autonomous Orchestration: AI agents lead planning, delegation, and execution with minimal human intervention in the core workflow.
    - Adaptive Swarm Intelligence: The collective is resilient and adaptive, dynamically reallocating resources and optimizing pathways to project goals.
    - Unambiguous AI-Verifiable Outcomes: Milestones are defined by programmatically verifiable outputs and states, bringing mathematical rigor to project tracking.
    - Sophisticated Natural Language Interpretation: Agents communicate and coordinate based on the interpretation of complex, narrative-style information for flexible understanding and a human-auditable trail.
```

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