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Found 23 Skills
Unstructured integration. Manage data, records, and automate workflows. Use when the user wants to interact with Unstructured data.
Interactive tutorial teaching Snowflake Cortex CLASSIFY_TEXT for categorizing unstructured text. Guide users through classifying customer reviews using Python and SQL. Use when user wants to learn text classification, Cortex LLM functions, or analyze unstructured feedback data.
Extract actionable Linear tickets from ambiguous input — Slack conversations, call transcripts, screenshots, meeting notes, or any unstructured material. Proposes tickets in a scratchpad file for user review, then creates them in Linear on approval. Use when the user wants to turn conversations, transcripts, screenshots, or notes into Linear tickets. Also use when user says "create tickets from this", "send to linear", "make issues from this call/chat", or provides raw material and asks for tickets.
Use this skill when the user asks to parse the content of an unstructured file (PDF, PPTX, DOCX...)
Generate structured narrative text visualizations from data using T8 Syntax. Use when users want to create data interpretation reports, summaries, or structured articles with semantic entity annotations. T8 is designed for unstructured data visualization where T stands for Text and 8 represents a byte of 8 bits, symbolizing deep insights beneath the text.
Review code for logging patterns and suggest evlog adoption. Detects console.log spam, unstructured errors, and missing context. Guides wide event design, structured error handling, request-scoped logging, and log draining with adapters (Axiom, OTLP).
Analyze messy and unstructured Excel files to identify data quality issues, detect format inconsistencies, find missing values, and generate comprehensive analysis reports. Use when Claude needs to work with Excel files (.xlsx, .xls) for data quality assessment, structure analysis, or when users request data auditing, cleaning recommendations, or statistical summaries of spreadsheet data.
Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.
Expert Swift concurrency decisions: async let vs TaskGroup selection, actor isolation boundaries, @MainActor placement strategies, Sendable conformance judgment calls, and structured vs unstructured task trade-offs. Use when designing concurrent code, debugging data races, or choosing between concurrency patterns. Trigger keywords: async, await, actor, Task, TaskGroup, @MainActor, Sendable, concurrency, data race, isolation, structured concurrency, continuation
Pull structured data from messy text using AI. Use when parsing invoices, extracting fields from emails, scraping entities from articles, converting unstructured text to JSON, extracting contact info, parsing resumes, reading forms, or any task where messy text goes in and clean structured data comes out. Powered by DSPy extraction.
Use this skill when the user asks to parse, perform multi-format document conversion or spatially extract text from an unstructured file (PDF, DOCX, PPTX, XLSX, images, etc.) locally without cloud dependencies.
Structured memory creation workflow. Converts messy notes, conversations, and unstructured thoughts into well-typed, tagged, confidence-scored memories. Uses 1-question-at-a-time clarification to avoid cognitive overload.