CODITECT Core Task List with Checkboxes

CODITECT Core - Task List with Checkboxes

Product: AZ1.AI CODITECT - Distributed Intelligence Framework Repository: coditect-core (Primary Product / CODITECT Brain) Status: Operational Foundation → Evolution to Full Autonomy Last Updated: December 17, 2025 (Merged Phase 0.7 from 04-MASTER-TASKLIST, V2 consolidation)

Overview

This TASKLIST tracks the operational status of all CODITECT Core components and the roadmap to achieving 100% autonomous operation. Tasks are organized by component and priority.

Legend:

✅ [x] - Completed and operational
🟡 [>] - In Progress (WIP)
⏸️ [ ] - Pending/Not Started
❌ [!] - Blocked/Issue Identified

Current Status: 78% Complete (Operational Foundation) + NEW FEATURES Nov 22 Target: 100% Autonomous Operation (Foundation phase 3 months away from full autonomy w/ hooks) Timeline: 20 weeks (Phases 1-4) + 7 weeks (Hooks Implementation)

Latest Additions (Nov 22, 2025):

✅ 2 New Agents (project-discovery-specialist, project-structure-optimizer)
✅ 4 New Commands (/new-project, /analyze-hooks, /web-search-hooks, /generate-project-plan-hooks)
✅ 4000+ lines of hooks analysis and planning documentation
✅ 2 New Submodule Management Skills
✅ +148 unique messages in MEMORY-CONTEXT system
⭐ NEW INITIATIVE: Memory Management System Design (Critical Infrastructure)
- Session memory extraction: 273,188+ messages recovered (Phases 1-2 complete)
- Comprehensive metadata assessment and project association analysis
- 4-tier architecture design (PostgreSQL + Meilisearch + Redis + S3 backup)
- Executive summary and submodule plan complete
- Timeline: 5 weeks implementation, 165% Year 1 ROI, break-even Month 7

Phase 0: Foundation (COMPLETE)
Phase 0.5: Hooks Implementation (NEW Nov 22)
Phase 0.6: Memory Management System (NEW Nov 22)
Phase 1: Foundation Infrastructure
Phase 2: Resilience & Recovery
Phase 3: Observability
Phase 4: Production Readiness
Phase 5: Universal Agents v2.0
Ongoing Maintenance

Phase 0: Foundation (COMPLETE) ✅

Status: 100% Complete and Operational Timeline: Completed November 2025

Agent System (all agents) ✅

Business Intelligence (6 agents):

venture-capital-business-analyst
competitive-market-analyst
business-intelligence-analyst
software-design-architect
software-design-document-specialist
ai-curriculum-specialist

Technical Development (see config/component-counts.json):

Research & Analysis (8 agents):

Quality Assurance (6 agents):

Project Management (5 agents):

Content & Documentation (4 agents):

educational-content-generator
assessment-creation-agent
codi-documentation-writer
senior-architect

AI Specialist (3 agents):

ai-specialist
orchestrator-detailed-backup
orchestrator (backup variant)

Command System (all commands) ✅

Research & Discovery (see config/component-counts.json):

Planning & Strategy (8 commands):

Development & Implementation (see config/component-counts.json):

Quality Assurance (9 commands):

Deployment & Operations (see config/component-counts.json):

Context Management (4 commands):

/context-save
/context-restore
/create-handoff
/resume-handoff

Educational (3 commands):

/generate-curriculum-content
/optimize-work-reuse
/notebooklm-optimize

Utility (see config/component-counts.json):

Skills Library (see config/component-counts.json) ✅

Development Skills:

code-editor (7 variations)
code-analysis-planning-editor (5 variations)
framework-patterns (5 variations)
rust-backend-patterns (3 variations)
production-patterns (5 variations)

Project Management Skills:

ai-curriculum-development (5 variations)
multi-agent-workflow (4 variations)
evaluation-framework (5 variations)

Infrastructure Skills:

build-deploy-workflow (4 variations)
google-cloud-build (3 variations)
foundationdb-queries (3 variations)
gcp-resource-cleanup (4 variations)
deployment-archeology (3 variations)

Communication Skills:

communication-protocols (5 variations)
internal-comms (5 variations)
document-skills (6 variations)
cross-file-documentation-update (4 variations)

Optimization Skills:

notebooklm-content-optimization (3 variations)
search-strategies (5 variations)
token-cost-tracking (4 variations)

Quality Skills:

git-workflow-automation (4 variations)

Asset Cataloging:

254+ reusable assets documented in skills/REGISTRY.json
Work reuse optimizer operational (13.8-27.6x ROI)
Token savings tracking implemented

MEMORY-CONTEXT System ✅

Core Components:

Session export with deduplication (80%+ reduction)
Checkpoint automation with git integration
Privacy manager (zero critical leaks verified)
NESTED LEARNING pattern extraction processor
Cascade push to master repository
6,400+ messages preserved and indexed

Features:

Content deduplication via hashing
Global hash tracking (global_hashes.json)
Unique message storage (unique_messages.jsonl)
Checkpoint index (checkpoint_index.json)
Export automation (<100ms execution time)
Session continuity across multiple sessions

Scripts:

export-dedup.sh (session export automation)
create-checkpoint.py (checkpoint creation)
privacy_manager.py (sensitive data redaction)
pattern_extractor.py (NESTED LEARNING processor)

Training System ✅

Training Materials (55,000+ words):

Live Demo Scripts:

demo-1-business-discovery.md (market research, value prop, PMF, GTM)
demo-2-technical-specification.md (C4 architecture, DB design, APIs)
demo-3-project-management.md (PROJECT-PLAN, TASKLIST, checkpoints)
demo-4-advanced-operations.md (MEMORY-CONTEXT, multi-session continuity)

Sample Templates:

Interactive Tools:

coditect-interactive-setup.py (automated environment setup)
Shell integration scripts (Bash, Zsh, Fish)

Installation System ✅

Installers:

GUI installer (install_gui.py) - tkinter-based, cross-platform
CLI installer (install.py) - Python-based, universal
Bash installer (install.sh) - Unix/Linux/macOS
Universal launcher (launch.py) - auto-detects platform

Features:

Platform detection (macOS, Linux, Windows)
Automated venv creation
Dependency installation (GitPython, etc.)
Verification and health checks
Next steps guidance
Modern GUI with progress tracking

Documentation:

scripts/installer/README.md (complete installation guide)
Troubleshooting section in main README.md

Documentation ✅

Core Documentation:

Architecture Documents (25 docs in docs/):

Diagrams:

diagrams/distributed-intelligence-architecture.md (5 Mermaid diagrams)
Visual architecture guide in training materials

Agent Documentation:

agents/README.md (agent catalog)
all agents specification files (agents/*.md)

Command Documentation:

commands/README.md (command catalog)
commands/COMMAND-GUIDE.md (decision trees)
all commands specification files (commands/*.md)

Skills Documentation:

skills/README.md (skills catalog)
skills/REGISTRY.json (254+ assets)
skills/SKILL-ENHANCEMENT-LOG.md (enhancement tracking)
24 skill family directories with documentation

New Agents (Nov 22) ⭐

project-discovery-specialist - Interactive discovery interviews with requirement gathering
project-structure-optimizer - Production-ready directory structure generation

New Commands (Nov 22) ⭐

Project Creation (1 command):

/new-project - Complete project initialization workflow

Hooks Implementation (3 commands):

/analyze-hooks - Assess CODITECT readiness for hooks automation
/web-search-hooks - Research industry best practices and patterns
/generate-project-plan-hooks - Create implementation roadmap

Phase 1C: Multi-Provider LLM Integration (COMPLETE) ✅ Nov 23, 2025

Timeline: Completed November 23, 2025 Priority: P0 (Critical - Foundation for Autonomous Operation) Status: 100% Complete - All 7 Providers Operational Achievement: 7 multi-provider LLM integrations, 44/44 tests passing, 75% coverage

Core Architecture (100% Complete)

Base Infrastructure

Create llm_abstractions package structure
Implement BaseLlm abstract base class (83% coverage)
Design unified message format (OpenAI-compatible)
Implement LlmFactory provider registry (78% coverage)
Add lazy loading for SDK imports
Create init.py with all exports

LLM Provider Implementations (7/7 Complete)

Provider 1: Anthropic Claude (79% coverage)

Implement AnthropicLlm class
AsyncAnthropic client integration
System message separation logic
Model support: claude-3-5-sonnet, claude-3-opus, claude-3-haiku
Error handling and validation
Unit tests (100% passing)

Provider 2: OpenAI GPT-4 (76% coverage)

Implement OpenAILlm class
AsyncOpenAI client integration
Model support: gpt-4, gpt-4o, o1-preview
Streaming support (infrastructure)
Error handling and validation
Unit tests (100% passing)

Provider 3: Google Gemini (73% coverage)

Implement Gemini class
GenerativeModel integration
Model support: gemini-pro, gemini-pro-vision
Safety filter configuration
Error handling and validation
Unit tests (100% passing)

Provider 4: Hugging Face (74% coverage)

Provider 5: Ollama Local (69% coverage)

Implement OllamaLlm class
HTTP API integration via aiohttp
Model support: llama3.2, mistral, codellama, etc.
Configurable base_url (default: localhost:11434)
No API key requirement
Error handling and validation
Unit tests (100% passing)

Provider 6: LM Studio Local (75% coverage)

Implement LMStudioLlm class
OpenAI-compatible API integration
GGUF model support
Dummy API key acceptance (local inference)
Configurable base_url
Error handling and validation
Unit tests (100% passing)
CRITICAL FIX: Added api_key parameter to init

Provider 7: Search-Augmented LLM (31% coverage)

Implement SearchAugmentedLlm wrapper class
DuckDuckGo search integration
Auto-detection of queries needing current info
Configurable search triggers and result count
Context injection into prompts
Error handling and validation
Basic unit tests (needs more coverage)

TaskExecutor Integration (100% Complete)

Integrate LlmFactory into orchestration/executor.py
Implement graceful fallback to script-based execution
Add metadata tracking (provider, model, execution_method)
CRITICAL FIX: Handle both enum and string agent types
CRITICAL FIX: Add completed_at timestamp for duration tracking
Test integration with all 7 providers
Verify fallback mechanism works

Testing Infrastructure (44/44 tests passing)

Test Suite 1: LlmFactory Tests (15 tests)

Test provider registration
Test provider instantiation
Test missing provider error handling
Test invalid API key error handling
Test configuration validation
All 15 tests passing

Test Suite 2: Provider Tests (17 tests)

Test Suite 3: Integration Tests (12 tests)

Package Configuration (100% Complete)

Create pyproject.toml for editable installation
Add all 6 LLM SDK dependencies to requirements.txt
Configure pytest with asyncio support
Setup coverage.py configuration
Install package in editable mode (pip install -e .)
Verify all imports work

Security (100% Complete)

Add *.key patterns to .gitignore
Add .env patterns to .gitignore
Add credentials/ patterns to .gitignore
Add hal-mac-os-anthropic.key to .gitignore
Verify API keys not tracked by git
Protect all secret patterns

Documentation (100% Complete)

Repository Organization (100% Complete)

Move PHASE-1C-* files to docs/06-research-analysis/completion-reports/
Create completion-reports index
Clean root directory
Commit all changes with proper messages
Verify git status clean

Bug Fixes Applied (8 fixes)

Fix 1: Package not installed - created pyproject.toml, installed editable
Fix 2: LMStudioLlm TypeError - added api_key parameter to init
Fix 3: Test mocking failures - patched actual SDK imports
Fix 4: AgentTask TypeError - added title and agent fields
Fix 5: Executor AttributeError - handle both enum and string agent types
Fix 6: Duration tracking - added completed_at timestamp
Fix 7: ValueError wrapping - factory wraps in RuntimeError
Fix 8: Missing API key tests - removed patches, cleared env

Phase 1C Success Criteria (All Met ✅)

Technical:

7 LLM providers production-ready
Unified interface across all providers
44/44 tests passing (100% pass rate)
75% average code coverage (professional quality)
TaskExecutor integration working
Graceful fallback to scripts

Documentation:

Comprehensive status report (30 pages)
Quick reference guide (6 pages)
Integration roadmap documented
Per-provider setup guides

Deliverables:

Cost Analysis (Completed)

Monthly cost estimate: ~$15/month for 1,000 tasks
Cost optimization strategies documented
Local inference options validated ($0 cost)
Cloud provider pricing analyzed

Next Steps (Phase 2 Integration)

Phase 2A: Agent-to-LLM Bindings (2-3 days) - PENDING

Design agent-llm-bindings.yaml schema
Create .claude/config/agent-llm-bindings.yaml
Map all all agents to specific LLM providers
Implement AgentLlmConfig loader
Test with 5-10 agents

Phase 2B: Slash Command Pipeline (3-4 days) - COMPLETE ✅

Phase 2B.1: REST API for Commands (2-3 days) - PENDING

Day 1: API Foundation

Day 2: Authentication & Rate Limiting

Design JWT authentication system
Implement API key generation and management
Add authentication middleware
Implement rate limiting (Redis-based)
- Per-user quotas
- Per-endpoint throttling
Add quota tracking and enforcement
Create admin endpoints for key management

Day 3: WebSocket & Documentation

Deliverables:

FastAPI application (api/main.py)
Authentication system (api/auth.py)
Rate limiting (api/rate_limit.py)
WebSocket handler (api/websocket.py)
Python SDK (api/client.py)
OpenAPI spec (api/openapi.json)
Integration tests (tests/test_api.py)
API documentation (docs/API.md)

Phase 2C: Skill Execution Pipeline (2-3 days) - PENDING

Convert skills to executable Python
Enable skill → agent invocation
Test skill execution
Document skill API

Phase 2D: Memory Integration (3-4 days) - PENDING

Phase 2E: Multi-Agent Orchestration (8-10 days) - PENDING

Requires Phase 1 Foundation Infrastructure (Message Bus, Agent Discovery, Task Queue)
Autonomous agent-to-agent communication
Full autonomous operation

Total Phase 2 Timeline: 20-26 days

Phase 0.5: Hooks Implementation (7 Weeks) ⭐ NEW Nov 22

Timeline: November 22, 2025 - January 10, 2026 (Can run in parallel with Phase 1) Priority: P1 (High - Productivity Multiplier for CODITECT) Status: Analysis & Planning Complete → Ready for Phase 1A Implementation Expected Benefit: 40-60% reduction in manual code reviews + automated compliance

Week 1-2: Phase 1A - Quick Wins (2 weeks)

Component Validation Hook (PreToolUse, Write)

Design hook schema for component validation
Implement Write tool interception
Add STANDARDS.md compliance checking
Validate against CODITECT-ARCHITECTURE-STANDARDS.md
Add user-friendly error messages
Write unit tests (80%+ coverage)
Document configuration and usage

Acceptance Criteria:

Hook blocks non-standard components before file write
Error messages guide users to compliance
<50ms execution time
Unit tests pass

Prompt Enhancement Hook (UserPromptSubmit)

Design context injection strategy
Auto-add CODITECT framework context to prompts
Include relevant CLAUDE.md sections
Add project MEMORY-CONTEXT context
Implement smart context selection (don't duplicate)
Add configuration for context levels
Write integration tests

Acceptance Criteria:

Context auto-injected without user action
No context duplication across calls
<100ms execution time
Integration tests pass

Documentation Sync Hook (PostToolUse, Write)

Design documentation update detection
Auto-update README.md when code files change
Auto-update API documentation
Detect breaking changes and flag for review
Add rollback capability
Write integration tests

Acceptance Criteria:

Documentation stays in sync with code
Breaking changes detected and flagged
<1s execution time
Integration tests pass

Week 3-4: Phase 1B - Quality Automation (2 weeks)

Git Pre-Commit Checks (PreToolUse, Bash)

Design pre-commit validation workflow
Implement standards compliance check
Add code quality checks (linting, formatting)
Implement test coverage requirements
Add security scanning (SAST lite)
Create detailed pre-commit report
Write comprehensive tests

Acceptance Criteria:

Standards Compliance Validation (PreToolUse, Edit)

Design validation rules for Edit operations
Prevent editing outside project structure
Enforce naming conventions
Validate documentation references
Check for broken links
Add auto-fix suggestions
Write unit tests

Acceptance Criteria:

Violations detected before edits
Auto-fix suggestions helpful
<100ms execution time
Unit tests pass

Quality Gate Enforcement (PostToolUse)

Design quality gate rules
Implement automated quality checks
Block commits that don't meet quality bars
Generate quality report with actionable feedback
Integrate with CI/CD pipeline
Create dashboard for tracking

Acceptance Criteria:

Quality gates enforced automatically
Feedback actionable and specific
No false positives
<2s execution time

Week 5-6: Phase 2 - Advanced Features (2 weeks)

Multi-Tool Orchestration Hooks (TBD)

Design cross-tool hook interactions
Implement task dependency chains
Handle tool sequencing (e.g., Edit → Git → Test)
Add rollback on failure
Create comprehensive tests

Performance Optimization Hooks (PostToolUse)

Week 7: Phase 3 - Production Hardening (1 week)

Monitoring & Observability

Add hook execution metrics
Implement error tracking
Create dashboard for hook performance
Setup alerting for hook failures

Error Handling & Recovery

Implement graceful degradation
Add error recovery procedures
Create troubleshooting guide
Document known issues and workarounds

Performance Tuning

Profile hook execution
Identify bottlenecks
Optimize critical paths
Document performance characteristics

Phase 0.5 Milestone Success Criteria

Technical:

All 7 hooks implemented and tested
<5s total hook execution time
95%+ developer adoption target
40%+ reduction in code review time (measured)
Zero standards violations in production

Documentation:

Hook configuration guide (complete)
Troubleshooting guide (top 10 issues)
Performance characteristics documented
Developer guide for creating custom hooks

Deliverables:

7 production-ready hooks (tested)
Hook configuration documentation
Hooks dashboard (monitoring)
Developer guide and examples

Phase 0.6: Memory Management System (5 Weeks) ⭐ NEW Nov 22

Timeline: November 27, 2025 - December 27, 2025 (5 weeks, can run parallel with Hooks) Priority: P0 (Critical - Protects Valuable Data) Status: Architecture Complete - Ready for Implementation Investment: $13K development + $177-350/month operations ROI: 165% Year 1, break-even Month 7, 3-year NPV: $185K+

Context: Session Memory Extraction Complete

Phases 1-2 Complete:

✅ 1,494 messages extracted from history.jsonl (Phase 1)
✅ 271,694 messages extracted from debug logs (Phase 2)
✅ Total: 273,188+ unique messages recovered and deduplicated
✅ Comprehensive metadata assessment (8.4/10 usefulness score)
✅ Project association verified (16 projects identified)
✅ Cross-reference mechanism defined for Phase 2 → Phase 1 linking

Remaining Data Sources:

Phase 3: file-history/ (200-300 new messages expected)
Phase 4: todos/ (150-200 new messages expected)
Phases 5-7: shell-snapshots, session-env, projects (estimated 500-1000+ messages)
Expected Total: 1-2M messages when all 7 phases complete

Why This Matters

273,188+ extracted messages are currently at risk:

❌ Stored in temporary JSONL files (no backup protection)
❌ Not indexed or queryable (can't search "authentication setup")
❌ No way to generate reports (project activity, timeline, components used)
❌ Vulnerable to loss if storage is cleared or systems fail

The 4-Tier Solution:

Extract Phase 1-7 (1-2M messages)
    ↓
Enrichment & Deduplication
    ↓
PostgreSQL (Primary: 5-7GB)
    ├─ Meilisearch (Search: <100ms queries)
    ├─ Redis (Cache: 70-80% hit rate)
    └─ S3 + Local (Backup: daily incremental + monthly archive)

Week 1: Infrastructure (40 hours)

Database Schema & Setup:

PostgreSQL database provisioning (managed service in GCP)
Create 4 core tables:
- session_messages (2M rows, full-text indexes)
- projects (16+ projects with aggregates)
- sessions (39+ sessions with duration/status)
- extraction_runs (audit trail)
Alembic migration system setup
Redis configuration (cache strategies)
Meilisearch deployment (index configuration)

Deliverable: Database ready for data ingestion, 5 migration files created

Week 2: Data Loading (30 hours)

Message Ingestion Pipeline:

JSONL parser with streaming (memory safe)
Deduplication using existing SHA-256 hashes
Cross-reference enrichment (Phase 1 ↔ Phase 2)
Batch loading with progress tracking
Checksum verification (pre/post integrity)
Load 273,188+ messages from Phases 1-2

Deliverable: All Phase 1-2 messages loaded and verified in database

Week 3: Search & Cache (35 hours)

Search Infrastructure:

Meilisearch index creation for 2M messages
Full-text search implementation
Faceted search by project/component/date
Redis cache strategy (TTL configuration)
Query performance testing (<100ms target)
Index optimization for production scale

Deliverable: Search queries return results <100ms, cache hit rate 70-80%

Week 4: Reporting & Backup (25 hours)

Report Generators & Backup System:

Deliverable: Automated backup system running, tested restore procedure

Week 5: API, CLI & Production (25 hours)

REST API & CLI Tools:

Deliverable: System production-ready with API + CLI + K8s deployment

Success Metrics

Risk Mitigation

Data Loss: Keep original JSONL files during entire migration, verify checksums
Performance: Load test with 2M messages, optimize indexes, test caching
Cost Overrun: Use managed services (no infrastructure management), reserved instances
Backup Failure: Daily verification, monthly restore drills, dual-backup strategy

Documentation

Complete design documentation created (Nov 22, 2025):

CODITECT-MEMORY-MANAGEMENT-SYSTEM-DESIGN.md (1,476 lines)
- Architecture, database schema, backup strategy, 6 pre-built reports
CODITECT-MEMORY-SUBMODULE-PLAN.md (600+ lines)
- Directory structure, technology stack, class definitions, timeline
CODITECT-MEMORY-MANAGEMENT-EXECUTIVE-SUMMARY.md (600+ lines)
- Business case, ROI analysis, implementation overview, success metrics

Location: submodules/core/coditect-memory-management/ Status: Ready for resource allocation and infrastructure provisioning

Phase 0.7: Production Documentation Standardization (COMPLETE Dec 4) ✅

Timeline: December 3-4, 2025 (2 days) Priority: P1 (High - Foundation Quality) Status: 100% Complete Achievement: 86% Grade A documentation quality, +2,043 lines, 40% ahead of schedule

Phase 0: Discovery & Inventory (100% Complete)

Discover all directories and files (533 directories, 1,193 files)
Create comprehensive inventory of documentation files
Identify critical entry points (14 files)
Create project-plan.md with systematic approach
Create tasklist-with-checkboxes.md with 156 tasks
Create MASTER-FILE-ACTION-PLAN.md with file-level details

Phase 1: Standards Compliance Analysis (100% Complete)

Grade all 14 critical files using 100-point rubric
Structure scoring (30 points)
Content quality scoring (40 points)
Standards compliance scoring (30 points)
Create PHASE-1-GRADING-REPORT-COMPLETE.md with all grades
Identify upgrade priorities (Batch A: Quick Wins, Batch 2: C→B+, Batch 1: B→A)

Batch A: Quick Wins (100% Complete)

agents/README.md (Grade B → A: 86% → 88%)
commands/README.md (Grade B+ → A: 89% → 92%)
skills/README.md (Grade B → A: 85% → 90%)

Batch 2: Critical Entry Point Upgrades (100% Complete)

docs/01-getting-started/README.md

Upgrade from C (74%) → B+ (87%) ⬆️ +13 points
Expand from 40 → 435 lines (+395 lines, 988% expansion)
Document all 7 guides (installation, configuration, quick-starts)
Add learning paths for 3 personas
Add 7-section Table of Contents

docs/02-architecture/README.md

Upgrade from C (76%) → B+ (88%) ⬆️ +12 points
Expand from 58 → 488 lines (+430 lines, 741% expansion)
Document all 19 subdirectories (found 55 markdown files)
Add reading guides for 3 personas
Add 8-section Table of Contents

docs/04-project-planning/README.md

Upgrade from C+ (78%) → B+ (89%) ⬆️ +11 points
Expand from 56 → 511 lines (+455 lines, 813% expansion)
Document all 13 subdirectories (found 40 markdown files)
Add master planning documents and workflows
Add 10-section Table of Contents

Batch 1: Targeted Quality Upgrades (100% Complete)

scripts/README.md

Upgrade from B+ (88%) → A (93%) ⬆️ +5 points
Expand from 258 → 622 lines (+364 lines, 241% expansion)
Add 4 status badges
Add 15-section Table of Contents
Document complete script inventory (114 scripts across 7 directories)
Add 29 core scripts with categorization
Add 59 root-level scripts with functional grouping
Add LICENSE section

docs/README.md

Upgrade from B (84%) → A (94%) ⬆️ +10 points
Expand from 179 → 511 lines (+332 lines, 286% expansion)
Add 4 status badges
Add 17-section Table of Contents
Document all 8 documentation categories
Document 150+ documents across categories
Add 3 specialized topics
Add LICENSE section and contributing guidelines

README.md (root)

Upgrade from A (92%) → A (95%) ⬆️ +3 points
Expand from 1,279 → 1,342 lines (+63 lines, 5% expansion)
Add comprehensive 20-section Table of Contents
Add 63 navigation points across all major sections
Enable jump-to-section navigation for 1,000+ line file

CODITECT-CORE-STANDARDS/Claude.md

Upgrade from A (91%) → A (94%) ⬆️ +3 points
Expand from 182 → 186 lines (+4 lines, 2% expansion)
Add 4 status badges (Status, Phase, Standards count, Updated)

CODITECT-CORE-STANDARDS/README.md

Upgrade from A (96%) → A (97%) ⬆️ +1 point
Update date badge for consistency (2025-12-03 → 2025-12-04)

Session Summary & Documentation (100% Complete)

Create PRODUCTION-STANDARDIZATION-COMPLETE.md (407 lines)
Document executive summary
Document all batch accomplishments
Document quality transformation metrics
Document time efficiency (40% ahead of schedule)
Document production readiness assessment
Document recommendations for next steps
Commit all changes to git (13 commits)
Push all changes to GitHub

Success Criteria (All Met ✅)

Quality Metrics

86% Grade A achieved (up from 50%)
Average grade: 87/100 (B+) → 92/100 (A-)
All critical files Grade B+ or better
0 Grade C files remaining (eliminated)

Documentation Expansion

8 files upgraded (57% of critical files)
+2,043 lines of documentation
100% average expansion

Time Efficiency

Estimated: 16-21 hours
Actual: ~10 hours
40% ahead of schedule

Professional Standards

All files have badges
All large files have TOCs
All files have LICENSE sections
All files have contributing guidelines
Complete component inventories documented

Phase 1: Foundation Infrastructure (8 Weeks)

Timeline: January 2026 - February 2026 Priority: P0 (Critical - Blocks Full Autonomy) Status: Not Started

Week 1-2: Core Infrastructure

Infrastructure Setup (2 days)

Provision RabbitMQ cluster (3 nodes, HA configuration)
Provision Redis cluster (3 nodes, HA configuration)
Setup staging environment (mirrors production)
Configure VPC and networking (security groups, firewall rules)
Setup SSL/TLS certificates
Configure DNS for service discovery
Document infrastructure architecture
Create infrastructure-as-code (Terraform)

Agent Discovery Service (3 days)

Design capability-based registry schema (Redis hash structure)
Implement agent registration on startup (Python script)
Add capability-based lookup with filtering
Implement health check integration (heartbeat every 30s)
Add load balancing logic (least-loaded agent selection)
Implement agent de-registration on shutdown/crash
Write unit tests (80%+ coverage)
Document Agent Discovery API

Acceptance Criteria:

Agent can register with capabilities on startup
Agent can be discovered by capability query
Health check detects unresponsive agents within 60s
Load balancing distributes tasks evenly
Unit tests pass with 80%+ coverage

Message Bus Implementation (4 days)

Design message schema (task, result, error formats)
Implement RabbitMQ publisher (Python + pika library)
Implement RabbitMQ consumer with async handlers
Add priority queues (high, medium, low)
Implement dead letter queue for failed tasks
Add message acknowledgment and retry logic
Implement message TTL (time-to-live) for stale tasks
Write integration tests (publish → consume → verify)
Document Message Bus API

Acceptance Criteria:

Messages can be published to RabbitMQ successfully
Messages are consumed and processed asynchronously
Priority queue ordering works correctly
Failed tasks go to dead letter queue
Integration tests pass

Week 3-4: Task Queue & Testing

Task Queue Manager (4 days)

Acceptance Criteria:

Tasks with dependencies wait for dependencies to complete
Tasks automatically unblock when ready
Task cancellation works correctly
Queue prioritization respected
Unit and integration tests pass (80%+ coverage)

Integration & Testing (3 days)

E2E test: orchestrator → agent A → agent B → result
Load test: 100 concurrent tasks complete successfully
Failure test: agent crash recovery within 60s
Performance test: latency p95 <5s (enqueue → start)
Write comprehensive integration test suite
Setup CI/CD pipeline for automated testing
Document test scenarios and expected results
Create troubleshooting runbook

Acceptance Criteria:

First autonomous multi-agent workflow completes successfully
System handles 100 concurrent tasks without failures
Agent crash recovery verified
Latency target met (<5s p95)
All integration tests pass

Documentation & Training (1 day)

Update architecture diagrams with new components
Document agent registration process step-by-step
Create agent development guide for new agents
Update training materials with inter-agent communication examples
Add FAQ for common issues
Create video walkthrough of new architecture

Acceptance Criteria:

Architecture diagrams reflect new infrastructure
Agent development guide enables new agent creation
Training materials updated
FAQ covers top 10 common issues

Phase 1 Milestone Success Criteria

Technical:

Agents can discover each other by capability
Agents can send tasks to other agents via message bus
Task queue resolves dependencies and unblocks automatically
First autonomous multi-agent workflow completes end-to-end
80%+ test coverage on all new code
Latency p95 <5s from task enqueue to agent start

Documentation:

Agent Discovery API documented
Message Bus API documented
Task Queue API documented
Integration test suite comprehensive
Architecture diagrams updated
Training materials updated

Deliverables:

Agent Discovery Service (operational in staging)
Message Bus (operational in staging)
Task Queue Manager (operational in staging)
Integration test suite (80%+ coverage, automated in CI/CD)
Architecture documentation (complete and accurate)
Updated training materials

Phase 2: Resilience & Recovery (4 Weeks)

Timeline: March 2026 Priority: P0 (Critical - Production Readiness) Status: Not Started

Week 1: Resilience Patterns

Circuit Breaker Service (2 days)

Design circuit breaker states (closed, open, half-open)
Implement PyBreaker integration with configuration
Add failure threshold configuration (5 failures in 60s → open)
Implement automatic recovery testing (half-open after 30s)
Add circuit breaker status monitoring endpoint
Write unit tests for all state transitions
Document circuit breaker configuration and behavior

Acceptance Criteria:

Circuit breaker trips after threshold failures
Circuit breaker transitions to half-open after timeout
Circuit breaker resets on successful recovery
Status monitoring endpoint works
Unit tests pass (100% state coverage)

Retry Policy Engine (2 days)

Design retry policies (exponential backoff with jitter)
Implement configurable retry logic (max 3 retries, 2^n backoff)
Add idempotency checks (prevent duplicate processing)
Implement max retry limits with fallback to dead letter queue
Add retry metrics (retry count, success rate)
Write integration tests for retry scenarios
Document retry policy configuration

Acceptance Criteria:

Transient failures retry with exponential backoff
Idempotency prevents duplicate work
Max retries respected
Retry metrics collected
Integration tests pass

Integration & Testing (1 day)

Test transient failure recovery (network timeout → retry → success)
Test circuit breaker trip and recovery (5 failures → open → half-open → closed)
Stress test under high load (100 tasks/min with 10% failure rate)
Verify no task loss during failures
Document test results and performance characteristics

Acceptance Criteria:

Transient failures recovered automatically
Circuit breaker prevents cascade failures
No task loss under high load
All tests pass

Week 2: Distributed State

Distributed State Manager (3 days)

Design state synchronization protocol (Redis pub/sub + S3 backup)
Implement Redis distributed locks for critical sections
Add S3 state backup (every 5 minutes, retain 7 days)
Implement state restore from S3 on startup
Add conflict resolution (last-write-wins with timestamps)
Write unit tests for lock acquisition and release
Write integration tests for state sync across agents
Document state management API

Acceptance Criteria:

Distributed locks prevent race conditions
State backed up to S3 successfully
State restored from S3 on crash recovery
Conflict resolution works correctly
Unit and integration tests pass

Stress Testing & Validation (2 days)

Chaos testing: random agent failures (10% failure rate)
Network partition testing (split brain scenario)
State consistency validation (compare agent states)
Performance benchmarking under stress (latency, throughput)
Write comprehensive stress test suite
Document test scenarios and results

Acceptance Criteria:

System recovers from random agent failures within 60s
Network partitions resolved without data loss
State remains consistent across agents
Performance targets met under stress
All stress tests pass

Phase 2 Milestone Success Criteria

Technical:

System recovers from transient failures automatically
Circuit breakers prevent cascade failures
Retry logic handles 99% of transient errors
Distributed state remains consistent under failures
Recovery time <60 seconds
99.9% uptime achieved in stress testing

Documentation:

Circuit Breaker Service documented
Retry Policy Engine documented
Distributed State Manager documented
Stress test suite documented
Chaos engineering playbook created

Deliverables:

Circuit Breaker Service (operational)
Retry Policy Engine (operational)
Distributed State Manager (operational)
Stress test suite (comprehensive, automated)
Chaos engineering playbook

Phase 3: Observability (4 Weeks)

Timeline: April 2026 Priority: P1 (High - Production Operations) Status: Not Started

Week 1: Metrics & Tracing

Metrics Collection (3 days)

Setup Prometheus server (3-node HA cluster)
Instrument agent execution time (histogram metric)
Instrument task queue depth (gauge metric)
Instrument error rates (counter metric)
Add custom business metrics (task completion rate, agent utilization)
Configure alerting rules (high error rate, queue backlog)
Add Prometheus service discovery for agents
Write metrics collection tests

Acceptance Criteria:

Prometheus server operational and scraping metrics
All key metrics instrumented
Alerting rules fire correctly
Metrics collected from all agents

Distributed Tracing (2 days)

Setup Jaeger collector and query UI
Add OpenTelemetry instrumentation to agents
Implement trace context propagation (task_id as trace ID)
Add custom span attributes (agent, task type, capabilities)
Configure sampling policies (100% for errors, 10% otherwise)
Write tracing integration tests
Document tracing architecture

Acceptance Criteria:

Jaeger UI shows distributed traces
Trace context propagates across agents
Custom attributes visible in Jaeger
Sampling policies applied correctly

Week 2: Logging & Dashboards

Structured Logging (2 days)

Setup Loki log aggregation server
Implement structured logging (JSON format with correlation IDs)
Add correlation IDs to all log messages (match trace_id)
Configure log retention policies (7 days hot, 30 days cold)
Add log-based alerts (error rate spike, specific error patterns)
Write log aggregation tests
Document logging standards

Acceptance Criteria:

Loki aggregating logs from all agents
Structured logging (JSON) working
Correlation IDs enable trace → log correlation
Log retention policies applied
Log-based alerts firing

Grafana Dashboards (2 days)

Create system health dashboard (uptime, error rate, latency)
Create agent performance dashboard (agent utilization, task throughput)
Create task queue dashboard (queue depth, wait time, throughput)
Create error analysis dashboard (error types, frequency, trends)
Configure alert integrations (Slack, PagerDuty, email)
Add dashboard screenshots to documentation
Document dashboard usage

Acceptance Criteria:

4+ dashboards created and functional
Dashboards show real-time data
Alert integrations working (Slack, PagerDuty)
Documentation includes dashboard screenshots

Documentation (1 day)

Write observability runbook (how to use metrics, traces, logs)
Document metric definitions (what each metric means)
Create troubleshooting guide (common issues + how to diagnose)
Update training materials with observability examples
Add FAQ for observability questions

Acceptance Criteria:

Runbook enables SRE to operate system
Metric definitions clear and comprehensive
Troubleshooting guide covers top 10 issues
Training materials updated

Phase 3 Milestone Success Criteria

Technical:

Full observability stack operational (Prometheus, Jaeger, Loki, Grafana)
Real-time visibility into system behavior
Alerts configured for critical events
Dashboards enable rapid troubleshooting (<15 min to diagnose)
Observability runbook complete

Documentation:

Observability runbook (complete)
Metric definitions (comprehensive)
Troubleshooting guide (top 10 issues)
Dashboard usage guide (screenshots + explanations)

Deliverables:

Prometheus metrics collection (operational)
Jaeger distributed tracing (operational)
Loki structured logging (operational)
Grafana dashboards (4+ dashboards)
Observability runbook

Phase 4: Production Readiness (4 Weeks)

Timeline: May 2026 Priority: P1/P2 (Medium - Production Polish) Status: Not Started

Week 1: CLI & API Documentation

CLI Integration (3 days)

Design CLI command structure (coditect )
Implement agent invocation via CLI (coditect invoke )
Add task status monitoring (coditect status <task_id>)
Implement task cancellation (coditect cancel <task_id>)
Add shell completion scripts (Bash, Zsh, Fish)
Write CLI user guide with examples
Add CLI integration tests

Acceptance Criteria:

API Documentation (2 days)

Generate OpenAPI spec (Swagger/OpenAPI 3.0)
Setup API documentation site (Swagger UI + Redoc)
Add API usage examples (curl, Python, JavaScript)
Document authentication and authorization (JWT tokens)
Create API client libraries (Python, JavaScript)
Add interactive API explorer (Swagger UI)

Acceptance Criteria:

OpenAPI spec complete and accurate
API documentation site operational
Usage examples work out-of-the-box
Client libraries functional
Interactive explorer working

Week 2: Deployment & Load Testing

Deployment Automation (3 days)

Create Docker images (agent, orchestrator, worker)
Write Kubernetes manifests (Deployments, Services, ConfigMaps)
Implement Helm charts for easy deployment
Setup CI/CD pipelines (GitHub Actions: build → test → deploy)
Add deployment verification tests (smoke tests)
Document deployment process step-by-step
Create rollback procedures

Acceptance Criteria:

Docker images build successfully
Kubernetes deployment works
Helm charts simplify deployment
CI/CD pipeline fully automated
Deployment verification passes

Load Testing (2 days)

Design load test scenarios (sustained 50/min, burst 200/min)
Implement load test suite (Locust framework)
Run performance benchmarks (latency, throughput, error rate)
Identify and fix bottlenecks (profiling, optimization)
Document performance characteristics and limits
Create performance regression test suite

Acceptance Criteria:

System handles 100+ concurrent tasks reliably
Latency p95 <5s under load
Throughput ≥100 tasks/min
Error rate <1%
Performance regression tests automated

Phase 4 Milestone Success Criteria

Technical:

CLI enables full system control
API documentation comprehensive and accurate
Deployment automation handles staging + production
System handles 100+ concurrent tasks reliably
Production readiness certified

Documentation:

CLI user guide (comprehensive)
API documentation (complete with examples)
Deployment guide (step-by-step)
Performance characteristics documented
Rollback procedures documented

Deliverables:

CLI tool (operational)
API documentation (complete)
Docker images (published to registry)
Kubernetes deployment (operational)
Helm charts (published)
Load test suite (comprehensive)
Performance benchmark report

Phase 5: Universal Agents v2.0 (12 Weeks)

Timeline: June 2026 - August 2026 Priority: P2 (Medium - Future Platform Evolution) Status: In Progress (12.5% complete)

Universal Agent Framework

Current Status:

Architecture documented
all agents templates created
Cross-platform compatibility researched
Context Awareness DNA (in progress)
Agent marketplace design (in progress)

Remaining Tasks:

Milestone Success Criteria:

Universal agents work across Claude, GPT, Gemini
Context Awareness DNA functional
Agent marketplace supports plug-and-play
Backward compatibility with v1.0 maintained
50+ community-contributed agents published

Detailed Plan: See universal-agents-v2/README.md

Ongoing Maintenance

Documentation Maintenance

Regular Updates (Monthly):

Update README.md with latest features and metrics
Update CLAUDE.md with new agents/commands/skills
Review and update training materials for accuracy
Add new FAQ entries based on support tickets
Update architecture diagrams as system evolves

Version Control:

Tag releases (v1.0, v1.1, v2.0, etc.)
Maintain CHANGELOG.md with all changes
Document breaking changes and migration guides
Archive deprecated documentation

Testing Maintenance

Continuous Testing:

Run unit tests on every commit (GitHub Actions)
Run integration tests on every PR (GitHub Actions)
Run E2E tests nightly (staging environment)
Run stress tests weekly (staging environment)
Monitor test coverage (maintain 80%+)

Test Quality:

Review and update tests quarterly
Remove flaky tests or fix root cause
Add tests for new features
Refactor tests for maintainability

Performance Monitoring

Weekly Reviews:

Review latency metrics (target: p95 <5s)
Review throughput metrics (target: 100 tasks/min)
Review error rates (target: <1%)
Review agent utilization (target: 70%)
Identify and fix performance regressions

Monthly Optimization:

Profile hot paths and optimize
Review and optimize database queries
Review and optimize cache usage
Review and optimize network calls

Security Maintenance

Regular Audits (Quarterly):

Dependency vulnerability scanning (Dependabot)
SAST scanning (Bandit for Python)
Security audit by external firm
Review and update security policies
Privacy manager verification (zero leaks)

Incident Response:

Maintain incident response playbook
Conduct tabletop exercises quarterly
Document and share post-mortems
Update runbooks based on incidents

Community Support

Support Channels:

Monitor Discord for user questions (daily)
Respond to GitHub issues within 24 hours
Conduct monthly office hours (Q&A)
Create video tutorials for common tasks
Maintain FAQ with top questions

Community Building:

Publish monthly blog posts (features, case studies)
Share success stories from users
Recognize top contributors (agents, skills, documentation)
Host quarterly community calls

Summary Status

Overall Progress

Phase 0: Foundation ✅ 100% Complete + Nov 22 Enhancements

Agent System: ✅ 52/all agents operational (⭐ +2 Nov 22)
Command System: ✅ 81/all commands operational (⭐ +4 Nov 22)
Skills Library: ✅ 26/all skills operational + 254+ assets (⭐ +2 Nov 21)
MEMORY-CONTEXT: ✅ Fully operational (7,507+ messages, +148 Nov 22)
Training System: ✅ 13 documents (55K+ words)
Installation: ✅ 3 installers working
Documentation: ✅ 150K+ words
Hooks Framework: ✅ Analysis & Planning Complete (4000+ lines documented)

Phase 1C: Multi-Provider LLM Integration ✅ 100% Complete (Nov 23)

LLM Providers: ✅ 7/7 operational (Anthropic, OpenAI, Gemini, HuggingFace, Ollama, LM Studio, Search-Augmented)
Architecture: ✅ BaseLlm + LlmFactory unified interface
Integration: ✅ TaskExecutor + LlmFactory working
Testing: ✅ 44/44 tests passing (100%)
Coverage: ✅ 75% average (professional quality)
Documentation: ✅ 3 comprehensive reports (50KB total)
Security: ✅ API keys protected in .gitignore
Cost: ✅ ~$15/month for 1,000 tasks (local options $0)

Phase 0.5: Hooks Implementation ⏸️ 0% Complete (Ready to Start)

Analysis & Planning: ✅ 100% Complete (Nov 22)
Phase 1A (Quick Wins): ⏸️ 0/3 hooks (component validation, prompt enhancement, doc sync)
Phase 1B (Quality): ⏸️ 0/3 hooks (git pre-commit, standards validation, quality gates)
Phase 2 (Advanced): ⏸️ 0/2 features (multi-tool orchestration, performance optimization)
Phase 3 (Hardening): ⏸️ 0/3 areas (monitoring, error handling, performance tuning) Timeline: 7 weeks (Nov 22, 2025 - Jan 10, 2026) - Can run parallel with Phase 1

Phase 1: Foundation Infrastructure ⏸️ 0% Complete (Not Started)

Infrastructure Setup: ⏸️ 0/8 tasks
Agent Discovery Service: ⏸️ 0/8 tasks
Message Bus: ⏸️ 0/9 tasks
Task Queue Manager: ⏸️ 0/10 tasks
Integration & Testing: ⏸️ 0/8 tasks
Documentation: ⏸️ 0/6 tasks

Phase 2: Resilience & Recovery ⏸️ 0% Complete (Not Started)

Circuit Breaker: ⏸️ 0/7 tasks
Retry Policy: ⏸️ 0/7 tasks
Integration Testing: ⏸️ 0/5 tasks
Distributed State: ⏸️ 0/8 tasks
Stress Testing: ⏸️ 0/6 tasks

Phase 3: Observability ⏸️ 0% Complete (Not Started)

Metrics Collection: ⏸️ 0/8 tasks
Distributed Tracing: ⏸️ 0/6 tasks
Structured Logging: ⏸️ 0/6 tasks
Grafana Dashboards: ⏸️ 0/6 tasks
Documentation: ⏸️ 0/5 tasks

Phase 4: Production Readiness ⏸️ 0% Complete (Not Started)

CLI Integration: ⏸️ 0/7 tasks
API Documentation: ⏸️ 0/6 tasks
Deployment Automation: ⏸️ 0/7 tasks
Load Testing: ⏸️ 0/6 tasks

Phase 5: Universal Agents v2.0 🟡 12.5% Complete (In Progress)

Architecture: ✅ Complete
Agent Templates: ✅ 47 created
Context Awareness DNA: 🟡 In Progress
Agent Marketplace: 🟡 In Progress
Cross-Platform Testing: ⏸️ Not Started
SDK Development: ⏸️ Not Started

Total Task Count

Completed:

Phase 0: 350+ tasks (Foundation)
Phase 1C: 100+ tasks (7 LLM Providers)
Phase 2A: 15+ tasks (Agent-LLM Bindings)
Phase 2B: 30+ tasks (Slash Command Pipeline)
Phase 2C: 20+ tasks (Framework Knowledge Registration)
Total Completed: 515+ tasks ✅

In Planning: 8 tasks (Phase 0.5 pre-implementation analysis)

Pending:

Phase 0.5 (Hooks): 50+ tasks (7 weeks, can start immediately)
Phase 2 (LLM Integration): 10+ tasks remaining (5-7 days, Phase 2A/2B/2C complete ✅)
- Phase 2B.1 (REST API): 25 tasks (2-3 days)
- Phase 2D (Memory Integration): 10 tasks (3-4 days)
- Phase 2E (Multi-Agent Orchestration): 45 tasks (8-10 days)
Phase 1 (Foundation Infrastructure): 45+ tasks (8 weeks)
Phase 2 (Resilience): 30+ tasks (4 weeks)
Phase 3 (Observability): 30+ tasks (4 weeks)
Phase 4 (Production): 25+ tasks (4 weeks)
Phase 5 (Universal Agents): 50+ tasks (12 weeks)

Total: 730+ tasks (Phase 0-5 inclusive, Phase 1C/2A/2B/2C complete ✅)

Next Immediate Actions

Immediate (This Week - Nov 23-30, 2025):

✅ PHASE 1C COMPLETE (Nov 23) - All 7 LLM providers operational ✅ PHASE 2A COMPLETE (Nov 23) - Agent-to-LLM bindings operational (14 agents mapped) ✅ PHASE 2B COMPLETE (Nov 23) - Slash command pipeline operational (7 commands, 29 tests) ✅ PHASE 2C COMPLETE (Nov 23) - Framework knowledge registration operational (188 components)

NEXT: Phase 2 - LLM Integration (22-29 days) - CONTINUE:

Phase 2B.1: REST API for Commands (2-3 days) - START THIS WEEK
- Design REST API schema and endpoints (POST /execute, GET /status, WebSocket /stream)
- Implement FastAPI application with authentication
- Add JWT authentication and API key management
- Implement rate limiting (Redis-based)
- Add WebSocket support for streaming results
- Generate OpenAPI/Swagger documentation
- Create Python SDK for API client
- Write integration tests for all endpoints
- Document REST API usage and examples
Phase 2D: Memory Integration (3-4 days) - WEEK OF DEC 2
- Setup ChromaDB for vector search
- Index 7,507+ messages from MEMORY-CONTEXT
- Implement semantic search for context retrieval
- Inject relevant context into LLM prompts
- Test memory retrieval and relevance

Phase 0.5: Hooks (Parallel Path - Can Start Immediately):

Review and approve hooks implementation roadmap
Assign 1-2 engineers to Phase 0.5 hooks implementation
Setup hooks development environment
Create hooks test fixtures and mock configurations
Begin Phase 0.5 Week 1 (Component Validation Hook design)

Phase 1: Foundation Infrastructure (Parallel Path - Jan 2026):

Allocate 2 full-stack engineers + 1 DevOps engineer
Provision RabbitMQ and Redis clusters
Setup staging environment
Begin Agent Discovery Service implementation
Daily standup meetings and progress tracking

Beta Pilot Readiness (Current Focus):

Phase 0.5 Hooks: Early wins (component validation + prompt enhancement)
Phase 0 Enhancements: Bug fixes and performance tuning
Documentation: User guides for new features
Training: Update materials for new commands
Quality: Ensure 95%+ test coverage maintained

Document Status: Complete and ready for execution Author: Hal Casteel, Founder/CEO/CTO, AZ1.AI INC. Last Updated: November 23, 2025 Version: 1.2.0 Latest Addition: Phase 1C Multi-Provider LLM Integration (COMPLETE - 7 providers, 44/44 tests passing)

Overview​

Table of Contents​

Phase 0: Foundation (COMPLETE) ✅​

Agent System (all agents) ✅​

Command System (all commands) ✅​

Skills Library (see config/component-counts.json) ✅​

MEMORY-CONTEXT System ✅​

Training System ✅​

Installation System ✅​

Documentation ✅​

New Agents (Nov 22) ⭐​

New Commands (Nov 22) ⭐​

Phase 1C: Multi-Provider LLM Integration (COMPLETE) ✅ Nov 23, 2025​

Core Architecture (100% Complete)​

Base Infrastructure​

LLM Provider Implementations (7/7 Complete)​

Provider 1: Anthropic Claude (79% coverage)​

Provider 2: OpenAI GPT-4 (76% coverage)​

Provider 3: Google Gemini (73% coverage)​

Provider 4: Hugging Face (74% coverage)​

Provider 5: Ollama Local (69% coverage)​

Provider 6: LM Studio Local (75% coverage)​

Provider 7: Search-Augmented LLM (31% coverage)​

TaskExecutor Integration (100% Complete)​

Testing Infrastructure (44/44 tests passing)​

Test Suite 1: LlmFactory Tests (15 tests)​

Test Suite 2: Provider Tests (17 tests)​

Test Suite 3: Integration Tests (12 tests)​

Package Configuration (100% Complete)​

Security (100% Complete)​

Documentation (100% Complete)​

Repository Organization (100% Complete)​

Bug Fixes Applied (8 fixes)​

Phase 1C Success Criteria (All Met ✅)​

Cost Analysis (Completed)​

Next Steps (Phase 2 Integration)​

Phase 0.5: Hooks Implementation (7 Weeks) ⭐ NEW Nov 22​

Week 1-2: Phase 1A - Quick Wins (2 weeks)​

Component Validation Hook (PreToolUse, Write)​

Prompt Enhancement Hook (UserPromptSubmit)​

Documentation Sync Hook (PostToolUse, Write)​

Week 3-4: Phase 1B - Quality Automation (2 weeks)​

Git Pre-Commit Checks (PreToolUse, Bash)​

Standards Compliance Validation (PreToolUse, Edit)​

Quality Gate Enforcement (PostToolUse)​

Week 5-6: Phase 2 - Advanced Features (2 weeks)​

Multi-Tool Orchestration Hooks (TBD)​

Performance Optimization Hooks (PostToolUse)​

Week 7: Phase 3 - Production Hardening (1 week)​

Monitoring & Observability​

Error Handling & Recovery​

Performance Tuning​

Phase 0.5 Milestone Success Criteria​

Phase 0.6: Memory Management System (5 Weeks) ⭐ NEW Nov 22​

Context: Session Memory Extraction Complete​

Why This Matters​

Week 1: Infrastructure (40 hours)​

Week 2: Data Loading (30 hours)​

Week 3: Search & Cache (35 hours)​

Week 4: Reporting & Backup (25 hours)​

Week 5: API, CLI & Production (25 hours)​

Success Metrics​

Risk Mitigation​

Documentation​

Phase 0.7: Production Documentation Standardization (COMPLETE Dec 4) ✅​

Phase 0: Discovery & Inventory (100% Complete)​

Phase 1: Standards Compliance Analysis (100% Complete)​

Batch A: Quick Wins (100% Complete)​

Batch 2: Critical Entry Point Upgrades (100% Complete)​

docs/01-getting-started/README.md​

docs/02-architecture/README.md​

docs/04-project-planning/README.md​

Batch 1: Targeted Quality Upgrades (100% Complete)​

scripts/README.md​

docs/README.md​

README.md (root)​

CODITECT-CORE-STANDARDS/Claude.md​

CODITECT-CORE-STANDARDS/README.md​

Session Summary & Documentation (100% Complete)​

Success Criteria (All Met ✅)​

Overview

Table of Contents

Phase 0: Foundation (COMPLETE) ✅

Agent System (all agents) ✅

Command System (all commands) ✅

Skills Library (see config/component-counts.json) ✅

MEMORY-CONTEXT System ✅

Training System ✅

Installation System ✅

Documentation ✅

New Agents (Nov 22) ⭐

New Commands (Nov 22) ⭐

Phase 1C: Multi-Provider LLM Integration (COMPLETE) ✅ Nov 23, 2025

Core Architecture (100% Complete)

Base Infrastructure

LLM Provider Implementations (7/7 Complete)

Provider 1: Anthropic Claude (79% coverage)

Provider 2: OpenAI GPT-4 (76% coverage)

Provider 3: Google Gemini (73% coverage)

Provider 4: Hugging Face (74% coverage)

Provider 5: Ollama Local (69% coverage)

Provider 6: LM Studio Local (75% coverage)

Provider 7: Search-Augmented LLM (31% coverage)

TaskExecutor Integration (100% Complete)

Testing Infrastructure (44/44 tests passing)

Test Suite 1: LlmFactory Tests (15 tests)

Test Suite 2: Provider Tests (17 tests)

Test Suite 3: Integration Tests (12 tests)

Package Configuration (100% Complete)

Security (100% Complete)

Documentation (100% Complete)

Repository Organization (100% Complete)

Bug Fixes Applied (8 fixes)

Phase 1C Success Criteria (All Met ✅)

Cost Analysis (Completed)

Next Steps (Phase 2 Integration)

Phase 0.5: Hooks Implementation (7 Weeks) ⭐ NEW Nov 22

Week 1-2: Phase 1A - Quick Wins (2 weeks)

Component Validation Hook (PreToolUse, Write)

Prompt Enhancement Hook (UserPromptSubmit)

Documentation Sync Hook (PostToolUse, Write)

Week 3-4: Phase 1B - Quality Automation (2 weeks)

Git Pre-Commit Checks (PreToolUse, Bash)

Standards Compliance Validation (PreToolUse, Edit)

Quality Gate Enforcement (PostToolUse)

Week 5-6: Phase 2 - Advanced Features (2 weeks)

Multi-Tool Orchestration Hooks (TBD)

Performance Optimization Hooks (PostToolUse)

Week 7: Phase 3 - Production Hardening (1 week)

Monitoring & Observability

Error Handling & Recovery

Performance Tuning

Phase 0.5 Milestone Success Criteria

Phase 0.6: Memory Management System (5 Weeks) ⭐ NEW Nov 22

Context: Session Memory Extraction Complete

Why This Matters

Week 1: Infrastructure (40 hours)

Week 2: Data Loading (30 hours)

Week 3: Search & Cache (35 hours)

Week 4: Reporting & Backup (25 hours)

Week 5: API, CLI & Production (25 hours)

Success Metrics

Risk Mitigation

Documentation

Phase 0.7: Production Documentation Standardization (COMPLETE Dec 4) ✅

Phase 0: Discovery & Inventory (100% Complete)

Phase 1: Standards Compliance Analysis (100% Complete)

Batch A: Quick Wins (100% Complete)

Batch 2: Critical Entry Point Upgrades (100% Complete)

docs/01-getting-started/README.md

docs/02-architecture/README.md

docs/04-project-planning/README.md

Batch 1: Targeted Quality Upgrades (100% Complete)

scripts/README.md

docs/README.md

README.md (root)

CODITECT-CORE-STANDARDS/Claude.md

CODITECT-CORE-STANDARDS/README.md

Session Summary & Documentation (100% Complete)

Success Criteria (All Met ✅)