* 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>
198 lines
6.1 KiB
YAML
198 lines
6.1 KiB
YAML
# Automated Skill Updates - Runs weekly to refresh documentation
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# Security Note: Schedule triggers with hardcoded constants. Workflow_dispatch input
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# accessed via FRAMEWORKS_INPUT env variable (safe pattern).
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name: Scheduled Skill Updates
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on:
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schedule:
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# Run every Sunday at 3 AM UTC
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- cron: '0 3 * * 0'
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workflow_dispatch:
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inputs:
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frameworks:
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description: 'Frameworks to update (comma-separated or "all")'
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required: false
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default: 'all'
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type: string
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jobs:
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update-skills:
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name: Update ${{ matrix.framework }}
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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# Popular frameworks to keep updated
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framework:
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- react
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- django
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- fastapi
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- godot
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- vue
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- flask
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env:
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FRAMEWORK: ${{ matrix.framework }}
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FRAMEWORKS_INPUT: ${{ github.event.inputs.frameworks }}
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steps:
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- uses: actions/checkout@v4
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with:
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submodules: recursive
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- name: Set up Python 3.12
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uses: actions/setup-python@v5
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with:
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python-version: '3.12'
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -e .
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- name: Check if framework should be updated
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id: should_update
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run: |
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FRAMEWORKS_INPUT="${FRAMEWORKS_INPUT:-all}"
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if [ "$FRAMEWORKS_INPUT" = "all" ] || [ -z "$FRAMEWORKS_INPUT" ]; then
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echo "update=true" >> $GITHUB_OUTPUT
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elif echo "$FRAMEWORKS_INPUT" | grep -q "$FRAMEWORK"; then
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echo "update=true" >> $GITHUB_OUTPUT
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else
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echo "update=false" >> $GITHUB_OUTPUT
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echo "⏭️ Skipping $FRAMEWORK (not in update list)"
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fi
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- name: Check for existing skill
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if: steps.should_update.outputs.update == 'true'
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id: check_existing
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run: |
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SKILL_DIR="output/$FRAMEWORK"
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if [ -d "$SKILL_DIR" ]; then
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echo "exists=true" >> $GITHUB_OUTPUT
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echo "📦 Found existing skill at $SKILL_DIR"
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else
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echo "exists=false" >> $GITHUB_OUTPUT
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echo "🆕 No existing skill found"
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fi
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- name: Incremental update (if exists)
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if: steps.should_update.outputs.update == 'true' && steps.check_existing.outputs.exists == 'true'
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run: |
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echo "⚡ Performing incremental update for $FRAMEWORK..."
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SKILL_DIR="output/$FRAMEWORK"
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# Detect changes using incremental updater
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python3 -c "
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import sys, os
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from pathlib import Path
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from skill_seekers.cli.incremental_updater import IncrementalUpdater
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framework = os.environ['FRAMEWORK']
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skill_dir = Path(f'output/{framework}')
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updater = IncrementalUpdater(skill_dir)
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changes = updater.detect_changes()
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if changes.has_changes:
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print(f'Changes detected:')
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print(f' Added: {len(changes.added)}')
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print(f' Modified: {len(changes.modified)}')
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print(f' Deleted: {len(changes.deleted)}')
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updater.current_versions = updater._scan_documents()
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updater.save_current_versions()
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else:
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print('No changes detected, skill is up to date')
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"
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- name: Full scrape (if new or manual)
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if: steps.should_update.outputs.update == 'true' && steps.check_existing.outputs.exists == 'false'
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run: |
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echo "📥 Performing full scrape for $FRAMEWORK..."
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CONFIG_FILE="configs/${FRAMEWORK}.json"
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if [ ! -f "$CONFIG_FILE" ]; then
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echo "⚠️ Config not found: $CONFIG_FILE"
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exit 0
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fi
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# Use streaming ingestion for large docs
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skill-seekers create "$CONFIG_FILE" --max-pages 200
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- name: Generate quality report
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if: steps.should_update.outputs.update == 'true'
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run: |
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SKILL_DIR="output/$FRAMEWORK"
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if [ ! -d "$SKILL_DIR" ]; then
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echo "⚠️ Skill directory not found"
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exit 0
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fi
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echo "📊 Generating quality metrics..."
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python3 -c "
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import sys, os
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from pathlib import Path
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from skill_seekers.cli.quality_metrics import QualityAnalyzer
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framework = os.environ['FRAMEWORK']
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skill_dir = Path(f'output/{framework}')
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analyzer = QualityAnalyzer(skill_dir)
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report = analyzer.generate_report()
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print(f'Quality Score: {report.overall_score.grade} ({report.overall_score.total_score:.1f}/100)')
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print(f' Completeness: {report.overall_score.completeness:.1f}%')
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print(f' Accuracy: {report.overall_score.accuracy:.1f}%')
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print(f' Coverage: {report.overall_score.coverage:.1f}%')
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print(f' Health: {report.overall_score.health:.1f}%')
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"
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- name: Package for Claude
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if: steps.should_update.outputs.update == 'true'
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run: |
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SKILL_DIR="output/$FRAMEWORK"
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if [ -d "$SKILL_DIR" ]; then
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echo "📦 Packaging $FRAMEWORK for Claude AI..."
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skill-seekers package "$SKILL_DIR" --target claude
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fi
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- name: Upload updated skill
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if: steps.should_update.outputs.update == 'true'
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uses: actions/upload-artifact@v4
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with:
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name: ${{ env.FRAMEWORK }}-skill-updated
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path: output/${{ env.FRAMEWORK }}.zip
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retention-days: 90
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summary:
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name: Update Summary
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needs: update-skills
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runs-on: ubuntu-latest
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if: always()
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steps:
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- name: Create summary
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run: |
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echo "## 🔄 Scheduled Skills Update" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "**Date:** $(date -u '+%Y-%m-%d %H:%M UTC')" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "### Updated Frameworks" >> $GITHUB_STEP_SUMMARY
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echo "- React" >> $GITHUB_STEP_SUMMARY
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echo "- Django" >> $GITHUB_STEP_SUMMARY
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echo "- FastAPI" >> $GITHUB_STEP_SUMMARY
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echo "- Godot" >> $GITHUB_STEP_SUMMARY
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echo "- Vue" >> $GITHUB_STEP_SUMMARY
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echo "- Flask" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "Updated skills available in workflow artifacts." >> $GITHUB_STEP_SUMMARY
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