* fix: resolve 8 pipeline bugs found during skill quality review - Fix 0 APIs extracted from documentation by enriching summary.json with individual page file content before conflict detection - Fix all "Unknown" entries in merged_api.md by injecting dict keys as API names and falling back to AI merger field names - Fix frontmatter using raw slugs instead of config name by normalizing frontmatter after SKILL.md generation - Fix leaked absolute filesystem paths in patterns/index.md by stripping .skillseeker-cache repo clone prefixes - Fix ARCHITECTURE.md file count always showing "1 files" by counting files per language from code_analysis data - Fix YAML parse errors on GitHub Actions workflows by converting boolean keys (on: true) to strings - Fix false React/Vue.js framework detection in C# projects by filtering web frameworks based on primary language - Improve how-to guide generation by broadening workflow example filter to include setup/config examples with sufficient complexity - Fix test_git_sources_e2e failures caused by git init default branch being 'main' instead of 'master' Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address 6 review issues in ExecutionContext implementation Fixes from code review: 1. Mode resolution (#3 critical): _args_to_data no longer unconditionally overwrites mode. Only writes mode="api" when --api-key explicitly passed. Env-var-based mode detection moved to _default_data() as lowest priority. 2. Re-initialization warning (#4): initialize() now logs debug message when called a second time instead of silently returning stale instance. 3. _raw_args preserved in override (#5): temp context now copies _raw_args from parent so get_raw() works correctly inside override blocks. 4. test_local_mode_detection env cleanup (#7): test now saves/restores API key env vars to prevent failures when ANTHROPIC_API_KEY is set. 5. _load_config_file error handling (#8): wraps FileNotFoundError and JSONDecodeError with user-friendly ValueError messages. 6. Lint fixes: added logging import, fixed Generator import from collections.abc, fixed AgentClient return type annotation. Remaining P2/P3 items (documented, not blocking): - Lock TOCTOU in override() — safe on CPython, needs fix for no-GIL - get() reads _instance without lock — same CPython caveat - config_path not stored on instance - AnalysisSettings.depth not Literal constrained Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address all remaining P2/P3 review issues in ExecutionContext 1. Thread safety: get() now acquires _lock before reading _instance (#2) 2. Thread safety: override() saves/restores _initialized flag to prevent re-init during override blocks (#10) 3. Config path stored: _config_path PrivateAttr + config_path property (#6) 4. Literal validation: AnalysisSettings.depth now uses Literal["surface", "deep", "full"] — rejects invalid values (#9) 5. Test updated: test_analysis_depth_choices now expects ValidationError for invalid depth, added test_analysis_depth_valid_choices 6. Lint cleanup: removed unused imports, fixed whitespace in tests All 10 previously reported issues now resolved. 26 tests pass, lint clean. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: restore 5 truncated scrapers, migrate unified_scraper, fix context init 5 scrapers had main() truncated with "# Original main continues here..." after Kimi's migration — business logic was never connected: - html_scraper.py — restored HtmlToSkillConverter extraction + build - pptx_scraper.py — restored PptxToSkillConverter extraction + build - confluence_scraper.py — restored ConfluenceToSkillConverter with 3 modes - notion_scraper.py — restored NotionToSkillConverter with 4 sources - chat_scraper.py — restored ChatToSkillConverter extraction + build unified_scraper.py — migrated main() to context-first pattern with argv fallback Fixed context initialization chain: - main.py no longer initializes ExecutionContext (was stealing init from commands) - create_command.py now passes config_path from source_info.parsed - execution_context.py handles SourceInfo.raw_input (not raw_source) All 18 scrapers now genuinely migrated. 26 tests pass, lint clean. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: resolve 7 data flow conflicts between ExecutionContext and legacy paths Critical fixes (CLI args silently lost): - unified_scraper Phase 6: reads ctx.enhancement.level instead of raw JSON when args=None (#3, #4) - unified_scraper Phase 6 agent: reads ctx.enhancement.agent instead of 3 independent env var lookups (#5) - doc_scraper._run_enhancement: uses agent_client.api_key instead of raw os.environ.get() — respects config file api_key (#1) Important fixes: - main._handle_analyze_command: populates _fake_args from ExecutionContext so --agent and --api-key aren't lost in analyze→enhance path (#6) - doc_scraper type annotations: replaced forward refs with Any to avoid F821 undefined name errors All changes include RuntimeError fallback for backward compatibility when ExecutionContext isn't initialized. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: 3 crashes + 1 stub in migrated scrapers found by deep scan 1. github_scraper.py: args.scrape_only and args.enhance_level crash when args=None (context path). Guarded with if args and getattr(). Also fixed agent fallback to read ctx.enhancement.agent. 2. codebase_scraper.py: args.output and args.skip_api_reference crash in summary block when args=None. Replaced with output_dir local var and ctx.analysis.skip_api_reference. 3. epub_scraper.py: main() was still a stub ending with "# Rest of main() continues..." — restored full extraction + build + enhancement logic using ctx values exclusively. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: complete ExecutionContext migration for remaining scrapers Kimi's Phase 4 scraper migrations + Claude's review fixes. All 18 scrapers now use context-first pattern with argv fallback. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: Phase 1 — ExecutionContext.get() always returns context (no RuntimeError) get() now returns a default context instead of raising RuntimeError when not explicitly initialized. This eliminates the need for try/except RuntimeError blocks in all 18 scrapers. Components can always call ExecutionContext.get() safely — it returns defaults if not initialized, or the explicitly initialized instance. Updated tests: test_get_returns_defaults_when_not_initialized, test_reset_clears_instance (no longer expects RuntimeError). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: Phase 2a-c — remove 16 individual scraper CLI commands Removed individual scraper commands from: - COMMAND_MODULES in main.py (16 entries: scrape, github, pdf, word, epub, video, jupyter, html, openapi, asciidoc, pptx, rss, manpage, confluence, notion, chat) - pyproject.toml entry points (16 skill-seekers-<type> binaries) - parsers/__init__.py (16 parser registrations) All source types now accessed via: skill-seekers create <source> Kept: create, unified, analyze, enhance, package, upload, install, install-agent, config, doctor, and utility commands. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: create SkillConverter base class + converter registry New base interface that all 17 converters will inherit: - SkillConverter.run() — extract + build (same call for all types) - SkillConverter.extract() — override in subclass - SkillConverter.build_skill() — override in subclass - get_converter(source_type, config) — factory from registry - CONVERTER_REGISTRY — maps source type → (module, class) create_command will use get_converter() instead of _call_module(). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: Grand Unification — one command, one interface, direct converters Complete the Grand Unification refactor: `skill-seekers create` is now the single entry point for all 18 source types. Individual scraper CLI commands (scrape, github, pdf, analyze, unified, etc.) are removed. ## Architecture changes - **18 SkillConverter subclasses**: Every scraper now inherits SkillConverter with extract() + build_skill() + SOURCE_TYPE. Factory via get_converter(). - **create_command.py rewritten**: _build_config() constructs config dicts from ExecutionContext for each source type. Direct converter.run() calls replace the old _build_argv() + sys.argv swap + _call_module() machinery. - **main.py simplified**: create command bypasses _reconstruct_argv entirely, calls CreateCommand(args).execute() directly. analyze/unified commands removed (create handles both via auto-detection). - **CreateParser mode="all"**: Top-level parser now accepts all 120+ flags (--browser, --max-pages, --depth, etc.) since create is the only entry. - **Centralized enhancement**: Runs once in create_command after converter, not duplicated in each scraper. - **MCP tools use converters**: 5 scraping tools call get_converter() directly instead of subprocess. Config type auto-detected from keys. - **ConfigValidator → UniSkillConfigValidator**: Renamed with backward- compat alias. - **Data flow**: AgentClient + LocalSkillEnhancer read ExecutionContext first, env vars as fallback. ## What was removed - main() from all 18 scraper files (~3400 lines) - 18 CLI commands from COMMAND_MODULES + pyproject.toml entry points - analyze + unified parsers from parser registry - _build_argv, _call_module, _SKIP_ARGS, _DEST_TO_FLAG, all _route_*() - setup_argument_parser, get_configuration, _check_deprecated_flags - Tests referencing removed commands/functions ## Net impact 51 files changed, ~6000 lines removed. 2996 tests pass, 0 failures. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: review fixes for Grand Unification PR - Add autouse conftest fixture to reset ExecutionContext singleton between tests - Replace hardcoded defaults in _is_explicitly_set() with parser-derived defaults - Upgrade ExecutionContext double-init log from debug to info - Use logger.exception() in SkillConverter.run() to preserve tracebacks - Fix docstring "17 types" → "18 types" in skill_converter.py - DRY up 10 copy-paste help handlers into dict + loop (~100 lines removed) - Fix 2 CI workflows still referencing removed `skill-seekers scrape` command - Remove broken pyproject.toml entry point for codebase_scraper:main Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: resolve 12 logic/flow issues found in deep review Critical fixes: - UnifiedScraper.run(): replace sys.exit(1) with return 1, add return 0 - doc_scraper: use ExecutionContext.get() when already initialized instead of re-calling initialize() which silently discards new config - unified_scraper: define enhancement_config before try/except to prevent UnboundLocalError in LOCAL enhancement timeout read Important fixes: - override(): cleaner tuple save/restore for singleton swap - --agent without --api-key now sets mode="local" so env API key doesn't override explicit agent choice - Remove DeprecationWarning from _reconstruct_argv (fires on every non-create command in production) - Rewrite scrape_generic_tool to use get_converter() instead of subprocess calls to removed main() functions - SkillConverter.run() checks build_skill() return value, returns 1 if False - estimate_pages_tool uses -m module invocation instead of .py file path Low-priority fixes: - get_converter() raises descriptive ValueError on class name typo - test_default_values: save/clear API key env vars before asserting mode - test_get_converter_pdf: fix config key "path" → "pdf_path" 3056 passed, 4 failed (pre-existing dep version issues), 32 skipped. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: update MCP server tests to mock converter instead of subprocess scrape_docs_tool now uses get_converter() + _run_converter() in-process instead of run_subprocess_with_streaming. Update 4 TestScrapeDocsTool tests to mock the converter layer instead of the removed subprocess path. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: YusufKaraaslanSpyke <yusuf@spykegames.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
253 lines
11 KiB
Markdown
253 lines
11 KiB
Markdown
# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project Overview
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**Skill Seekers** converts documentation from 17 source types into production-ready formats for 24+ AI platforms (LLM platforms, RAG frameworks, vector databases, AI coding assistants). Published on PyPI as `skill-seekers`.
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**Version:** 3.4.0 | **Python:** 3.10+ | **Website:** https://skillseekersweb.com/
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**Architecture:** See `docs/UML_ARCHITECTURE.md` for UML diagrams and module overview. StarUML project at `docs/UML/skill_seekers.mdj`.
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## Essential Commands
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```bash
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# REQUIRED before running tests or CLI (src/ layout)
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pip install -e .
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# Run all tests (NEVER skip - all must pass before commits)
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pytest tests/ -v
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# Fast iteration (skip slow MCP tests ~20min)
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pytest tests/ --ignore=tests/test_mcp_fastmcp.py --ignore=tests/test_mcp_server.py --ignore=tests/test_install_skill_e2e.py -q
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# Single test
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pytest tests/test_scraper_features.py::test_detect_language -vv -s
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# Code quality (must pass before push - matches CI)
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uvx ruff check src/ tests/
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uvx ruff format --check src/ tests/
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mypy src/skill_seekers # continue-on-error in CI
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# Auto-fix lint/format issues
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uvx ruff check --fix --unsafe-fixes src/ tests/
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uvx ruff format src/ tests/
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# Build & publish
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uv build
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uv publish
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```
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## CI Matrix
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Runs on push/PR to `main` or `development`. Lint job (Python 3.12, Ubuntu) + Test job (Ubuntu + macOS, Python 3.10/3.11/3.12, excludes macOS+3.10). Both must pass for merge.
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## Git Workflow
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- **Main branch:** `main` (requires tests + 1 review)
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- **Development branch:** `development` (default PR target, requires tests)
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- **Feature branches:** `feature/{task-id}-{description}` from `development`
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- PRs always target `development`, never `main` directly
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## Architecture
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### CLI: Unified create command
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Entry point `src/skill_seekers/cli/main.py`. The `create` command is the **only** entry point for skill creation — it auto-detects source type and routes to the appropriate `SkillConverter`.
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```
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skill-seekers create <source> # Auto-detect: URL, owner/repo, ./path, file.pdf, etc.
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skill-seekers package <dir> # Package for platform (--target claude/gemini/openai/markdown/minimax/opencode/kimi/deepseek/qwen/openrouter/together/fireworks, --format langchain/llama-index/haystack/chroma/faiss/weaviate/qdrant/pinecone)
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```
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### SkillConverter Pattern (Template Method + Factory)
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All 18 source types implement the `SkillConverter` base class (`skill_converter.py`):
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```python
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converter = get_converter("web", config) # Factory lookup
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converter.run() # Template: extract() → build_skill()
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```
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Registry in `CONVERTER_REGISTRY` maps source type → (module, class). `create_command.py` builds config from `ExecutionContext`, calls `get_converter()`, then runs centralized enhancement.
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### Data Flow (5 phases)
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1. **Scrape** - Source-specific scraper extracts content to `output/{name}_data/pages/*.json`
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2. **Build** - `build_skill()` categorizes pages, extracts patterns, generates `output/{name}/SKILL.md`
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3. **Enhance** (optional) - LLM rewrites SKILL.md (`--enhance-level 0-3`, auto-detects API vs LOCAL mode)
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4. **Package** - Platform adaptor formats output (`.zip`, `.tar.gz`, JSON, vector index)
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5. **Upload** (optional) - Platform API upload
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### Platform Adaptor Pattern (Strategy + Factory)
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Factory: `get_adaptor(platform, config)` in `adaptors/__init__.py` returns a `SkillAdaptor` instance. Base class `SkillAdaptor` + `SkillMetadata` in `adaptors/base.py`.
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```
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src/skill_seekers/cli/adaptors/
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├── __init__.py # Factory: get_adaptor(platform, config), ADAPTORS registry
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├── base.py # Abstract base: SkillAdaptor, SkillMetadata
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├── openai_compatible.py # Shared base for OpenAI-compatible platforms
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├── claude.py # --target claude
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├── gemini.py # --target gemini
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├── openai.py # --target openai
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├── markdown.py # --target markdown
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├── minimax.py # --target minimax
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├── opencode.py # --target opencode
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├── kimi.py # --target kimi
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├── deepseek.py # --target deepseek
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├── qwen.py # --target qwen
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├── openrouter.py # --target openrouter
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├── together.py # --target together
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├── fireworks.py # --target fireworks
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├── langchain.py # --format langchain
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├── llama_index.py # --format llama-index
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├── haystack.py # --format haystack
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├── chroma.py # --format chroma
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├── faiss_helpers.py # --format faiss
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├── qdrant.py # --format qdrant
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├── weaviate.py # --format weaviate
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├── pinecone_adaptor.py # --format pinecone
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└── streaming_adaptor.py # --format streaming
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```
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`--target` = LLM platforms, `--format` = RAG/vector DBs. All adaptors are imported with `try/except ImportError` so missing optional deps don't break the registry.
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### 18 Source Type Converters
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Each in `src/skill_seekers/cli/{type}_scraper.py` as a `SkillConverter` subclass (no `main()`). The `create_command.py` uses `source_detector.py` to auto-detect, then calls `get_converter()`. Converters: web (doc_scraper), github, pdf, word, epub, video, local (codebase_scraper), jupyter, html, openapi, asciidoc, pptx, rss, manpage, confluence, notion, chat, config (unified_scraper).
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### CLI Argument System
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```
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src/skill_seekers/cli/
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├── parsers/ # Subcommand parser registration
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│ └── create_parser.py # Progressive help disclosure (--help-web, --help-github, etc.)
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├── arguments/ # Argument definitions
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│ ├── common.py # add_all_standard_arguments() - shared across all scrapers
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│ └── create.py # UNIVERSAL_ARGUMENTS, WEB_ARGUMENTS, GITHUB_ARGUMENTS, etc.
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└── source_detector.py # Auto-detect source type from input string
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```
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### C3.x Codebase Analysis Pipeline
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Local codebase analysis features, all opt-out (`--skip-*` flags):
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- C3.1 `pattern_recognizer.py` - Design pattern detection (10 GoF patterns, 9 languages)
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- C3.2 `test_example_extractor.py` - Usage examples from tests
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- C3.3 `how_to_guide_builder.py` - AI-enhanced educational guides
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- C3.4 `config_extractor.py` - Configuration pattern extraction
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- C3.5 `generate_router.py` - Architecture overview generation
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- C3.10 `signal_flow_analyzer.py` - Godot signal flow analysis
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### MCP Server
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`src/skill_seekers/mcp/server_fastmcp.py` - 40 tools via FastMCP. Transport: stdio (Claude Code) or HTTP (Cursor/Windsurf). Optional dependency: `pip install -e ".[mcp]"`
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Supporting modules:
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- `marketplace_publisher.py` - Publish skills to plugin marketplace repositories
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- `marketplace_manager.py` - Manage marketplace registry
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- `config_publisher.py` - Push configs to registered config source repositories
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### Enhancement Modes (via AgentClient)
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Enhancement now uses the `AgentClient` abstraction (`src/skill_seekers/cli/agent_client.py`) instead of direct Claude API calls:
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- **API mode** (if API key set): Supports Anthropic, Moonshot/Kimi, Google Gemini, OpenAI
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- **LOCAL mode** (fallback): Supports Claude Code, Kimi Code, Codex, Copilot, OpenCode, custom agents
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- Control: `--enhance-level 0` (off) / `1` (SKILL.md only) / `2` (default, balanced) / `3` (full)
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- Agent selection: `--agent claude|codex|copilot|opencode|kimi|custom`
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## Key Implementation Details
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### Smart Categorization (`doc_scraper.py:smart_categorize()`)
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Scores pages against category keywords: 3 points for URL match, 2 for title, 1 for content. Threshold of 2+ required. Falls back to "other".
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### Content Extraction (`doc_scraper.py`)
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`FALLBACK_MAIN_SELECTORS` constant + `_find_main_content()` helper handle CSS selector fallback. Links are extracted from the full page before early return (not just main content). `body` is deliberately excluded from fallbacks.
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### Three-Stream GitHub Architecture (`unified_codebase_analyzer.py`)
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Stream 1: Code Analysis (AST, patterns, tests, guides). Stream 2: Documentation (README, docs/, wiki). Stream 3: Community (issues, PRs, metadata). Depth control: `basic` (1-2 min) or `c3x` (20-60 min).
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## Testing
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### Test markers (pytest.ini)
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```bash
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pytest tests/ -v # Default: fast tests only
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pytest tests/ -v -m slow # Include slow tests (>5s)
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pytest tests/ -v -m integration # External services required
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pytest tests/ -v -m e2e # Resource-intensive
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pytest tests/ -v -m "not slow and not integration" # Fastest subset
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```
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### Known legitimate skips (~11)
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- 2: chromadb incompatible with Python 3.14 (pydantic v1)
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- 2: weaviate-client not installed
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- 2: Qdrant not running (requires docker)
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- 2: langchain/llama_index not installed
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- 3: GITHUB_TOKEN not set
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### sys.modules gotcha
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`test_swift_detection.py` deletes `skill_seekers.cli` modules from `sys.modules`. It must save and restore both `sys.modules` entries AND parent package attributes (`setattr`). See the test file for the pattern.
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## Dependencies
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Core deps include `langchain`, `llama-index`, `anthropic`, `httpx`, `PyMuPDF`, `pydantic`. Platform-specific deps are optional:
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```bash
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pip install -e ".[mcp]" # MCP server
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pip install -e ".[gemini]" # Google Gemini
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pip install -e ".[openai]" # OpenAI
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pip install -e ".[docx]" # Word documents
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pip install -e ".[epub]" # EPUB books
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pip install -e ".[video]" # Video (lightweight)
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pip install -e ".[video-full]"# Video (Whisper + visual)
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pip install -e ".[jupyter]" # Jupyter notebooks
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pip install -e ".[pptx]" # PowerPoint
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pip install -e ".[rss]" # RSS/Atom feeds
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pip install -e ".[confluence]"# Confluence wiki
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pip install -e ".[notion]" # Notion pages
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pip install -e ".[chroma]" # ChromaDB
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pip install -e ".[all]" # Everything (except video-full)
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```
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Dev dependencies use PEP 735 `[dependency-groups]` in pyproject.toml.
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## Environment Variables
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```bash
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ANTHROPIC_API_KEY=sk-ant-... # Claude AI (or compatible endpoint)
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ANTHROPIC_BASE_URL=https://... # Optional: Claude-compatible API endpoint
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GOOGLE_API_KEY=AIza... # Google Gemini (optional)
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OPENAI_API_KEY=sk-... # OpenAI (optional)
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GITHUB_TOKEN=ghp_... # Higher GitHub rate limits
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```
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## Adding New Features
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### New platform adaptor
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1. Create `src/skill_seekers/cli/adaptors/{platform}.py` inheriting `SkillAdaptor` from `base.py`
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2. Register in `adaptors/__init__.py` (add try/except import + add to `ADAPTORS` dict)
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3. Add optional dep to `pyproject.toml`
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4. Add tests in `tests/`
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### New source type converter
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1. Create `src/skill_seekers/cli/{type}_scraper.py` with a class inheriting `SkillConverter`
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2. Implement `extract()` and `build_skill()` methods, set `SOURCE_TYPE`
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3. Register in `CONVERTER_REGISTRY` in `skill_converter.py`
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4. Add source type config building in `create_command.py:_build_config()`
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5. Add auto-detection in `source_detector.py`
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6. Add optional dep if needed
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7. Add tests
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### New CLI argument
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- Universal: `UNIVERSAL_ARGUMENTS` in `arguments/create.py`
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- Source-specific: appropriate dict (`WEB_ARGUMENTS`, `GITHUB_ARGUMENTS`, etc.)
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- Shared across scrapers: `add_all_standard_arguments()` in `arguments/common.py`
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