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  * PROJECT_STATUS.md (4.2KB) → outdated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

3.5 KiB
Raw Blame History

name description category
token-counter Dynamic token usage calculation from system notifications module

Token Counter Module

Purpose: Parse and format real-time token usage from system notifications

Input Source

System provides token notifications after each tool call:

<system_warning>Token usage: [used]/[total]; [remaining] remaining</system_warning>

Example:

Token usage: 57425/200000; 142575 remaining

Calculation Logic

Parse:
  used: Extract first number (57425)
  total: Extract second number (200000)
  remaining: Extract third number (142575)

Compute:
  percentage: (used / total) × 100
  # Example: (57425 / 200000) × 100 = 28.7125%

Format:
  percentage: Round to integer (28.7% → 28%)
  used: Round to K (57425 → 57K)
  total: Round to K (200000 → 200K)
  remaining: Round to K (142575 → 142K)

Output:
  "[%] ([used]K/[total]K) · [remaining]K avail"
  # Example: "28% (57K/200K) · 142K avail"

Formatting Rules

Number Rounding (K format)

Rules:
  < 1,000: Show as-is (e.g., 850 → 850)
  ≥ 1,000: Divide by 1000, round to integer (e.g., 57425 → 57K)

Examples:
  500 → 500
  1500 → 1K (not 2K)
  57425 → 57K
  142575 → 142K
  200000 → 200K

Percentage Rounding

Rules:
  Always round to nearest integer
  No decimal places

Examples:
  28.1% → 28%
  28.7% → 28%
  28.9% → 29%
  30.0% → 30%

Implementation Pattern

Step 1 - Wait for System Notification:
  Execute ANY tool call (Bash, Read, etc.)
  System automatically sends token notification

Step 2 - Extract Values:
  Parse notification text using regex or string split
  Extract: used, total, remaining

Step 3 - Calculate:
  percentage = (used / total) × 100
  Round percentage to integer

Step 4 - Format:
  Convert numbers to K format
  Construct output string

Step 5 - Display:
  🧠 [percentage]% ([used]K/[total]K) · [remaining]K avail

Usage in PM Command

Session Start Protocol (Step 3):
  1. Execute git status (triggers system notification)
  2. Wait for: <system_warning>Token usage: ...</system_warning>
  3. Apply token-counter module logic
  4. Format output: 🧠 [calculated values]
  5. Display to user

Anti-Patterns (FORBIDDEN)

❌ Static Values:
   🧠 30% (60K/200K) · 140K avail  # WRONG - hardcoded

❌ Guessing:
   🧠 ~25% (estimated)  # WRONG - no evidence

❌ Placeholder:
   🧠 [calculating...]  # WRONG - incomplete

✅ Dynamic Calculation:
   🧠 28% (57K/200K) · 142K avail  # CORRECT - real data

Validation

Self-Check Questions:
  ❓ Did I parse the actual system notification?
  ❓ Are the numbers from THIS session, not a template?
  ❓ Does the math check out? (used + remaining = total)
  ❓ Are percentages rounded correctly?
  ❓ Are K values formatted correctly?

Validation Formula:
  used + remaining should equal total
  Example: 57425 + 142575 = 200000 ✅

Edge Cases

No System Notification Yet:
  Action: Execute a tool call first (e.g., git status)
  Then: Parse the notification that appears

Multiple Notifications:
  Action: Use the MOST RECENT notification
  Reason: Token usage increases over time

Parse Failure:
  Fallback: "🧠 [calculating...] (execute a tool first)"
  Then: Retry after next tool call

Integration Points

Used by:

  • commands/pm.md - Session start protocol
  • agents/pm-agent.md - Status reporting
  • Any command requiring token awareness

Dependencies:

  • System-provided notifications (automatic)
  • No external tools required