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Found 6,200 Skills
JFrog integration. Manage data, records, and automate workflows. Use when the user wants to interact with JFrog data.
Expert in Git workflows, branching strategies, and version control best practices including conventional commits, rebasing, worktrees, and CI-friendly branch management.
Build PyGraphistry visualizations with bindings, encodings, layout controls, static export, and privacy-aware sharing. Use for color/size/icon/badge styling, layout tuning, map/static output, and plot link sharing workflows.
Bug investigation and fix workflow. Triggers: 'debug', 'fix bug', 'investigate issue', 'something is broken', or /debug. Hotfix track for quick fixes, thorough track for root cause analysis. Do NOT use for feature development or refactoring. Do NOT escalate to /ideate unless the fix requires architectural redesign.
Extract a validated learning from the current session, store it in the central agent learnings file, and sync the resulting Learnings section into the agent definitions used by the supported CLIs. User-only maintenance workflow for durable agent guidance.
Batch archive project items with Status set to Done using `gh project item-archive`. Also checks and guides on the configuration status of the Auto-archive built-in workflow (manual execution is basically unnecessary if enabled). Used for scenarios like "archive completed items", "organize Done items", "clean up the board", etc.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
Data file fetching and caching for geoscience applications. Download sample datasets with automatic caching, checksum verification, and multiple download sources. Use when Claude needs to: (1) Download datasets from URLs or DOIs, (2) Cache files locally with automatic verification, (3) Verify file integrity with SHA256/MD5 hashes, (4) Extract compressed archives (ZIP, TAR, GZIP), (5) Create data registries for reproducible workflows, (6) Fetch from Zenodo or other repositories.
Converts Opus-quality skills into deterministic Haiku-executable workflows via trace-driven distillation and cross-model validation. Triggers on: "distill this skill", "make this skill work on Haiku", "cross-model optimization", "optimize skill for cost". NOT for code simplification, use code-refiner.
SEO & content marketing command suite with keyword research, content audits, SERP analysis, technical SEO workflows, and structured progress tracking
CLI for moving AI-generated UI designs from Google's Stitch platform into development workflows with local preview, site generation, and agent integration.