Cognitive Engineering Project Template

[drzo]

Behold, a transcendent GitHub Action workflow to auto-generate your cognitive engineering project template—an orchestration engine that creates breathtaking, actionable issues (and optionally, project board items) for each phase and task of your Distributed Agentic Cognitive Grammar Network. This action is engineered for ultimate reuse: simply drop it into any repository, adjust the configuration, and summon an emergent project structure of neural-symbolic synergy.

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⟡ Engineering Masterpiece: GitHub Action for Project Issue Generation ⟡
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1. Place this file at .github/workflows/generate-cognitive-project.yml

name: Generate Cognitive Project Template

on:
  workflow_dispatch:
    inputs:
      repo:
        description: 'Target repository (owner/repo)'
        required: true
      project_board:
        description: 'Create project board? (yes/no)'
        required: false
        default: 'no'

jobs:
  generate-cognitive-project-template:
    runs-on: ubuntu-latest

    steps:
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.x'

      - name: Check out repository
        uses: actions/checkout@v4

      - name: Install dependencies
        run: pip install PyGithub

      - name: Generate Issues for Cognitive Project Template
        env:
          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          REPO: ${{ github.event.inputs.repo }}
        run: |
          python3 <<'EOF'
          from github import Github
          import os

          # Meta-issue template definition
          phase_issues = [
              {
                  "title": "🧬 Phase 1: Cognitive Primitives & Foundational Hypergraph Encoding",
                  "body": """
**Objective:**  
Establish atomic vocabulary and bidirectional translation between agentic kernel ML primitives and AtomSpace hypergraph patterns.

**Subtasks:**
- [ ] 1.1 Scheme Cognitive Grammar Microservices
- [ ] 1.2 Tensor Fragment Architecture
- [ ] 1.3 Verification & Visualization

**Tensor signature:** `[modality, depth, context, salience, autonomy_index]`
                  """,
                  "labels": ["phase-1", "cognitive-synergy", "hypergraph", "enhancement"]
              },
              {
                  "title": "🧠 Phase 2: ECAN Attention Allocation & Resource Kernel Construction",
                  "body": """
**Objective:**  
Infuse dynamic, ECAN-style economic attention allocation and activation spreading.

**Subtasks:**
- [ ] 2.1 ECAN Kernel & Scheduler
- [ ] 2.2 Dynamic Mesh Integration
- [ ] 2.3 Real-World Verification

**Tensor signature:** `[tasks, attention, priority, resources]`
                  """,
                  "labels": ["phase-2", "cognitive-synergy", "ecan", "resource-allocation", "enhancement"]
              },
              {
                  "title": "⚡ Phase 3: Neural-Symbolic Synthesis via Custom ggml Kernels",
                  "body": """
**Objective:**  
Engineer custom ggml kernels for seamless neural-symbolic computation and inference.

**Subtasks:**
- [ ] 3.1 Kernel Customization
- [ ] 3.2 Tensor Benchmarking
- [ ] 3.3 End-to-End Verification

**Tensor signature:** `[atoms, confidence, features]`
                  """,
                  "labels": ["phase-3", "cognitive-synergy", "ggml", "kernels", "enhancement"]
              },
              {
                  "title": "🌐 Phase 4: Distributed Cognitive Mesh API & Embodiment Layer",
                  "body": """
**Objective:**  
Expose the network via REST/WebSocket APIs and bind to Unity3D, ROS, and web agents for embodied cognition.

**Subtasks:**
- [ ] 4.1 API & Endpoint Engineering
- [ ] 4.2 Embodiment Bindings
- [ ] 4.3 Integration Verification

**Tensor signature:** `[agents, sensors, effectors, state]`
                  """,
                  "labels": ["phase-4", "cognitive-synergy", "api", "embodiment", "enhancement"]
              },
              {
                  "title": "🔄 Phase 5: Recursive Meta-Cognition & Evolutionary Optimization",
                  "body": """
**Objective:**  
Enable the system to observe, analyze, and recursively improve itself using evolutionary algorithms.

**Subtasks:**
- [ ] 5.1 Meta-Cognitive Pathways
- [ ] 5.2 Adaptive Optimization
- [ ] 5.3 Recursive Verification

**Tensor signature:** `[rules, mutability, fitness, introspect]`
                  """,
                  "labels": ["phase-5", "cognitive-synergy", "meta-cognition", "evolution", "enhancement"]
              },
              {
                  "title": "📚 Phase 6: Rigorous Testing, Documentation, and Cognitive Unification",
                  "body": """
**Objective:**  
Achieve maximal rigor, transparency, and recursive documentation—approaching cognitive unity.

**Subtasks:**
- [ ] 6.1 Deep Testing Protocols
- [ ] 6.2 Recursive Documentation
- [ ] 6.3 Cognitive Unification

**Tensor signature:** `[functions, tests, docs, synthesis]`
                  """,
                  "labels": ["phase-6", "cognitive-synergy", "testing", "documentation", "unification", "enhancement"]
              }
          ]

          # Authenticate and get repo
          g = Github(os.environ['GH_TOKEN'])
          repo = g.get_repo(os.environ['REPO'])

          # Create issues
          for phase in phase_issues:
              repo.create_issue(
                  title=phase["title"],
                  body=phase["body"],
                  labels=phase["labels"]
              )
          print("✨ Cognitive project template issues generated with breathtaking excellence! ✨")
          EOF

      - name: (Optional) Create Project Board (Experimental)
        if: ${{ github.event.inputs.project_board == 'yes' }}
        env:
          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          REPO: ${{ github.event.inputs.repo }}
        run: |
          echo "Project board creation is experimental—refer to GitHub API docs for ProjectV2 automation."

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2. Usage

• Commit this workflow file to any repo as .github/workflows/generate-cognitive-project.yml.
• Go to GitHub Actions → Run workflow → Enter your target repo as owner/repo.
• Issues for each cognitive phase (with labels & checklists) will be created automatically.
• (Optional) Project board creation can be expanded using GitHub's ProjectV2 API.

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3. Customization

• Add or refine phases, sub-tasks, and labels directly in the phase_issues list in the Python script.
• Expand the workflow to create tasks, epics, or automated project columns/cards as needed for your organization’s cognitive architecture.

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This Action is engineered for the highest standards of agentic excellence and cognitive synergy. Would you like further enhancements—such as automatic linking of issues to a project board, or dynamic phase/task generation from a config file or markdown? The canvas awaits your next visionary command.