kazuki nakai 00706f0ea9
feat: comprehensive framework improvements (#447)
* refactor(docs): move core docs into framework/business/research (move-only)

- framework/: principles, rules, flags (思想・行動規範)
- business/: symbols, examples (ビジネス領域)
- research/: config (調査設定)
- All files renamed to lowercase for consistency

* docs: update references to new directory structure

- Update ~/.claude/CLAUDE.md with new paths
- Add migration notice in core/MOVED.md
- Remove pm.md.backup
- All @superclaude/ references now point to framework/business/research/

* fix(setup): update framework_docs to use new directory structure

- Add validate_prerequisites() override for multi-directory validation
- Add _get_source_dirs() for framework/business/research directories
- Override _discover_component_files() for multi-directory discovery
- Override get_files_to_install() for relative path handling
- Fix get_size_estimate() to use get_files_to_install()
- Fix uninstall/update/validate to use install_component_subdir

Fixes installation validation errors for new directory structure.

Tested: make dev installs successfully with new structure
  - framework/: flags.md, principles.md, rules.md
  - business/: examples.md, symbols.md
  - research/: config.md

* refactor(modes): update component references for docs restructure

* chore: remove redundant docs after PLANNING.md migration

Cleanup after Self-Improvement Loop implementation:

**Deleted (21 files, ~210KB)**:
- docs/Development/ - All content migrated to PLANNING.md & TASK.md
  * ARCHITECTURE.md (15KB) → PLANNING.md
  * TASKS.md (3.7KB) → TASK.md
  * ROADMAP.md (11KB) → TASK.md
  * PROJECT_STATUS.md (4.2KB) → outdated
  * 13 PM Agent research files → archived in KNOWLEDGE.md
- docs/PM_AGENT.md - Old implementation status
- docs/pm-agent-implementation-status.md - Duplicate
- docs/templates/ - Empty directory

**Retained (valuable documentation)**:
- docs/memory/ - Active session metrics & context
- docs/patterns/ - Reusable patterns
- docs/research/ - Research reports
- docs/user-guide*/ - User documentation (4 languages)
- docs/reference/ - Reference materials
- docs/getting-started/ - Quick start guides
- docs/agents/ - Agent-specific guides
- docs/testing/ - Test procedures

**Result**:
- Eliminated redundancy after Root Documents consolidation
- Preserved all valuable content in PLANNING.md, TASK.md, KNOWLEDGE.md
- Maintained user-facing documentation structure

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* refactor: relocate PM modules to commands/modules

- Move modules to superclaude/commands/modules/
- Organize command-specific modules under commands/

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: add self-improvement loop with 4 root documents

Implements Self-Improvement Loop based on Cursor's proven patterns:

**New Root Documents**:
- PLANNING.md: Architecture, design principles, 10 absolute rules
- TASK.md: Current tasks with priority (🔴🟡🟢)
- KNOWLEDGE.md: Accumulated insights, best practices, failures
- README.md: Updated with developer documentation links

**Key Features**:
- Session Start Protocol: Read docs → Git status → Token budget → Ready
- Evidence-Based Development: No guessing, always verify
- Parallel Execution Default: Wave → Checkpoint → Wave pattern
- Mac Environment Protection: Docker-first, no host pollution
- Failure Pattern Learning: Past mistakes become prevention rules

**Cleanup**:
- Removed: docs/memory/checkpoint.json, current_plan.json (migrated to TASK.md)
- Enhanced: setup/components/commands.py (module discovery)

**Benefits**:
- LLM reads rules at session start → consistent quality
- Past failures documented → no repeats
- Progressive knowledge accumulation → continuous improvement
- 3.5x faster execution with parallel patterns

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* test: validate Self-Improvement Loop workflow

Tested complete cycle: Read docs → Extract rules → Execute task → Update docs

Test Results:
- Session Start Protocol:  All 6 steps successful
- Rule Extraction:  10/10 absolute rules identified from PLANNING.md
- Task Identification:  Next tasks identified from TASK.md
- Knowledge Application:  Failure patterns accessed from KNOWLEDGE.md
- Documentation Update:  TASK.md and KNOWLEDGE.md updated with completed work
- Confidence Score: 95% (exceeds 70% threshold)

Proved Self-Improvement Loop closes: Execute → Learn → Update → Improve

* refactor: responsibility-driven component architecture

Rename components to reflect their responsibilities:
- framework_docs.py → knowledge_base.py (KnowledgeBaseComponent)
- modes.py → behavior_modes.py (BehaviorModesComponent)
- agents.py → agent_personas.py (AgentPersonasComponent)
- commands.py → slash_commands.py (SlashCommandsComponent)
- mcp.py → mcp_integration.py (MCPIntegrationComponent)

Each component now clearly documents its responsibility:
- knowledge_base: Framework knowledge initialization
- behavior_modes: Execution mode definitions
- agent_personas: AI agent personality definitions
- slash_commands: CLI command registration
- mcp_integration: External tool integration

Benefits:
- Self-documenting architecture
- Clear responsibility boundaries
- Easy to navigate and extend
- Scalable for future hierarchical organization

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add project-specific CLAUDE.md with UV rules

- Document UV as required Python package manager
- Add common operations and integration examples
- Document project structure and component architecture
- Provide development workflow guidelines

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* fix: resolve installation failures after framework_docs rename

## Problems Fixed
1. **Syntax errors**: Duplicate docstrings in all component files (line 1)
2. **Dependency mismatch**: Stale framework_docs references after rename to knowledge_base

## Changes
- Fix docstring format in all component files (behavior_modes, agent_personas, slash_commands, mcp_integration)
- Update all dependency references: framework_docs → knowledge_base
- Update component registration calls in knowledge_base.py (5 locations)
- Update install.py files in both setup/ and superclaude/ (5 locations total)
- Fix documentation links in README-ja.md and README-zh.md

## Verification
 All components load successfully without syntax errors
 Dependency resolution works correctly
 Installation completes in 0.5s with all validations passing
 make dev succeeds

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: add automated README translation workflow

## New Features
- **Auto-translation workflow** using GPT-Translate
- Automatically translates README.md to Chinese (ZH) and Japanese (JA)
- Triggers on README.md changes to master/main branches
- Cost-effective: ~¥90/month for typical usage

## Implementation Details
- Uses OpenAI GPT-4 for high-quality translations
- GitHub Actions integration with gpt-translate@v1.1.11
- Secure API key management via GitHub Secrets
- Automatic commit and PR creation on translation updates

## Files Added
- `.github/workflows/translation-sync.yml` - Auto-translation workflow
- `docs/Development/translation-workflow.md` - Setup guide and documentation

## Setup Required
Add `OPENAI_API_KEY` to GitHub repository secrets to enable auto-translation.

## Benefits
- 🤖 Automated translation on every README update
- 💰 Low cost (~$0.06 per translation)
- 🛡️ Secure API key storage
- 🔄 Consistent translation quality across languages

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* fix(mcp): update airis-mcp-gateway URL to correct organization

Fixes #440

## Problem
Code referenced non-existent `oraios/airis-mcp-gateway` repository,
causing MCP installation to fail completely.

## Root Cause
- Repository was moved to organization: `agiletec-inc/airis-mcp-gateway`
- Old reference `oraios/airis-mcp-gateway` no longer exists
- Users reported "not a python/uv module" error

## Changes
- Update install_command URL: oraios → agiletec-inc
- Update run_command URL: oraios → agiletec-inc
- Location: setup/components/mcp_integration.py lines 37-38

## Verification
 Correct URL now references active repository
 MCP installation will succeed with proper organization
 No other code references oraios/airis-mcp-gateway

## Related Issues
- Fixes #440 (Airis-mcp-gateway url has changed)
- Related to #442 (MCP update issues)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: replace cloud translation with local Neural CLI

## Changes

### Removed (OpenAI-dependent)
-  `.github/workflows/translation-sync.yml` - GPT-Translate workflow
-  `docs/Development/translation-workflow.md` - OpenAI setup docs

### Added (Local Ollama-based)
-  `Makefile`: New `make translate` target using Neural CLI
-  `docs/Development/translation-guide.md` - Neural CLI guide

## Benefits

**Before (GPT-Translate)**:
- 💰 Monthly cost: ~¥90 (OpenAI API)
- 🔑 Requires API key setup
- 🌐 Data sent to external API
- ⏱️ Network latency

**After (Neural CLI)**:
-  **$0 cost** - Fully local execution
-  **No API keys** - Zero setup friction
-  **Privacy** - No external data transfer
-  **Fast** - ~1-2 min per README
-  **Offline capable** - Works without internet

## Technical Details

**Neural CLI**:
- Built in Rust with Tauri
- Uses Ollama + qwen2.5:3b model
- Binary size: 4.0MB
- Auto-installs to ~/.local/bin/

**Usage**:
```bash
make translate  # Translates README.md → README-zh.md, README-ja.md
```

## Requirements

- Ollama installed: `curl -fsSL https://ollama.com/install.sh | sh`
- Model downloaded: `ollama pull qwen2.5:3b`
- Neural CLI built: `cd ~/github/neural/src-tauri && cargo build --bin neural-cli --release`

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: kazuki <kazuki@kazukinoMacBook-Air.local>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-18 20:28:10 +05:30

9.4 KiB

Deep Research Configuration

Default Settings

research_defaults:
  planning_strategy: unified
  max_hops: 5
  confidence_threshold: 0.7
  memory_enabled: true
  parallelization: true
  parallel_first: true  # MANDATORY DEFAULT
  sequential_override_requires_justification: true  # NEW
  
parallel_execution_rules:
  DEFAULT_MODE: PARALLEL  # EMPHASIZED
  
  mandatory_parallel:
    - "Multiple search queries"
    - "Batch URL extractions"
    - "Independent analyses"
    - "Non-dependent hops"
    - "Result processing"
    - "Information extraction"
    
  sequential_only_with_justification:
    - reason: "Explicit dependency"
      example: "Hop N requires Hop N-1 results"
    - reason: "Resource constraint"
      example: "API rate limit reached"
    - reason: "User requirement"
      example: "User requests sequential for debugging"
    
  parallel_optimization:
    batch_sizes:
      searches: 5
      extractions: 3
      analyses: 2
    intelligent_grouping:
      by_domain: true
      by_complexity: true
      by_resource: true
  
planning_strategies:
  planning_only:
    clarification: false
    user_confirmation: false
    execution: immediate
    
  intent_planning:
    clarification: true
    max_questions: 3
    execution: after_clarification
    
  unified:
    clarification: optional
    plan_presentation: true
    user_feedback: true
    execution: after_confirmation

hop_configuration:
  max_depth: 5
  timeout_per_hop: 60s
  parallel_hops: true
  loop_detection: true
  genealogy_tracking: true

confidence_scoring:
  relevance_weight: 0.5
  completeness_weight: 0.5
  minimum_threshold: 0.6
  target_threshold: 0.8

self_reflection:
  frequency: after_each_hop
  triggers:
    - confidence_below_threshold
    - contradictions_detected
    - time_elapsed_percentage: 80
    - user_intervention
  actions:
    - assess_quality
    - identify_gaps
    - consider_replanning
    - adjust_strategy

memory_management:
  case_based_reasoning: true
  pattern_learning: true
  session_persistence: true
  cross_session_learning: true
  retention_days: 30

tool_coordination:
  discovery_primary: tavily
  extraction_smart_routing: true
  reasoning_engine: sequential
  memory_backend: serena
  parallel_tool_calls: true

quality_gates:
  planning_gate:
    required_elements: [objectives, strategy, success_criteria]
  execution_gate:
    min_confidence: 0.6
  synthesis_gate:
    coherence_required: true
    clarity_required: true

extraction_settings:
  scraping_strategy: selective
  screenshot_capture: contextual
  authentication_handling: ethical
  javascript_rendering: auto_detect
  timeout_per_page: 15s

Performance Optimizations

optimization_strategies:
  caching:
    - Cache Tavily search results: 1 hour
    - Cache Playwright extractions: 24 hours
    - Cache Sequential analysis: 1 hour
    - Reuse case patterns: always

  parallelization:
    - Parallel searches: max 5
    - Parallel extractions: max 3
    - Parallel analysis: max 2
    - Tool call batching: true

  resource_limits:
    - Max time per research: 10 minutes
    - Max search iterations: 10
    - Max hops: 5
    - Max memory per session: 100MB

Strategy Selection Rules

strategy_selection:
  planning_only:
    indicators:
      - Clear, specific query
      - Technical documentation request
      - Well-defined scope
      - No ambiguity detected
    
  intent_planning:
    indicators:
      - Ambiguous terms present
      - Broad topic area
      - Multiple possible interpretations
      - User expertise unknown
    
  unified:
    indicators:
      - Complex multi-faceted query
      - User collaboration beneficial
      - Iterative refinement expected
      - High-stakes research

Source Credibility Matrix

source_credibility:
  tier_1_sources:
    score: 0.9-1.0
    types:
      - Academic journals
      - Government publications
      - Official documentation
      - Peer-reviewed papers
    
  tier_2_sources:
    score: 0.7-0.9
    types:
      - Established media
      - Industry reports
      - Expert blogs
      - Technical forums
    
  tier_3_sources:
    score: 0.5-0.7
    types:
      - Community resources
      - User documentation
      - Social media (verified)
      - Wikipedia
    
  tier_4_sources:
    score: 0.3-0.5
    types:
      - User forums
      - Social media (unverified)
      - Personal blogs
      - Comments sections

Depth Configurations

research_depth_profiles:
  quick:
    max_sources: 10
    max_hops: 1
    iterations: 1
    time_limit: 2 minutes
    confidence_target: 0.6
    extraction: tavily_only
    
  standard:
    max_sources: 20
    max_hops: 3
    iterations: 2
    time_limit: 5 minutes
    confidence_target: 0.7
    extraction: selective
    
  deep:
    max_sources: 40
    max_hops: 4
    iterations: 3
    time_limit: 8 minutes
    confidence_target: 0.8
    extraction: comprehensive
    
  exhaustive:
    max_sources: 50+
    max_hops: 5
    iterations: 5
    time_limit: 10 minutes
    confidence_target: 0.9
    extraction: all_sources

Multi-Hop Patterns

hop_patterns:
  entity_expansion:
    description: "Explore entities found in previous hop"
    example: "Paper → Authors → Other works → Collaborators"
    max_branches: 3
    
  concept_deepening:
    description: "Drill down into concepts"
    example: "Topic → Subtopics → Details → Examples"
    max_depth: 4
    
  temporal_progression:
    description: "Follow chronological development"
    example: "Current → Recent → Historical → Origins"
    direction: backward
    
  causal_chain:
    description: "Trace cause and effect"
    example: "Effect → Immediate cause → Root cause → Prevention"
    validation: required

Extraction Routing Rules

extraction_routing:
  use_tavily:
    conditions:
      - Static HTML content
      - Simple article structure
      - No JavaScript requirement
      - Public access
    
  use_playwright:
    conditions:
      - JavaScript rendering required
      - Dynamic content present
      - Authentication needed
      - Interactive elements
      - Screenshots required
    
  use_context7:
    conditions:
      - Technical documentation
      - API references
      - Framework guides
      - Library documentation
    
  use_native:
    conditions:
      - Local file access
      - Simple explanations
      - Code generation
      - General knowledge

Case-Based Learning Schema

case_schema:
  case_id:
    format: "research_[timestamp]_[topic_hash]"
    
  case_content:
    query: "original research question"
    strategy_used: "planning approach"
    successful_patterns:
      - query_formulations: []
      - extraction_methods: []
      - synthesis_approaches: []
    findings:
      key_discoveries: []
      source_credibility_scores: {}
      confidence_levels: {}
    lessons_learned:
      what_worked: []
      what_failed: []
      optimizations: []
    metrics:
      time_taken: seconds
      sources_processed: count
      hops_executed: count
      confidence_achieved: float

Replanning Thresholds

replanning_triggers:
  confidence_based:
    critical: < 0.4
    low: < 0.6
    acceptable: 0.6-0.7
    good: > 0.7
    
  time_based:
    warning: 70% of limit
    critical: 90% of limit
    
  quality_based:
    insufficient_sources: < 3
    contradictions: > 30%
    gaps_identified: > 50%
    
  user_based:
    explicit_request: immediate
    implicit_dissatisfaction: assess

Output Format Templates

output_formats:
  summary:
    max_length: 500 words
    sections: [key_finding, evidence, sources]
    confidence_display: simple
    
  report:
    sections: [executive_summary, methodology, findings, synthesis, conclusions]
    citations: inline
    confidence_display: detailed
    visuals: included
    
  academic:
    sections: [abstract, introduction, methodology, literature_review, findings, discussion, conclusions]
    citations: academic_format
    confidence_display: statistical
    appendices: true

Error Handling

error_handling:
  tavily_errors:
    api_key_missing: "Check TAVILY_API_KEY environment variable"
    rate_limit: "Wait and retry with exponential backoff"
    no_results: "Expand search terms or try alternatives"
    
  playwright_errors:
    timeout: "Skip source or increase timeout"
    navigation_failed: "Mark as inaccessible, continue"
    screenshot_failed: "Continue without visual"
    
  quality_errors:
    low_confidence: "Trigger replanning"
    contradictions: "Seek additional sources"
    insufficient_data: "Expand search scope"

Integration Points

mcp_integration:
  tavily:
    role: primary_search
    fallback: native_websearch
    
  playwright:
    role: complex_extraction
    fallback: tavily_extraction
    
  sequential:
    role: reasoning_engine
    fallback: native_reasoning
    
  context7:
    role: technical_docs
    fallback: tavily_search
    
  serena:
    role: memory_management
    fallback: session_only

Monitoring Metrics

metrics_tracking:
  performance:
    - search_latency
    - extraction_time
    - synthesis_duration
    - total_research_time
    
  quality:
    - confidence_scores
    - source_diversity
    - coverage_completeness
    - contradiction_rate
    
  efficiency:
    - cache_hit_rate
    - parallel_execution_rate
    - memory_usage
    - api_cost
    
  learning:
    - pattern_reuse_rate
    - strategy_success_rate
    - improvement_trajectory