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Found 2,695 Skills
Use when creating, listing, inspecting, or deleting Tigris Storage buckets
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore. Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. NOT for custom model training, Rekognition, or Comprehend.
Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.
Query papers using RAG (PaperQA2 or LEANN). Use when user needs synthesized answers from papers, asks "what does paper X say about Y", or needs cited responses.
Write comprehensive unit tests with high coverage using testing frameworks like Jest, pytest, JUnit, or RSpec. Use when writing tests for functions, classes, components, or establishing testing standards.
OpenDuck — open-source distributed DuckDB with differential storage, hybrid dual execution, and transparent remote database attach
Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3 Storage Lens tables via Athena SQL. Applies when counting objects, finding recent uploads or deletions, identifying who wrote to a prefix, breaking down storage classes, finding objects by tag, searching annotation content, analyzing storage lens metrics, or enabling S3 Metadata tracking. Prefers system tables over raw S3 APIs (list-objects-v2, head-object) at scale. Trigger phrases: bucket activity, object count, who uploaded, track deletions, storage class breakdown, find by tag, search annotations, storage lens metrics, audit bucket changes.
Use when writing unit/integration tests for Vite projects - provides Vitest configuration, test APIs, mocking patterns, and coverage setup
Analyzes changed files and improves unit test coverage using project-specific testing conventions from .trellis/spec/ unit-test specs. Determines test scope (unit vs integration vs regression), adds or updates tests following existing patterns, and runs validation. Use when code changes need test coverage, after implementing a feature, after fixing a bug, or when test gaps are identified.
Validate skill files for structural compliance and behavioral correctness. Three modes: static (linter), spec (behavioral), audit (coverage report).
Analyze disk space usage, filesystem mounts, and storage allocation on Linux systems. Identifies large files and directories, checks partition usage, and reports inode consumption. Use when the user asks about disk full errors, free space, storage usage, du/df output, finding large files, or checking which directories consume the most space.
Split text into contextual chunks for RAG/embedding pipelines. Document segmentation and section extraction using window, tfidf, punctuation, or hybrid strategies chosen by intent.