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Found 93 Skills
Use this when the Discover (reverse engineering) of legacy projects tends to get out of control in coverage. You need to first conduct module classification (P0/P1/P2) and constrain the depth of reverse engineering, ensuring that high-ROI modules are made traceable first instead of "writing everything but making it unmaintainable."
Structured error classification and recovery during autonomous operation. Classify runtime errors, apply retry strategies with backoff, maintain error logs, and escalate intelligently. Activate when encountering API failures, build tool crashes, file permission issues, or unexpected runtime errors during autonomous work. Triggers on: "error recovery", "retry", "API failure", "crash recovery", "service unavailable".
Standardized error handling patterns with classification, recovery, and logging strategies. error handling, error recovery, graceful degradation, resilience.
[WHAT] Universal content intake system for URLs (GitHub repos, YouTube videos, articles, PDFs) and skill packages (skills.sh, skill:// protocol) [HOW] Phase 1: Clone repos/fetch transcripts/scrape content/resolve skills to ~/lev/workshop/intake/. Phase 2-3: Load workshop/intake.md for full analysis [WHEN] Use when user provides a URL to analyze, says "intake/download", wants to evaluate external content, or references a skill package [WHY] Systematically evaluates external content and skill packages for adoption/adaptation with tier classification and ADR creation Triggers: "intake", "download", "analyze this url", "check out this repo", "review this video", "evaluate content", "install skill", "skill://"
Create GitHub issues with proper task classification. Classification determines which Skills will be used when working on the issue.
Use when the user mentions document parsing, PDF extraction, OCR, markdown extraction, structured data extraction from documents, document classification/splitting, LandingAI, ADE API, or wants to pull data out of a PDF/image/spreadsheet
Integrate with HyperAPI for financial document processing - OCR text extraction, document classification, PDF splitting, and structured data extraction from invoices, receipts, and financial documents. Use when the user needs to parse PDFs, extract text from documents, classify document types, split multi-document PDFs, or extract structured entities like invoice numbers, vendor names, line items. Keywords: hyperapi, hyperbots, document parsing, OCR, PDF processing, invoice extraction, receipt processing, document classification, VLM, vision language model.
Use when "scikit-learn", "sklearn", "machine learning", "classification", "regression", "clustering", or asking about "train test split", "cross validation", "hyperparameter tuning", "ML pipeline", "random forest", "SVM", "preprocessing"
This skill should be used when the user asks to "predictive intelligence", "machine learning", "ML", "classification", "similarity", "clustering", "prediction", "AI", or any ServiceNow Predictive Intelligence development.