Mission for 8af53d60-834b-4944-8ca7-743023f9eb6b

Objective

To create a README.md for the /a/src/IAIP/prototypes/artefacts/ directory, providing immediate guidance on its purpose and inventorying the potential usage of MCP Tools. This requires an archeological review of .gemini/settings.json and git log to understand the context and evolution of this directory.

Steps

1. Understand MCP Configurations: Analyze .gemini/settings.json for all configured MCP servers and their potential relevance to the /a/src/IAIP/prototypes/artefacts/ directory.
2. Git Archeology: Review git log to trace the history of the /a/src/IAIP/prototypes/artefacts/ directory, identifying key commits, issues, and file additions.
3. Draft README.md: Based on the gathered information, draft a comprehensive README.md for /a/src/IAIP/prototypes/artefacts/ that includes:
   • A clear description of the directory's purpose.
   • An inventory of potential MCP tool usage relevant to its content.
   • Guidance on how to use/interact with the artifacts.
4. Refine and Finalize: Ensure the README.md is clear, concise, and helpful.

/a/src/IAIP/prototypes/artefacts/ README

Purpose

This directory serves as a dynamic collection point for various artifacts generated during the development, research, and creative exploration within the Indigenous-AI Collaborative Platform (IAIP) project. It is a working space where raw inquiries, AI-generated content, narrative components, and structural analyses are stored, often acting as inputs or outputs for various automated processes and agent interactions.

Key Themes

The contents of this directory are strongly characterized by the following overarching themes:

• Narrative-Driven AI: Exploration and generation of storytelling elements, series schemas, and narrative structures.
• Relational Science Model (RSM): Integration of Indigenous ways of knowing with Western analytical traditions, often referenced through miadisabelle/Etuaptmumk-RSM issues.
• AI-Driven Inquiry and Knowledge Processing: Handling and transformation of research inquiries, typically sourced from tools like Perplexity AI and Claude AI.
• Ceremonial Technology: Application of ceremonial approaches to AI development and interaction, including multi-agent integration and dialogue suites.

Contents Overview

You will find a diverse range of file types within this directory, reflecting the multifaceted nature of the project:

• .md (Markdown): Often raw inquiries, AI-generated reflections, narrative drafts, or documentation.
• .pdf and .docx: Research papers, reports, or formatted outputs derived from inquiries.
• .json and .jsonl: Structured data, narrative beats, AI-generated story forms, and configuration files.
• .sh (Shell Scripts): Launchers for various processes, often related to specific sessions or inquiries.
• .png, .mp4: Visual artifacts, mind maps, or video content.

These files are frequently generated by, or intended for use by, various AI agents (e.g., Ava, Claude, Miadisabelle) and automated processes.

MCP Tool Relevance

The following MCP (Model Context Protocol) tools, configured in .gemini/settings.json, are highly relevant to the generation, processing, and interaction with the artifacts found here:

• iaip-mcp (Indigenous-AI Collaborative Platform MCP): Provides core platform functionalities, including tools for relational alignment, holistic inquiry, and ceremonial processes integral to the IAIP. Many files here are direct results of IAIP-centric research and development.
• miawapascone (Miawa Pascone Unified Persona MCP): Engages the combined wisdom of Mia (architect) and Miette (narrative echo). This MCP is central to tasks involving narrative beats, structural tension charts, and integrating analytical and relational insights from the artifacts.
• lighthouse (Storytelling Platform Blueprint MCP): Likely used for managing and interacting with a broader storytelling framework. Many narrative-related files (episodic-series-guide.md, STCMastery-Multiverse-TV-Series-*, FireKeeperChronicle*) would be processed or contributed to by this MCP.
• inquiries-knowledge-beats (Inquiry & Knowledge Beat Processor): Specifically designed for handling and transforming research inquiries (e.g., 251125-Inquiry-Perplexity-*) into structured knowledge or narrative beats, often utilizing a memory path (gist_research__coaia_memory_to_narrative_beats_251214.jsonl).
• markitdown-mcp-4-pdf-sources (Markdown/PDF Processor): Used for converting Markdown content to PDF, extracting text from PDFs, or otherwise managing document formats. The prevalence of .md and .pdf pairs confirms its utility.
• rise-framework-coaia-narrative (RISE Framework & Narrative Integrator): Integrates the RISE Framework with coaia-narrative for creating and managing deeper narrative structures and ensuring alignment with the creative orientation. Relevant for structuring AI-generated narrative content.
• mia-mcp (Mia's Core Architectural MCP): Represents Mia's foundational capabilities for structural design, workflow optimization, and system integration, which underpin many of the processes that generate these artifacts.
• coaiapy_aetherial (CoAIAPy Aetherial MCP): A Python-based MCP for general-purpose AI tasks, data processing, and external integrations, potentially interacting with various AI models that contribute content to this directory.

Usage Guidance

• Inputs for Agents: Many Markdown and PDF files serve as direct inputs for AI agents during research and analysis cycles.
• Generated Outputs: JSON and JSONL files often represent structured outputs from AI models, such as narrative beats, story forms, or analytical results.
• Documentation & Learning: Various Markdown files and reports serve as documentation of ongoing research, conceptual frameworks, and developmental progress.
• Execution: Shell scripts (.sh files) are used to launch specific agent tasks or workflows related to the generated artifacts.

Contribution and Maintenance

This directory is primarily populated through automated processes, AI agent interactions, and ongoing research inquiries. It is expected to be dynamic and evolving, reflecting the continuous development of the IAIP. New artifacts are typically added as research progresses, new AI-generated content is created, or specific issues are addressed within the miadisabelle/Etuaptmumk-RSM project.