- Filter out chunks smaller than min_chunk_size (default 100 tokens)
- Exception: Keep all chunks if entire document is smaller than target size
- All 15 tests passing (100% pass rate)
Fixes edge case where very small chunks (e.g., 'Short.' = 6 chars) were
being created despite min_chunk_size=100 setting.
Test: pytest tests/test_rag_chunker.py -v
- Remove hardcoded version string
- Import from skill_seekers._version instead
- Ensures single source of truth for version management
- Future version bumps only need pyproject.toml update
Thanks @franklegolasyoung for the excellent work on the core fixes for issues #267, #242, and #260! 🙏
Your comprehensive approach to fixing PDF processing, expanding workflow detection, and improving the Chinese README documentation is much appreciated. I've added code quality fixes and comprehensive tests to ensure everything passes CI.
All 1266+ tests are now passing, and the issues are resolved! 🎉
Complete implementation of C3.9, granular AI enhancement control, performance optimizations, and bug fixes.
Features:
- C3.9 Project Documentation Extraction (markdown files)
- Granular AI enhancement control (--enhance-level 0-3)
- C# test extraction support
- 6-12x faster LOCAL mode with parallel execution
- Auto-enhancement UX improvements
- LOCAL mode fallback for all AI enhancements
Bug Fixes:
- C# language support
- Config type field compatibility
- LocalSkillEnhancer import
Documentation:
- Updated CHANGELOG.md
- Updated CLAUDE.md
- Removed client-specific files
Tests: All 1,257 tests passing
Critical linter errors: Fixed
CRITICAL BUG FIX - Resolves 404 errors when fetching configs from API
Root Cause:
The code was constructing download URLs manually:
download_url = f"{API_BASE_URL}/api/download/{config_name}.json"
This fails because the API provides download_url in the response, which
may differ from the constructed path (e.g., CDN URLs, version-specific paths).
Solution:
Changed both MCP server implementations to use download_url from API:
download_url = config_info.get("download_url")
Added validation check for missing download_url field.
Files Modified:
- src/skill_seekers/mcp/tools/source_tools.py (FastMCP server, line 285-297)
- src/skill_seekers/mcp/server_legacy.py (Legacy server, line 1483-1494)
Bug Report:
User reported: skill-seekers install --config godot --unlimited
- API check: /api/configs/godot → 200 OK ✅
- Download: /api/download/godot.json → 404 Not Found ❌
After Fix:
- Uses download_url from API response → Works correctly ✅
Testing:
✅ All 15 source tools tests pass (test_mcp_fastmcp.py::TestSourceTools)
✅ All 8 fetch_config tests pass
✅ test_fetch_config_download_api: PASSED
✅ test_fetch_config_from_source: PASSED
Impact:
- Fixes config downloads from official API (skillseekersweb.com)
- Fixes config downloads from private Git repositories
- Prevents all future 404 errors from URL construction mismatch
- No breaking changes - fully backward compatible
Related Issue: Bug reported by user when testing Godot skill
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Start development cycle for v2.8.0.
Version updated in 5 locations:
- pyproject.toml
- src/skill_seekers/__init__.py
- src/skill_seekers/cli/__init__.py
- src/skill_seekers/mcp/__init__.py
- src/skill_seekers/mcp/tools/__init__.py
All version numbers synchronized to prevent Issue #248.
[Unreleased] section in CHANGELOG.md ready for v2.8.0 changes.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Fixed case-sensitivity bug where regex patterns failed to match output messages
due to case mismatch between 'saved to:' (lowercase in regex) and 'Saved to:'
(uppercase in actual output).
Changes:
- Line 529: Added (?i) flag to config path extraction regex
- Line 668: Added (?i) flag to package path extraction regex
This fixes the issue where 'skill-seekers install --config react' would:
1. Successfully download and save config to disk
2. Output: '📂 Saved to: output/react.json'
3. But fail with '❌ Failed to fetch config' due to regex mismatch
The workflow now correctly continues to Phase 2 (scraping) after fetching config.
Also updated comment on line 528 to reflect actual output format with emoji.
Fixes#236
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Fixed version mismatch bug where hardcoded versions were out of sync
with pyproject.toml.
Updated version from 2.5.2 to 2.7.0 in:
- src/skill_seekers/__init__.py
- src/skill_seekers/cli/__init__.py
- src/skill_seekers/mcp/__init__.py
- src/skill_seekers/mcp/tools/__init__.py
Now skill-seekers --version correctly reports: 2.7.0
Fixes#248
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add comprehensive AI enhancement to C3.4 Configuration Pattern Extraction
similar to C3.3's dual-mode architecture (API + LOCAL).
NEW CAPABILITIES (What users can do now):
1. **AI-Powered Config Analysis** - Understand what configs do, not just extract them
- Explanations: What each configuration setting does
- Best Practices: Suggested improvements and better organization
- Security Analysis: Identifies hardcoded secrets, exposed credentials
- Migration Suggestions: Opportunities to consolidate configs
- Context: Explains detected patterns and when to use them
2. **Dual-Mode AI Support** (Same as C3.3):
- API Mode: Claude API analyzes configs (requires ANTHROPIC_API_KEY)
- LOCAL Mode: Claude Code CLI (FREE, no API key needed)
- AUTO Mode: Automatically detects best available mode
3. **Seamless Integration**:
- CLI: --enhance, --enhance-local, --ai-mode flags
- Codebase Scraper: Works with existing enhance_with_ai parameter
- MCP Tools: Enhanced extract_config_patterns with AI parameters
- Optional: Enhancement only runs when explicitly requested
Components Added:
- ConfigEnhancer class (~400 lines) - Dual-mode AI enhancement engine
- Enhanced CLI flags in config_extractor.py
- AI integration in codebase_scraper.py config extraction workflow
- MCP tool parameter expansion (enhance, enhance_local, ai_mode)
- FastMCP server tool signature updates
- Comprehensive documentation in CHANGELOG.md and README.md
Performance:
- Basic extraction: ~3 seconds for 100 config files
- With AI enhancement: +30-60 seconds (LOCAL mode, FREE)
- With AI enhancement: +20-40 seconds (API mode, ~$0.10-0.20)
Use Cases:
- Security audits: Find hardcoded secrets across all configs
- Migration planning: Identify consolidation opportunities
- Onboarding: Understand what each config file does
- Best practices: Get improvement suggestions for config organization
Technical Details:
- Structured JSON prompts for reliable AI responses
- 5 enhancement categories: explanations, best_practices, security, migration, context
- Graceful fallback if AI enhancement fails
- Security findings logged separately for visibility
- Results stored in JSON under 'ai_enhancements' key
Testing:
- 28 comprehensive tests in test_config_extractor.py
- Tests cover: file detection, parsing, pattern detection, enhancement modes
- All integrations tested: CLI, codebase_scraper, MCP tools
Documentation:
- CHANGELOG.md: Complete C3.4 feature description
- README.md: Updated C3.4 section with AI enhancement
- MCP tool descriptions: Added AI enhancement details
Related Issues: #74🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
- Add build_dependency_graph parameter to scrape_codebase MCP tool
- Update tool documentation with new parameter
- Pass --build-dependency-graph flag to CLI command
- Update FastMCP server function signature
Usage via MCP:
scrape_codebase(
directory="/path/to/repo",
build_dependency_graph=True
)
This completes the C2.6 feature set by exposing dependency graph
generation through the MCP interface, making it available to all
MCP clients (Claude Code, Cursor, etc.).
- Switch from manual package listing to automatic discovery
- Improves maintainability and prevents missing module bugs
- All tests passing (700+ tests)
- Package contents verified identical to v2.5.1
Fixes#226
Merges #227
Thanks to @iamKhan79690 for the contribution!
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Co-Authored-By: Anas Ur Rehman (@iamKhan79690) <noreply@github.com>
- Replace TextContent = None with proper fallback class in all MCP tool modules
- Fixes TypeError when MCP library is not fully initialized in test environment
- Ensures all 700 tests pass (was 699 passing, 1 failing)
- Affected files:
* packaging_tools.py
* config_tools.py
* scraping_tools.py
* source_tools.py
* splitting_tools.py
The fallback class maintains the same interface as mcp.types.TextContent,
allowing tests to run successfully even when the MCP library import fails.
Test results: ✅ 700 passed, 157 skipped, 2 warnings
