TASKLIST: CLAUDE.md Creation

Overview

Create CLAUDE.md files for all submodules missing AI agent configuration.

Current State: 17 have CLAUDE.md, 25 missing Parent (master): Already has comprehensive CLAUDE.md

Progress Summary

Category	Total	Have	Missing
core	3	2	1
cloud	4	1	3
dev	9	4	5
docs	5	1	4
ops	3	1	2
gtm	6	1	5
market	2	0	2
labs	11	8	3
TOTAL	43	18	25

Submodules Needing CLAUDE.md (25)

core/ (1 missing)

coditect-core-framework
- Path: submodules/core/coditect-core-framework/CLAUDE.md
- Type: Library/Framework (Stub)
- Context: Distributable CODITECT framework for external projects

cloud/ (3 missing)

coditect-cloud-backend
- Path: submodules/cloud/coditect-cloud-backend/CLAUDE.md
- Type: Standalone Application
- Context: FastAPI backend, PostgreSQL, JWT auth
coditect-cloud-frontend
- Path: submodules/cloud/coditect-cloud-frontend/CLAUDE.md
- Type: Standalone Application (Stub)
- Context: React/TypeScript admin dashboard
coditect-cloud-infra
- Path: submodules/cloud/coditect-cloud-infra/CLAUDE.md
- Type: Configuration (Stub)
- Context: Terraform, GCP, Kubernetes

dev/ (5 missing)

coditect-cli
- Path: submodules/dev/coditect-cli/CLAUDE.md
- Type: Standalone Application (Stub)
- Context: CLI tools for CODITECT operations
coditect-analytics
- Path: submodules/dev/coditect-analytics/CLAUDE.md
- Type: Library (Stub)
- Context: Usage analytics and metrics
coditect-automation
- Path: submodules/dev/coditect-automation/CLAUDE.md
- Type: Library (Stub)
- Context: AI orchestration and workflow automation
coditect-dev-context
- Path: submodules/dev/coditect-dev-context/CLAUDE.md
- Type: Library (Stub)
- Context: Context management system

docs/ (4 missing)

coditect-docs-main
- Path: submodules/docs/coditect-docs-main/CLAUDE.md
- Type: Documentation (Stub)
- Context: Docusaurus documentation site
coditect-docs-blog
- Path: submodules/docs/coditect-docs-blog/CLAUDE.md
- Type: Standalone Application
- Context: NestJS/React enterprise blog platform
coditect-docs-training
- Path: submodules/docs/coditect-docs-training/CLAUDE.md
- Type: Documentation/Configuration
- Context: AI curriculum framework, Python ML stack
coditect-legal
- Path: submodules/docs/coditect-legal/CLAUDE.md
- Type: Documentation (Stub)
- Context: Legal documents (EULA, ToS, Privacy)

ops/ (2 missing)

coditect-ops-license
- Path: submodules/ops/coditect-ops-license/CLAUDE.md
- Type: Library/Application
- Context: License management, Python client + FastAPI server
coditect-ops-projects
- Path: submodules/ops/coditect-ops-projects/CLAUDE.md
- Type: Configuration
- Context: Project coordination hub, tasklists

gtm/ (5 missing)

coditect-gtm-strategy
- Path: submodules/gtm/coditect-gtm-strategy/CLAUDE.md
- Type: Documentation
- Context: Master GTM strategy (66K+ words)
coditect-gtm-comms
- Path: submodules/gtm/coditect-gtm-comms/CLAUDE.md
- Type: Documentation
- Context: Communications center, Mermaid diagrams
coditect-gtm-crm
- Path: submodules/gtm/coditect-gtm-crm/CLAUDE.md
- Type: Research
- Context: Rust ERP/CRM based on ODOO
coditect-gtm-personas
- Path: submodules/gtm/coditect-gtm-personas/CLAUDE.md
- Type: Documentation
- Context: Customer personas, interview frameworks
coditect-gtm-customer-clipora
- Path: submodules/gtm/coditect-gtm-customer-clipora/CLAUDE.md
- Type: Standalone Application
- Context: AI social media SaaS (FastAPI/React)

market/ (2 missing)

coditect-market-agents
- Path: submodules/market/coditect-market-agents/CLAUDE.md
- Type: Standalone Application (Stub)
- Context: Agent marketplace
coditect-market-activity
- Path: submodules/market/coditect-market-activity/CLAUDE.md
- Type: Library (Stub)
- Context: Activity feed for marketplace

labs/ (3 missing)

coditect-labs-first-principles
- Path: submodules/labs/coditect-labs-first-principles/CLAUDE.md
- Type: Documentation
- Context: Strategic vision document (127KB)
coditect-labs-learning
- Path: submodules/labs/coditect-labs-learning/CLAUDE.md
- Type: Research
- Context: Google Nested Learning research
coditect-labs-mcp-auth
- Path: submodules/labs/coditect-labs-mcp-auth/CLAUDE.md
- Type: Library
- Context: MCP server for Claude Code
coditect-labs-screenshot
- Path: submodules/labs/coditect-labs-screenshot/CLAUDE.md
- Type: Research
- Context: Screenshot capture utilities

Submodules with Existing CLAUDE.md (17)

Already have comprehensive CLAUDE.md files:

core/ (2)

✅ coditect-core (407 lines)
✅ coditect-core-architecture (140 lines)

cloud/ (1)

✅ coditect-cloud-ide (345 lines)

dev/ (4)

✅ coditect-dev-audio2text (658 lines)
✅ coditect-dev-intelligence (784 lines)
✅ coditect-dev-pdf (545 lines)
✅ coditect-dev-qrcode (172 lines)

docs/ (1)

✅ coditect-docs-setup (239 lines)

ops/ (1)

✅ coditect-ops-distribution (141 lines)

gtm/ (1)

✅ coditect-gtm-legitimacy (393 lines)

labs/ (7)

✅ coditect-labs-agent-standards (360 lines)
✅ coditect-labs-agents-research (88 lines)
✅ coditect-labs-claude-research (646 lines)
✅ coditect-labs-cli-web-arch (516 lines)
✅ coditect-labs-multi-agent-rag (471 lines)
✅ coditect-labs-v4-archive (1466 lines)
✅ coditect-labs-workflow (778 lines)

Parent Repository

✅ coditect-rollout-master - Has comprehensive CLAUDE.md (already complete)

Next Steps

Create CLAUDE.md template based on existing good examples
Use SUBMODULE-ANALYSIS-FRAMEWORK.md for context
Systematically create 25 missing CLAUDE.md files
Each should include:
- Project overview and purpose
- Technology stack
- Key commands
- Development workflow
- Testing approach
- Important files/directories

Created: 2025-11-20 Status: Ready for Execution Priority: P1

This tasklist tracks CLAUDE.md creation for AI agent configuration across all submodules.

TASKLIST: README Standardization

Overview

Track progress of README standardization across all 43 repositories.

Template: docs/README-TEMPLATE-STANDARD.md Project Plan: docs/PROJECT-PLAN-README-STANDARDIZATION.md

Progress Summary

Phase	Total	Pending
Phase 1: Foundation	7	7
Phase 2: Dev Tools	8	8
Phase 3: Docs/Ops	8	8
Phase 4: Market/GTM	8	8
Phase 5: Labs	11	11
Phase 6: Master	1	1
TOTAL	43	43

Phase 1: Foundation (core/ & cloud/)

Priority: P0 - Critical foundation

core/ (3 repos)

cloud/ (4 repos)

Phase 2: Development Tools (dev/)

Priority: P0 - Developer daily use

Phase 3: Documentation & Operations (docs/ & ops/)

Priority: P1 - Supporting infrastructure

docs/ (5 repos)

ops/ (3 repos)

Phase 4: Marketplace & Go-to-Market (market/ & gtm/)

Priority: P1 - Business and go-to-market

market/ (2 repos)

gtm/ (6 repos)

Phase 5: Labs & Research (labs/)

Priority: P2 - Research and experimental

Phase 6: Master Repository

Priority: P0 - Central orchestration

coditect-rollout-master (373 lines - substantial)
- Path: README.md (root)
- Action: Review and ensure template compliance
- Update checkpoint references
- Verify submodule table accuracy
- Update status section
- Review quick start commands

Verification Checklist

After all phases complete, verify:

All 43 READMEs standardized
No placeholder text (TODO/TBD) remaining
All distributed intelligence sections present
Cross-references accurate
Quick start commands tested
Technology stacks accurate
Git commit for each update
All changes pushed to remote

Notes

Mark main checkbox when entire repo README is complete
Mark sub-checkboxes as you complete each section
Commit after each README update
Test quick start commands where possible
Flag any repos needing additional review

Created: 2025-11-19 Status: Ready for Execution Last Updated: 2025-11-19

Systematic progress through this tasklist ensures complete README standardization.

CODITECT Repository Reorganization - Tasklist

Progress Summary

Phase	Tasks	Pending	% Complete
Phase 1: Preparation	8	8	0%
Phase 2: Consolidations	12	12	0%
Phase 3: Renames	25	25	0%
Phase 4: Transfers	6	6	0%
Phase 5: Restructure	18	18	0%
Phase 6: References	15	15	0%
Phase 7: Testing	10	10	0%
Phase 8: Documentation	8	8	0%
Total	102	102	0%

Phase 1: Preparation & Backup (Day 1 - 2 hours)

1.1 Backup Current State

Agent: codi-devops-engineer Duration: 30 min Dependencies: None

Create backup directory backups/pre-reorg-2025-11-19/
Copy current .gitmodules to backup
Export current submodule SHAs: git submodule status > backup/submodule-shas.txt
Create tarball of docs/ directory

Acceptance: Backup directory contains .gitmodules and SHA list

1.2 Create Rollback Script

Agent: codi-devops-engineer Duration: 30 min Dependencies: 1.1

Create scripts/rollback-reorg.sh
Script restores .gitmodules from backup
Script resets submodule paths
Test rollback on copy of repo

Acceptance: Rollback script documented and tested

1.3 Verify Permissions

Agent: codi-devops-engineer Duration: 15 min Dependencies: None

Run gh auth status - verify admin access
Verify write access to coditect-ai org
Verify write access to halcasteel repos
Test rename on throwaway repo

Acceptance: All permissions confirmed

Phase 2: Consolidations & Merges (Day 1-2 - 2 hours)

2.1 Merge coditect-installer → coditect

Agent: codi-devops-engineer Duration: 45 min Dependencies: Phase 1 complete

Clone both repos locally
Copy coditect-installer content into coditect
Resolve any conflicts
Commit with merge message
Push to halcasteel/coditect
Archive coditect-ai/coditect-installer

Acceptance: All installer content in halcasteel/coditect

2.2 Merge coditect-license-server → coditect-license-manager

Agent: codi-devops-engineer Duration: 45 min Dependencies: Phase 1 complete

Clone both repos locally
Copy license-server content into license-manager
Resolve any conflicts
Update imports/references as needed
Commit with merge message
Push to coditect-ai/coditect-license-manager
Archive coditect-ai/coditect-license-server

Acceptance: License server functionality in license-manager

2.3 Merge competitive research

Agent: codi-devops-engineer Duration: 30 min Dependencies: Phase 1 complete

Copy az1.ai-coditect-AI-IDE-competitive-market-research content
Add to halcasteel/coditect-competition
Commit with merge message
Archive source repo

Acceptance: All competitive research consolidated

Phase 3: GitHub Renames (Day 2-3 - 1.5 hours)

3.1 Rename Core Repos (3)

Agent: codi-devops-engineer Duration: 10 min Dependencies: Phase 2 complete

gh repo rename coditect-ai/coditect-project-dot-claude coditect-core
gh repo rename coditect-ai/coditect-framework coditect-core-framework
gh repo rename coditect-ai/coditect-distributed-architecture coditect-core-architecture

Acceptance: All core repos renamed, redirects active

3.2 Rename Cloud Repos (5)

Agent: codi-devops-engineer Duration: 10 min Dependencies: Phase 2 complete

gh repo rename coditect-ai/Coditect-v5-multiple-LLM-IDE coditect-cloud-ide
gh repo rename coditect-ai/coditect-infrastructure coditect-cloud-infra
Verify coditect-cloud-backend (no change needed)
Verify coditect-cloud-frontend (no change needed)
Note: foundationdb added later from az1-ai

Acceptance: All cloud repos renamed

3.3 Rename Dev Repos (9)

Agent: codi-devops-engineer Duration: 15 min Dependencies: Phase 2 complete

Verify coditect-cli (no change needed)
Verify coditect-automation (no change needed)
Verify coditect-analytics (no change needed)
gh repo rename coditect-ai/coditect-context-api coditect-dev-context
gh repo rename coditect-ai/coditect-project-intelligence coditect-dev-intelligence
gh repo rename coditect-ai/coditect-pdf-convertor coditect-dev-pdf
gh repo rename coditect-ai/az1.ai-coditect-audio2text-workflow coditect-dev-audio2text
gh repo rename coditect-ai/az1.ai-coditect-contact-qr-code-generator coditect-dev-qrcode

Acceptance: All dev repos renamed

3.4 Rename Market Repos (3)

Agent: codi-devops-engineer Duration: 10 min Dependencies: Phase 2 complete

gh repo rename coditect-ai/coditect-agent-marketplace coditect-market-agents
gh repo rename coditect-ai/coditect-activity-data-model-ui coditect-market-activity
Note: enterprise-agents added later from az1-ai

Acceptance: All market repos renamed

3.5 Rename Docs Repos (5)

Agent: codi-devops-engineer Duration: 10 min Dependencies: Phase 2 complete

gh repo rename coditect-ai/coditect-docs coditect-docs-main
Verify coditect-legal (no change needed)
Verify coditect-blog-application → coditect-docs-blog
gh repo rename coditect-ai/az1.ai-coditect-ai-syllubus-curriculum-course-material coditect-docs-training
gh repo rename coditect-ai/coditect-claude-code-initial-setup coditect-docs-setup

Acceptance: All docs repos renamed

3.6 Rename Ops Repos (3)

Agent: codi-devops-engineer Duration: 10 min Dependencies: Phase 2 complete

gh repo rename coditect-ai/coditect-rollout-master coditect-ops-master
Note: distribution and license renamed after transfer (Phase 4)
gh repo rename coditect-ai/coditect-projects coditect-ops-projects

Acceptance: Ops repos renamed

3.7 Rename GTM Repos (7)

Agent: codi-devops-engineer Duration: 15 min Dependencies: Phase 2 complete

gh repo rename coditect-ai/coditect-communications coditect-gtm-comms
gh repo rename coditect-ai/az1.ai-CODITECT.AI-GTM coditect-gtm-strategy
gh repo rename coditect-ai/az1.ai-CODITECT-ERP-CRM coditect-gtm-crm
Note: competition renamed after transfer
gh repo rename coditect-ai/coditect-persona-customer-questions coditect-gtm-personas
gh repo rename coditect-ai/coditect-customer-clipora-ravi-mehta coditect-gtm-customer-clipora
gh repo rename coditect-ai/product-legitimacy-enterprise-software coditect-gtm-legitimacy

Acceptance: All GTM repos renamed

3.8 Rename Labs Repos (14)

Agent: codi-devops-engineer Duration: 20 min Dependencies: Phase 2 complete

Acceptance: All labs repos renamed

Phase 4: Repo Transfers (Day 3 - 30 min)

4.1 Transfer halcasteel repos to coditect-ai

Agent: codi-devops-engineer Duration: 15 min Dependencies: Phase 3 complete

gh repo transfer halcasteel/coditect coditect-ai
gh repo transfer halcasteel/coditect-competition coditect-ai
gh repo transfer halcasteel/coditect-core-1.0 coditect-ai (if needed)

Acceptance: Repos visible in coditect-ai org

4.2 Rename transferred repos

Agent: codi-devops-engineer Duration: 10 min Dependencies: 4.1

gh repo rename coditect-ai/coditect coditect-ops-distribution
gh repo rename coditect-ai/coditect-competition coditect-gtm-competition
gh repo rename coditect-ai/coditect-license-manager coditect-ops-license

Acceptance: Transferred repos follow naming convention

Phase 5: Submodule Restructure (Day 3-4 - 1.5 hours)

5.1 Create folder structure

Agent: codi-devops-engineer Duration: 10 min Dependencies: Phase 4 complete

Acceptance: All 8 category folders exist

5.2 Remove existing submodules

Agent: codi-devops-engineer Duration: 30 min Dependencies: 5.1

Record all current submodule URLs
Run git submodule deinit -f --all
Remove submodule entries from .gitmodules
Remove submodule directories
Clean .git/modules

Acceptance: No submodules registered, clean state

5.3 Re-add core submodules

Agent: codi-devops-engineer Duration: 10 min Dependencies: 5.2

git submodule add https://github.com/coditect-ai/coditect-core submodules/core/coditect-core
git submodule add https://github.com/coditect-ai/coditect-core-framework submodules/core/coditect-core-framework
git submodule add https://github.com/coditect-ai/coditect-core-architecture submodules/core/coditect-core-architecture

Acceptance: Core submodules in submodules/core/

5.4 Re-add cloud submodules

Agent: codi-devops-engineer Duration: 10 min Dependencies: 5.2

Add coditect-cloud-backend to submodules/cloud/
Add coditect-cloud-frontend to submodules/cloud/
Add coditect-cloud-ide to submodules/cloud/
Add coditect-cloud-infra to submodules/cloud/
Add coditect-cloud-foundationdb to submodules/cloud/

Acceptance: Cloud submodules in submodules/cloud/

5.5 Re-add dev submodules

Agent: codi-devops-engineer Duration: 15 min Dependencies: 5.2

Add all 9 dev repos to submodules/dev/

Acceptance: Dev submodules in submodules/dev/

5.6 Re-add market submodules

Agent: codi-devops-engineer Duration: 5 min Dependencies: 5.2

Add all 3 market repos to submodules/market/

Acceptance: Market submodules in submodules/market/

5.7 Re-add docs submodules

Agent: codi-devops-engineer Duration: 10 min Dependencies: 5.2

Add all 5 docs repos to submodules/docs/

Acceptance: Docs submodules in submodules/docs/

5.8 Re-add ops submodules

Agent: codi-devops-engineer Duration: 5 min Dependencies: 5.2

Add all 3 ops repos to submodules/ops/

Acceptance: Ops submodules in submodules/ops/

5.9 Re-add gtm submodules

Agent: codi-devops-engineer Duration: 10 min Dependencies: 5.2

Add all 7 gtm repos to submodules/gtm/

Acceptance: GTM submodules in submodules/gtm/

5.10 Re-add labs submodules

Agent: codi-devops-engineer Duration: 15 min Dependencies: 5.2

Add all 14 labs repos to submodules/labs/

Acceptance: Labs submodules in submodules/labs/

5.11 Update communications submodule

Agent: codi-devops-engineer Duration: 5 min Dependencies: 5.2

Move communications from root to submodules/gtm/coditect-gtm-comms

Acceptance: No submodules at root level (except .coditect)

Phase 6: Reference Updates (Day 4-5 - 2 hours)

6.1 Update install.sh

Agent: codi-devops-engineer Duration: 20 min Dependencies: Phase 5 complete

Update CODITECT_REPO URL to coditect-ai/coditect-ops-distribution
Update raw.githubusercontent.com URLs
Test URL accessibility
Commit changes

Acceptance: install.sh uses new URLs

6.2 Update update.sh

Agent: codi-devops-engineer Duration: 10 min Dependencies: Phase 5 complete

Update all GitHub URLs
Test URL accessibility
Commit changes

Acceptance: update.sh uses new URLs

6.3 Bulk update CLAUDE.md files

Agent: codi-devops-engineer Duration: 30 min Dependencies: Phase 5 complete

Find all CLAUDE.md files in submodules
Search/replace old repo names with new
Verify no broken references
Commit changes

Acceptance: All CLAUDE.md files updated

6.4 Bulk update README.md files

Agent: codi-documentation-writer Duration: 30 min Dependencies: Phase 5 complete

Find all README.md files
Update GitHub links to new repo names
Update any architecture diagrams
Commit changes

Acceptance: All README links valid

6.5 Update CI/CD workflows

Agent: codi-devops-engineer Duration: 30 min Dependencies: Phase 5 complete

Find all .github/workflows/*.yml files
Update repo name references
Update checkout actions
Test workflow syntax

Acceptance: All workflows use new names

6.6 Update main docs/

Agent: codi-documentation-writer Duration: 20 min Dependencies: Phase 5 complete

Update all docs/*.md files
Fix any internal links
Update diagrams if needed

Acceptance: Documentation links valid

Phase 7: Testing & Validation (Day 5 - 1 hour)

7.1 Fresh clone test

Agent: codi-test-engineer Duration: 15 min Dependencies: Phase 6 complete

Clone coditect-ops-master with --recurse-submodules
Verify all 49 submodules initialize
Check submodule paths are correct

Acceptance: Fresh clone works perfectly

7.2 Submodule validation

Agent: codi-test-engineer Duration: 15 min Dependencies: 7.1

Run git submodule status - all should show clean
Verify each category folder has correct repos
Check symlinks (.coditect → .claude)

Acceptance: All submodules functional

7.3 Install script test

Agent: codi-test-engineer Duration: 15 min Dependencies: Phase 6 complete

Run install.sh in clean environment
Verify it downloads from correct URL
Check installation completes successfully

Acceptance: install.sh functional

7.4 Link validation

Agent: codi-test-engineer Duration: 10 min Dependencies: Phase 6 complete

Check all GitHub links in README.md
Verify old URLs redirect properly
Test external documentation links

Acceptance: Zero broken links

7.5 Redirect validation

Agent: codi-test-engineer Duration: 5 min Dependencies: Phase 3 complete

Test old repo URLs redirect to new names
Verify halcasteel/coditect redirects to coditect-ai/coditect-ops-distribution

Acceptance: All redirects working

Phase 8: Documentation & Communication (Day 5-6 - 1 hour)

8.1 Update main README.md

Agent: codi-documentation-writer Duration: 20 min Dependencies: Phase 7 complete

Update submodule structure section
Add new folder organization
Update getting started instructions
Update clone commands

Acceptance: README reflects new structure

8.2 Create REPO-NAMING-CONVENTION.md

Agent: codi-documentation-writer Duration: 15 min Dependencies: Phase 7 complete

Document 8 category prefixes
Provide examples for each category
Add rules for new repo creation
Include decision tree for categorization

Acceptance: Convention documented for future use

8.3 Update CLAUDE.md

Agent: codi-documentation-writer Duration: 15 min Dependencies: Phase 7 complete

Update all submodule paths
Update architecture diagrams
Add new folder structure

Acceptance: CLAUDE.md accurate

8.4 Create migration guide

Agent: codi-documentation-writer Duration: 10 min Dependencies: Phase 7 complete

Instructions for users with existing clones
How to update remotes
How to re-sync submodules

Acceptance: Migration guide available

Completion Checklist

Final Validation

Commit & Push

Commit all changes with comprehensive message
Push to main branch
Tag release: v2.0.0-reorganized
Create GitHub release notes

Agent Invocation Quick Reference

Execute Full Reorganization

Task(
    subagent_type="orchestrator",
    prompt="Execute repository reorganization following docs/TASKLIST-REPO-REORGANIZATION.md phases 1-8"
)

Execute Single Phase

Task(
    subagent_type="codi-devops-engineer",
    prompt="Execute Phase 3 (GitHub Renames) from docs/TASKLIST-REPO-REORGANIZATION.md"
)

Validate Results

Task(
    subagent_type="codi-test-engineer",
    prompt="Validate repository reorganization per Phase 7 of docs/TASKLIST-REPO-REORGANIZATION.md"
)

Generated: 2025-11-19 Total Tasks: 102 Estimated Time: 11.5 hours Categories: 8 Repos: 49

TASKLIST-SKILLS-STANDARDIZATION.md

Overview

Detailed checkbox tasklist for standardizing all 21 CODITECT skills to the format specified in skills/README.md.

Skills Location: /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/skills/

Phase 1: Audit (Agent: qa-reviewer)

Estimated Time: 2-3 hours Objective: Complete assessment of all 21 skills

Global Audit Tasks

Read skills/README.md to understand complete standard
Create audit spreadsheet template
Document all findings in standardized format

Phase 1: Individual Skill Audits

1. ai-curriculum-development

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Note: NOT in REGISTRY.json - needs addition
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

2. build-deploy-workflow

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

3. code-analysis-planning-editor

Priority: CRITICAL | Time Estimate: 15 min

Check for SKILL.md (KNOWN ISSUE: file is named CODE_EDITOR_SKILL.md)
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Note: NOT in REGISTRY.json - needs addition
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: Wrong filename (CODE_EDITOR_SKILL.md)

4. code-editor

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

5. communication-protocols

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

6. cross-file-documentation-update

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

7. deployment-archeology

Priority: CRITICAL | Time Estimate: 15 min

Verify SKILL.md exists
Verify YAML frontmatter has name field (KNOWN ISSUE: missing frontmatter)
Verify YAML frontmatter has description field (KNOWN ISSUE: missing frontmatter)
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Note: NOT in REGISTRY.json - needs addition
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: Missing YAML frontmatter

8. document-skills

Priority: High | Time Estimate: 20 min

Note: Contains subdirectories (docx, pdf, pptx, xlsx)

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

9. evaluation-framework

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

10. foundationdb-queries

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

11. framework-patterns

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

12. gcp-resource-cleanup

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

13. git-workflow-automation

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

14. google-cloud-build

Priority: CRITICAL | Time Estimate: 15 min

Verify SKILL.md exists
Verify YAML frontmatter has name field (KNOWN ISSUE: missing frontmatter)
Verify YAML frontmatter has description field (KNOWN ISSUE: missing frontmatter)
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Note: NOT in REGISTRY.json - needs addition
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: Missing YAML frontmatter

15. internal-comms

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

16. multi-agent-workflow

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

17. notebooklm-content-optimization

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Note: NOT in REGISTRY.json - needs addition
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

18. production-patterns

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

19. rust-backend-patterns

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

20. search-strategies

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

21. token-cost-tracking

Priority: Medium | Time Estimate: 10 min

Verify SKILL.md exists
Verify YAML frontmatter has name field
Verify YAML frontmatter has description field
Check "When to Use" section exists
Check "Core Capabilities" section exists
Check "Examples" section exists
Check "Guidelines/Best Practices" section exists
Verify REGISTRY.json entry is accurate
Document audit findings

Audit Status: [ ] Pass [ ] Fail - Issues: _________________

Phase 1: Audit Summary

Compile all audit findings
Categorize by severity (Critical/Major/Minor)
Create prioritized fix list
Estimate total fix time
Hand off to Phase 2

Total Phase 1 Estimated Time: 3 hours

Phase 2: Fix (Agent: codi-documentation-writer)

Estimated Time: 4-6 hours Objective: Remediate all compliance issues

Critical Fixes (P0 - Must Complete First)

Fix 3.1: code-analysis-planning-editor - Rename SKILL.md

Time Estimate: 15 min

Read current CODE_EDITOR_SKILL.md content
Rename file to SKILL.md
Verify YAML frontmatter format
Add missing sections if any
Test file is recognized

Fix 7.1: deployment-archeology - Add YAML Frontmatter

Time Estimate: 15 min

Read current SKILL.md content

Add YAML frontmatter:

---
name: deployment-archeology
description: Find and restore previous successful deployment configurations by analyzing git history, Cloud Build logs, and Kubernetes deployments. Use when current deployment is failing and need to find what worked before.
---

Verify sections are complete
Add missing sections if needed

Fix 14.1: google-cloud-build - Add YAML Frontmatter

Time Estimate: 15 min

Read current SKILL.md content

Add YAML frontmatter:

---
name: google-cloud-build
description: Successfully build and deploy Coditect modules (backend, frontend+Theia combined) to Google Cloud Platform using Cloud Build. Use when deploying to GKE or troubleshooting build failures.
---

Verify sections are complete
Add missing sections if needed

Major Fixes (P1 - Required for Compliance)

For each skill failing audit, complete these tasks:

Generic Section Fix Template

Time Estimate: 10-20 min per skill

Add "When to Use" section if missing
- Include scenarios with bullet points
- Add "don't use when" guidance
Add "Core Capabilities" section if missing
- List main features/capabilities
- Include code examples where relevant
Add "Examples" section if missing
- Provide concrete usage examples
- Include command-line examples
- Add code snippets
Add "Guidelines/Best Practices" section if missing
- Add "Do this" items with checkmarks
- Add "Avoid this" items with X marks
- Include common pitfalls

REGISTRY.json Updates (P1 - Required)

Time Estimate: 30 min total

Read current REGISTRY.json

Add entry for ai-curriculum-development:

{
  "name": "ai-curriculum-development",
  "path": ".claude/skills/ai-curriculum-development/SKILL.md",
  "description": "Comprehensive AI curriculum development with multi-level content generation, assessment creation, and NotebookLM optimization.",
  "tags": ["education", "curriculum", "ai-learning", "multi-level", "assessment"],
  "version": "1.0.0",
  "status": "production",
  "use_cases": [
    "multi-level content creation (beginner through expert)",
    "assessment-integrated learning design",
    "notebooklm optimization for ai-powered content"
  ]
}

Add entry for code-analysis-planning-editor:

{
  "name": "code-analysis-planning-editor",
  "path": ".claude/skills/code-analysis-planning-editor/SKILL.md",
  "description": "Code analysis, planning, and editing workflows for systematic code improvements.",
  "tags": ["code-analysis", "planning", "editing"],
  "version": "1.0.0",
  "status": "production",
  "use_cases": [
    "analyzing code for improvements",
    "planning code changes",
    "systematic editing workflows"
  ]
}

Add entry for deployment-archeology:

{
  "name": "deployment-archeology",
  "path": ".claude/skills/deployment-archeology/SKILL.md",
  "description": "Find and restore previous successful deployment configurations by analyzing git history, Cloud Build logs, and Kubernetes deployments.",
  "tags": ["deployment", "git-history", "cloud-build", "kubernetes", "recovery"],
  "version": "1.0.0",
  "status": "production",
  "use_cases": [
    "current deployment failing, need to find what worked before",
    "investigating deployment regressions",
    "recovering from accidental configuration changes"
  ]
}

Add entry for document-skills:

{
  "name": "document-skills",
  "path": ".claude/skills/document-skills/",
  "description": "Document manipulation skills for docx, pdf, pptx, and xlsx files. Contains sub-skills for each document type.",
  "tags": ["documents", "docx", "pdf", "pptx", "xlsx", "office"],
  "version": "1.0.0",
  "status": "production",
  "use_cases": [
    "creating and editing Word documents",
    "generating PDF reports",
    "building PowerPoint presentations",
    "manipulating Excel spreadsheets"
  ]
}

Add entry for google-cloud-build:

{
  "name": "google-cloud-build",
  "path": ".claude/skills/google-cloud-build/SKILL.md",
  "description": "Successfully build and deploy Coditect modules to GCP using Cloud Build. Covers backend API (Rust) and combined frontend+Theia deployments.",
  "tags": ["deployment", "gcp", "cloud-build", "gke", "docker"],
  "version": "1.0.0",
  "status": "production",
  "use_cases": [
    "deploying backend api (rust/actix-web) to gke",
    "deploying combined frontend+theia to gke",
    "troubleshooting cloud build failures",
    "optimizing build times and upload sizes"
  ]
}

Add entry for notebooklm-content-optimization:

{
  "name": "notebooklm-content-optimization",
  "path": ".claude/skills/notebooklm-content-optimization/SKILL.md",
  "description": "Optimize educational content for Google NotebookLM processing, book generation, quiz creation, and flashcard development.",
  "tags": ["notebooklm", "ai-optimization", "content-formatting", "metadata", "adaptive-learning"],
  "version": "1.0.0",
  "status": "production",
  "use_cases": [
    "preparing content for notebooklm processing",
    "optimizing for ai-powered book generation",
    "adding rich metadata for ai understanding",
    "building knowledge graphs and cross-references"
  ]
}

Validate JSON syntax (use JSON linter)
Update version timestamp in REGISTRY.json header
Save and commit

Minor Fixes (P2 - Quality Improvements)

Time Estimate: As time permits

For each skill:

Improve clarity of descriptions
Add more concrete examples
Ensure consistent formatting
Add cross-references to related skills
Check spelling and grammar

Git Commit

Stage all modified files

Create commit message:

chore(skills): Standardize all 21 skills to format specification

- Rename CODE_EDITOR_SKILL.md to SKILL.md in code-analysis-planning-editor
- Add YAML frontmatter to deployment-archeology and google-cloud-build
- Add missing sections to non-compliant skills
- Update REGISTRY.json with all 21 skills (added 6 missing entries)
- Ensure all skills have: When to Use, Core Capabilities, Examples, Guidelines

Resolves skills standardization initiative

Push to repository

Total Phase 2 Estimated Time: 6 hours

Phase 3: Validate (Agent: qa-reviewer)

Estimated Time: 1-2 hours Objective: Verify all fixes are correct and complete

Validation Tasks

Re-Audit All Skills

Run quick compliance check on all 21 skills
Verify each has valid SKILL.md filename
Verify each has YAML frontmatter with name/description
Verify each has 4 required sections

REGISTRY.json Validation

Verify JSON syntax is valid
Confirm all 21 entries present
Verify all paths are correct
Check version is updated

Functional Testing

Test skill loading in Claude Code session
Verify skills appear in skill list
Test one skill invocation

Documentation Updates

Update skills/README.md if needed
Update any references in main CLAUDE.md
Note completion in SKILL-ENHANCEMENT-LOG.md

Final Sign-Off

Total Phase 3 Estimated Time: 2 hours

Summary Statistics

Time Estimates

Phase	Estimated Time
Phase 1: Audit	3 hours
Phase 2: Fix	6 hours
Phase 3: Validate	2 hours
Total	11 hours

Critical Issues Count

Issue Type	Count	Skills Affected
Wrong filename	1	code-analysis-planning-editor
Missing YAML	2	deployment-archeology, google-cloud-build
Missing from REGISTRY	6	ai-curriculum-development, code-analysis-planning-editor, deployment-archeology, document-skills, google-cloud-build, notebooklm-content-optimization

Success Metrics

21/21 skills have SKILL.md (100%)
21/21 skills have YAML frontmatter (100%)
21/21 skills have required sections (100%)
21/21 skills in REGISTRY.json (100%)
0 audit failures in final validation

Execution Notes

Agent Invocation Pattern

To execute this tasklist with agents:

# Phase 1 - Audit
Task(
    subagent_type="general-purpose",
    prompt="Use qa-reviewer subagent to audit all 21 skills in /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/skills/ against the standard in README.md. Complete all Phase 1 tasks in TASKLIST-SKILLS-STANDARDIZATION.md"
)

# Phase 2 - Fix
Task(
    subagent_type="general-purpose",
    prompt="Use codi-documentation-writer subagent to fix all compliance issues identified in Phase 1. Complete all Phase 2 tasks in TASKLIST-SKILLS-STANDARDIZATION.md including REGISTRY.json updates"
)

# Phase 3 - Validate
Task(
    subagent_type="general-purpose",
    prompt="Use qa-reviewer subagent to validate all fixes and complete Phase 3 tasks in TASKLIST-SKILLS-STANDARDIZATION.md"
)

Progress Tracking

Update this section as tasks complete:

Phase 1 Start: _______________
Phase 1 Complete: _______________
Phase 2 Start: _______________
Phase 2 Complete: _______________
Phase 3 Start: _______________
Phase 3 Complete: _______________
Project Complete: _______________

Document Version: 1.0 Created: 2025-11-19 Author: Orchestrator Agent Status: Ready for Execution

Sprint +1: MEMORY-CONTEXT Implementation - Task List

Sprint: Sprint +1: MEMORY-CONTEXT Implementation Repository: coditect-core Duration: 2 weeks (10 business days) Start Date: 2025-11-18 Target Completion: 2025-11-29 Status: 📋 PLANNED - Ready to Begin

Overview

This task list tracks the implementation of the MEMORY-CONTEXT system with checkboxes for daily progress tracking. Each task includes time estimates and acceptance criteria.

Legend:

[ ] Not started
[~] In progress
[x] Complete
[!] Blocked

Week 1: Core Infrastructure (Days 1-5)

Day 1: Session Export Engine (8 hours) ✅ COMPLETE

Goal: Automated session context capture

Setup project structure (1h)
- Create scripts/core/ directory
- Add __init__.py files
- Setup imports and dependencies
- Acceptance: Directory structure matches project plan ✅
Create session_export.py framework (1h)
- SessionExporter class skeleton
- Configuration loading
- Logging setup
- Acceptance: Script runs without errors ✅
Implement conversation extraction (2h)
- Parse conversation history
- Extract user messages and AI responses
- Capture timestamps
- Acceptance: Can extract conversation from checkpoint ✅
Add metadata generation (1h)
- Timestamp (ISO-DATETIME)
- Participants (user, AI agents used)
- Session objectives
- Tags and categories
- Acceptance: Metadata JSON validates against schema ✅
Implement file change tracking (2h)
- Git diff parsing
- Changed file list
- Line-level changes
- Acceptance: Captures all modified files since last checkpoint ✅
Add decision logging (1h)
- Extract decision points from conversation
- Capture rationale
- Link to related files/code
- Acceptance: Decisions extracted and structured correctly ✅
Write unit tests (2h)
- 16 comprehensive unit tests
- 100% test pass rate
- Edge case coverage
- Acceptance: All tests passing ✅

Day 1 Deliverable: Working session export script ✅ Commit: 0a72883 - Day 1 Complete: Session Export Engine Date Completed: 2025-11-16

Day 2: Privacy Control Manager (8 hours) ✅ COMPLETE

Goal: 4-level privacy model with PII protection

Create privacy_manager.py framework (1h)
- PrivacyManager class
- Privacy level enum (PUBLIC, TEAM, PRIVATE, EPHEMERAL)
- Configuration loading from privacy.config.json
- Acceptance: Script structure complete ✅
Implement 4-level privacy model (1h)
- PUBLIC: Can be shared publicly, no PII
- TEAM: Internal team sharing, minimal PII
- PRIVATE: Restricted access, full PII allowed
- EPHEMERAL: Never stored, session-only
- Acceptance: Privacy levels defined and documented ✅
Add PII detection using regex patterns (2h)
- Detect EMAIL, PHONE, SSN, CREDIT_CARD, IP_ADDRESS
- Detect API_KEY, AWS_KEY, PASSWORD
- Detect all 6 GITHUB token types (ghp_, github_pat_, gho_, ghu_, ghs_, ghr_)
- Pattern matching for common PII formats
- Acceptance: Detects 100% of critical credentials in test cases ✅
Implement automatic redaction (2h)
- Replace detected PII with [REDACTED-TYPE]
- Preserve format (e.g., j***@example.com for emails)
- Configurable redaction strategies (preserve_format, preserve_domain)
- Acceptance: All PII redacted in test cases (34/34 tests passing) ✅
Create privacy configuration system (1h)
- Privacy config in MEMORY-CONTEXT/privacy.config.json
- Default levels and auto-redact settings
- PII types configuration
- Acceptance: Configuration system operational ✅
CRITICAL: Security vulnerability fix (2h)
- Fixed GitHub token detection (was leaking 31-char tokens)
- Added all 6 GitHub token types with 20+ char minimum
- Deep security testing with comprehensive test suite
- Acceptance: ZERO critical leaks verified (test_privacy_deep.py) ✅

Day 2 Deliverable: Privacy control system operational ✅ Commit: Multiple commits - Final: afcc2cf - FEATURE: Make --auto-push the DEFAULT behavior for checkpoints Date Completed: 2025-11-16 Test Results: 34/34 passing (100%), Zero critical leaks

Day 3: Database Schema & Setup (8 hours) ✅ COMPLETE

Goal: Persistent storage for sessions and patterns

Design SQLite schema (2h)
- Sessions table (id, session_id, timestamp, privacy_level, metadata, content)
- Patterns table (id, pattern_id, type, content, frequency, last_used)
- Tags table (many-to-many with sessions and patterns)
- Checkpoints table (links to sessions and git commits)
- Additional tables: context_loads, privacy_audit, db_metadata
- 4 views for common queries (active sessions, patterns by usage, etc.)
- Acceptance: Schema designed and documented ✅
Create database initialization scripts (2h)
- db_init.py - Create tables with full schema validation
- db_seed.py - Add comprehensive sample data (tags, checkpoints, sessions, patterns)
- Version tracking via db_metadata table
- Test data: 21 tags, 2 checkpoints, 3 sessions, 3 patterns
- Acceptance: Database initializes without errors (188 KB database created) ✅
Setup ChromaDB for vector storage (2h)
- ChromaDB client configuration with persistent storage
- Collection creation (sessions, patterns) with cosine similarity
- Embedding generation using sentence-transformers/all-MiniLM-L6-v2
- Sample embeddings and similarity search testing
- Acceptance: ChromaDB stores and retrieves embeddings ✅
Implement database migrations (1h)
- Alembic setup with db_migrate.py script
- alembic.ini configuration auto-generated
- Migration commands: init, upgrade, downgrade, current, history
- Version tracking integrated
- Acceptance: Migrations framework operational ✅
Add database backup/restore utilities (1h)
- db_backup.py - Comprehensive backup script (SQLite + ChromaDB)
- Restore script with safety backups before restore
- List and cleanup commands for backup management
- Backup metadata tracking
- Acceptance: Backup and restore work correctly (tested successfully) ✅

Day 3 Deliverable: Database infrastructure operational ✅ Commit: TBD - Day 3 checkpoint pending Date Completed: 2025-11-16 Deliverables:

database-schema.sql (540 lines, 9 tables, 4 views)
db_init.py (working database initialization)
db_seed.py (sample data seeding)
chromadb_setup.py (vector storage setup)
db_migrate.py (Alembic migrations)
db_backup.py (backup and restore)
memory-context.db (188 KB with sample data)
Backup system tested and working

Day 4: NESTED LEARNING Processor (Part 1) (8 hours) ✅ COMPLETE

Goal: Pattern extraction and knowledge graph

Create nested_learning.py framework (1h)
- NestedLearningProcessor class with full extraction pipeline
- Pattern types enum (workflow, decision, code, error, architecture, configuration)
- Configuration loading from JSON with intelligent defaults
- Pattern dataclasses (Pattern, WorkflowPattern, DecisionPattern, CodePattern)
- Acceptance: Framework structure complete ✅
Implement workflow pattern recognition (2h)
- Detect common task sequences from conversation
- Extract workflow templates with steps
- Identify action verbs (create, update, delete, test, deploy, review)
- Generate descriptive workflow names
- Acceptance: Extracts workflow patterns from test sessions ✅
Add decision pattern extraction (2h)
- Identify decision points from session decisions
- Extract decision criteria with alternatives considered
- Capture outcomes and rationale
- Create decision templates
- Acceptance: Decision patterns structured correctly ✅
Implement knowledge graph schema (2h)
- Pattern relationships tracked in database
- Related patterns JSON storage
- Source session linkage
- Pattern versioning (parent_pattern_id, version number)
- Similarity-based pattern merging
- Acceptance: Knowledge graph stores and queries patterns ✅
Implement similarity scoring (1h)
- Jaccard similarity for token overlap (60% weight)
- Levenshtein edit distance normalized (40% weight)
- Combined weighted scoring (0.0 to 1.0)
- Configurable similarity threshold (default: 0.7)
- Acceptance: Similarity scores validated with unit tests ✅

Day 4 Deliverable: Pattern extraction working ✅ Commit: TBD - Day 4 checkpoint pending Date Completed: 2025-11-16 Deliverables:

nested_learning.py (850 lines, 4 extractor classes)
test_nested_learning.py (435 lines, 16 unit tests)
nested-learning.config.json (auto-generated configuration)
3 pattern extractors: WorkflowPatternExtractor, DecisionPatternExtractor, CodePatternExtractor
Pattern library with 6 patterns stored (3 seed + 3 test)
All 16/16 tests passing (100%)

Day 5: Week 1 Integration & Testing (8 hours)

Goal: Integration and Week 1 checkpoint

Integrate session export with checkpoint script (2h)
- Modify create_checkpoint.py to call session export
- Add session export to checkpoint workflow
- Error handling
- Acceptance: Checkpoint creation auto-exports session
End-to-end test: checkpoint → export → database (2h)
- Create test checkpoint
- Verify session exported
- Verify stored in database
- Verify privacy controls applied
- Acceptance: Full pipeline works end-to-end
Add privacy controls to session export (1h)
- Auto-detect PII in session content
- Apply redaction
- Tag with privacy level
- Acceptance: Exported sessions have PII redacted
Write MEMORY-CONTEXT-architecture.md (2h)
- System overview
- Component descriptions
- Data flow diagrams
- Privacy model documentation
- Acceptance: Architecture doc complete and reviewed
Code review and refactoring (1h)
- Review all Week 1 code
- Refactor for clarity
- Add docstrings
- Acceptance: Code meets quality standards

Day 5 Deliverable: Week 1 checkpoint and integration complete

Week 2: Intelligence & Optimization (Days 6-10)

Day 6: NESTED LEARNING Processor (Part 2) (8 hours)

Goal: Code patterns and incremental learning

Implement code pattern extraction (2h)
- Detect common code structures
- Extract reusable code templates
- Identify anti-patterns
- Acceptance: Code patterns extracted from test repos
Add pattern library management (2h)
- Pattern CRUD operations
- Pattern search and filtering
- Pattern versioning
- Acceptance: Pattern library stores and retrieves patterns
Create incremental learning pipeline (2h)
- Add new patterns without overwriting old
- Merge similar patterns
- Update pattern frequencies
- Acceptance: New sessions update pattern library correctly
Implement pattern versioning (1h)
- Version tracking for patterns
- Diff between versions
- Rollback capability
- Acceptance: Pattern versions tracked correctly
Add pattern conflict resolution (1h)
- Detect conflicting patterns
- Merge strategies
- User notification for manual resolution
- Acceptance: Conflicts detected and resolved

Day 6 Deliverable: NESTED LEARNING fully operational

Day 7: Context Loader (8 hours)

Goal: Intelligent context retrieval for new sessions

Create context_loader.py framework (1h)
- ContextLoader class
- Configuration loading
- Token budget management
- Acceptance: Framework structure complete
Implement relevance scoring (2h)
- Recency weighting (exponential decay)
- Similarity scoring (cosine similarity)
- Importance scoring (user ratings, reuse count)
- Combined scoring function
- Acceptance: Relevance scores match manual ranking
Add similarity search via ChromaDB (2h)
- Query ChromaDB with current context
- Retrieve top-k similar sessions
- Filter by privacy level
- Acceptance: Returns relevant sessions in < 2s
Create token budget manager (1h)
- Calculate token budget (e.g., 8000 tokens)
- Allocate tokens to highest-relevance contexts
- Truncate or summarize if needed
- Acceptance: Respects token budget
Implement progressive context loading (2h)
- Load most relevant contexts first
- Stream additional context as needed
- Cache loaded contexts
- Acceptance: Context loads in < 5s

Day 7 Deliverable: Context loader operational

Day 8: Token Optimizer (8 hours)

Goal: Compress context while preserving quality

Create token_optimizer.py framework (1h)
- TokenOptimizer class
- Compression strategies enum
- Configuration loading
- Acceptance: Framework structure complete
Implement semantic compression (2h)
- Summarize verbose content
- Extract key points
- Preserve critical details
- Acceptance: 30%+ token reduction with quality maintained
Add redundancy elimination (2h)
- Detect duplicate content
- Merge similar sections
- Remove boilerplate
- Acceptance: Removes duplicates without losing information
Create priority-based selection (1h)
- Prioritize high-value content
- Drop low-value filler
- Configurable priority weights
- Acceptance: Selected content matches priority criteria
Add cost tracking system (1h)
- Track tokens used vs. saved
- ROI calculation
- Cost reporting dashboard (CLI)
- Acceptance: Accurate token usage tracking
Implement A/B testing framework (1h)
- Test different compression strategies
- Measure quality vs. token reduction
- Statistical significance testing
- Acceptance: A/B tests run and report results

Day 8 Deliverable: Token optimizer working

Day 9: Integration & Polish (8 hours)

Goal: System integration and refinement

Full system integration test (2h)
- Test all components together
- End-to-end workflows
- Error handling
- Acceptance: Full system works without errors
Performance benchmarking (2h)
- Context load time (10, 100, 1000 sessions)
- Token reduction measurement
- Database query performance
- Memory usage profiling
- Acceptance: Meets performance targets (< 5s load, 40%+ reduction)
Error handling and edge cases (1h)
- Handle missing data
- Handle corrupted databases
- Handle API failures
- Graceful degradation
- Acceptance: All edge cases handled gracefully
CLI integration (2h)
- coditect memory export - Export session
- coditect memory load [--relevance 0.7] [--budget 8000] - Load context
- coditect memory search <query> - Search sessions
- coditect memory stats - Show statistics
- Acceptance: All CLI commands work
Write documentation (1h)
- NESTED-LEARNING-GUIDE.md
- PRIVACY-CONTROLS-SPEC.md
- Update README.md
- Acceptance: Documentation complete

Day 9 Deliverable: Integrated and polished system

Day 10: Final Testing & Documentation (8 hours)

Goal: User acceptance and deployment

End-to-end user acceptance testing (2h)
- Test from 3 different submodules
- Real-world usage scenarios
- User feedback collection
- Acceptance: UAT passes with 4/5+ rating
Performance validation (1h)
- Verify < 5s context load
- Verify 40%+ token reduction
- Verify 99%+ PII detection accuracy
- Acceptance: All performance targets met
Create user guides and API documentation (2h)
- MEMORY-CONTEXT-USER-GUIDE.md
- API-REFERENCE.md
- BEST-PRACTICES.md
- TROUBLESHOOTING.md
- Acceptance: User guides complete and clear
Update all README.md files (1h)
- Add MEMORY-CONTEXT features to main README
- Update submodule READMEs with usage examples
- Add links to documentation
- Acceptance: READMEs updated across all repos
Final code review (1h)
- Review all code for quality
- Ensure 80%+ test coverage
- Security audit
- Acceptance: Code review approved
Create Sprint +1 completion checkpoint (1h)
- Use create_checkpoint.py to create checkpoint
- Document all completed work
- Create MEMORY-CONTEXT export
- Update tasklist.md with completion markers
- Acceptance: Checkpoint created and committed

Day 10 Deliverable: Sprint +1 complete and ready for rollout

Post-Sprint Rollout (Week 3)

Deployment to All 19 Submodules

Test in 3 diverse submodules (4h)
- coditect-cloud-backend (Python backend)
- coditect-cloud-frontend (JavaScript frontend)
- coditect-cli (Python CLI)
- Acceptance: Works in all 3 submodules
Document any submodule-specific issues (2h)
- Create issue tracker
- Document workarounds
- Acceptance: Known issues documented
Create training materials (4h)
- Quick start guide (15 minutes)
- Demo script
- Video walkthrough
- Acceptance: Training materials ready
Conduct team training session (2h)
- Live demonstration
- Q&A session
- Hands-on practice
- Acceptance: Team trained and confident
Monitor usage and gather feedback (ongoing)
- Track usage metrics
- Collect user feedback
- Identify issues
- Acceptance: Feedback loop operational
Fix critical issues (as needed)
- Address blockers
- Quick bug fixes
- Acceptance: No P0 bugs blocking usage

Testing Checklist

Unit Tests (Target: 80%+ coverage)

Integration Tests

End-to-end: checkpoint → export → database → load
Privacy enforcement across all components
Database operations (SQLite + ChromaDB)
CLI integration

Performance Tests

Context load time: 10 sessions (target: < 2s)
Context load time: 100 sessions (target: < 5s)
Context load time: 1000 sessions (target: < 10s)
Token reduction (target: 40%+)
Memory usage (target: < 500MB)

Security Tests

PII detection accuracy (target: 99%+)
Privacy level enforcement (no unauthorized access)
SQL injection prevention
Access control audit log

Success Metrics Tracking

Metric	Target	Day 5	Day 10	Week 3
Session Export Time	< 10s	-	-	-
Context Load Time	< 5s	-	-	-
Token Reduction	40%+	-	-	-
Patterns Extracted	10+/week	-	-	-
PII Detection Accuracy	99%+	-	-	-
Test Coverage	80%+	-	-	-
User Rating	4/5+	-	-	-

Blockers & Issues

Track blockers here as they arise:

Date	Issue	Impact	Status	Resolution
-	-	-	-	-

Daily Standup Notes

Day 1 (2025-11-18)

Plan:

Setup project structure
Create session export framework
Implement conversation extraction

Completed:

(Fill in at end of day)

Blockers:

(Fill in if any)

Tomorrow:

(Plan for Day 2)

Day 2 (2025-11-19)

Plan:

Create privacy control framework
Implement PII detection
Add automatic redaction

Completed:

(Fill in at end of day)

Blockers:

(Fill in if any)

Tomorrow:

(Plan for Day 3)

(Continue for Days 3-10)

Sprint +1 Completion Checklist

Code Quality

Documentation

MEMORY-CONTEXT-architecture.md complete
NESTED-LEARNING-GUIDE.md complete
PRIVACY-CONTROLS-SPEC.md complete
TOKEN-OPTIMIZATION-GUIDE.md complete
API-REFERENCE.md complete
User guides complete
README.md files updated

Functionality

Deployment

Next Sprint Preview: Sprint +2

Potential features for Sprint +2:

Multi-user context sharing (team collaboration)
Cross-project pattern recognition
Context search web UI
Advanced token optimization (LLM-based)
Integration with agent orchestration system

Status: 📋 PLANNED - Ready to Begin Last Updated: 2025-11-16 Repository: https://github.com/coditect-ai/coditect-core Owner: AZ1.AI CODITECT Team

Overview​

Progress Summary​

Submodules Needing CLAUDE.md (25)​

core/ (1 missing)​

cloud/ (3 missing)​

dev/ (5 missing)​

docs/ (4 missing)​

ops/ (2 missing)​

gtm/ (5 missing)​

market/ (2 missing)​

labs/ (3 missing)​

Submodules with Existing CLAUDE.md (17)​

core/ (2)​

cloud/ (1)​

dev/ (4)​

docs/ (1)​

ops/ (1)​

gtm/ (1)​

labs/ (7)​

Parent Repository​

Next Steps​

TASKLIST: README Standardization

Overview​

Progress Summary​

Phase 1: Foundation (core/ & cloud/)​

core/ (3 repos)​

cloud/ (4 repos)​

Phase 2: Development Tools (dev/)​

Phase 3: Documentation & Operations (docs/ & ops/)​

docs/ (5 repos)​

ops/ (3 repos)​

Phase 4: Marketplace & Go-to-Market (market/ & gtm/)​

market/ (2 repos)​

gtm/ (6 repos)​

Phase 5: Labs & Research (labs/)​

Phase 6: Master Repository​

Verification Checklist​

Notes​

CODITECT Repository Reorganization - Tasklist

Progress Summary​

Phase 1: Preparation & Backup (Day 1 - 2 hours)​

1.1 Backup Current State​

1.2 Create Rollback Script​

1.3 Verify Permissions​

Phase 2: Consolidations & Merges (Day 1-2 - 2 hours)​

2.1 Merge coditect-installer → coditect​

2.2 Merge coditect-license-server → coditect-license-manager​

2.3 Merge competitive research​

Phase 3: GitHub Renames (Day 2-3 - 1.5 hours)​

3.1 Rename Core Repos (3)​

3.2 Rename Cloud Repos (5)​

3.3 Rename Dev Repos (9)​

3.4 Rename Market Repos (3)​

3.5 Rename Docs Repos (5)​

3.6 Rename Ops Repos (3)​

3.7 Rename GTM Repos (7)​

3.8 Rename Labs Repos (14)​

Phase 4: Repo Transfers (Day 3 - 30 min)​

4.1 Transfer halcasteel repos to coditect-ai​

4.2 Rename transferred repos​

Phase 5: Submodule Restructure (Day 3-4 - 1.5 hours)​

5.1 Create folder structure​

5.2 Remove existing submodules​

5.3 Re-add core submodules​

5.4 Re-add cloud submodules​

5.5 Re-add dev submodules​

5.6 Re-add market submodules​

5.7 Re-add docs submodules​

5.8 Re-add ops submodules​

5.9 Re-add gtm submodules​

5.10 Re-add labs submodules​

5.11 Update communications submodule​

Phase 6: Reference Updates (Day 4-5 - 2 hours)​

6.1 Update install.sh​

6.2 Update update.sh​

6.3 Bulk update CLAUDE.md files​

6.4 Bulk update README.md files​

6.5 Update CI/CD workflows​

6.6 Update main docs/​

Phase 7: Testing & Validation (Day 5 - 1 hour)​

Overview

Progress Summary

Submodules Needing CLAUDE.md (25)

core/ (1 missing)

cloud/ (3 missing)

dev/ (5 missing)

docs/ (4 missing)

ops/ (2 missing)

gtm/ (5 missing)

market/ (2 missing)

labs/ (3 missing)

Submodules with Existing CLAUDE.md (17)

core/ (2)

cloud/ (1)

dev/ (4)

docs/ (1)

ops/ (1)

gtm/ (1)

labs/ (7)

Parent Repository

Next Steps

Overview

Progress Summary

Phase 1: Foundation (core/ & cloud/)

core/ (3 repos)

cloud/ (4 repos)

Phase 2: Development Tools (dev/)

Phase 3: Documentation & Operations (docs/ & ops/)

docs/ (5 repos)

ops/ (3 repos)

Phase 4: Marketplace & Go-to-Market (market/ & gtm/)

market/ (2 repos)

gtm/ (6 repos)

Phase 5: Labs & Research (labs/)

Phase 6: Master Repository

Verification Checklist

Notes

Progress Summary

Phase 1: Preparation & Backup (Day 1 - 2 hours)

1.1 Backup Current State

1.2 Create Rollback Script

1.3 Verify Permissions

Phase 2: Consolidations & Merges (Day 1-2 - 2 hours)

2.1 Merge coditect-installer → coditect

2.2 Merge coditect-license-server → coditect-license-manager

2.3 Merge competitive research

Phase 3: GitHub Renames (Day 2-3 - 1.5 hours)

3.1 Rename Core Repos (3)

3.2 Rename Cloud Repos (5)

3.3 Rename Dev Repos (9)

3.4 Rename Market Repos (3)

3.5 Rename Docs Repos (5)

3.6 Rename Ops Repos (3)

3.7 Rename GTM Repos (7)

3.8 Rename Labs Repos (14)

Phase 4: Repo Transfers (Day 3 - 30 min)

4.1 Transfer halcasteel repos to coditect-ai

4.2 Rename transferred repos

Phase 5: Submodule Restructure (Day 3-4 - 1.5 hours)

5.1 Create folder structure

5.2 Remove existing submodules

5.3 Re-add core submodules

5.4 Re-add cloud submodules

5.5 Re-add dev submodules

5.6 Re-add market submodules

5.7 Re-add docs submodules

5.8 Re-add ops submodules

5.9 Re-add gtm submodules

5.10 Re-add labs submodules

5.11 Update communications submodule

Phase 6: Reference Updates (Day 4-5 - 2 hours)

6.1 Update install.sh

6.2 Update update.sh

6.3 Bulk update CLAUDE.md files

6.4 Bulk update README.md files

6.5 Update CI/CD workflows

6.6 Update main docs/

Phase 7: Testing & Validation (Day 5 - 1 hour)

7.1 Fresh clone test

7.2 Submodule validation