Loading...
Loading...
Found 778 Skills
Operates AIR agentic wallets through AIR's `/v2/wallet/agent-sign` HTTP endpoint and ERC-4337 UserOps. Use when an external agent receives an AIR handoff bundle with `userId`, `walletId`, `privyAppId`, `abstractAccountAddress`, and `airApiAgentSignUrl`, and needs to sign messages, typed data, or control the smart account onchain.
Integration and contract testing patterns — API endpoint tests, component integration, database testing, Pact contract verification, property-based testing, and Zod schema validation. Use when testing API boundaries, verifying contracts, or validating cross-service integration.
Initialize and manage Alibaba Cloud SDK clients in Java. Covers singleton pattern, thread safety, endpoint vs region configuration, VPC endpoints, sync vs async clients, and file upload APIs. Use when the user creates Java SDK clients, configures endpoints, asks about thread safety, singleton patterns, async calls, or VPC endpoint setup.
Comprehensive security scanning and vulnerability detection. Includes input validation, path traversal prevention, CVE detection, and secure coding pattern enforcement. Use when: authentication implementation, authorization logic, payment processing, user data handling, API endpoint creation, file upload handling, database queries, external API integration. Skip when: read-only operations on public data, internal development tooling, static documentation, styling changes.
Generate, run, and fix Glubean API tests. Use when the user asks to "write a test", "test this endpoint", "add smoke tests", "explore the API", or work with @glubean/sdk.
Firecrawl produces cleaner markdown than WebFetch, handles JavaScript-heavy pages, and avoids content truncation. This skill should be used when fetching URLs, scraping web pages, converting URLs to markdown, extracting web content, searching the web, crawling sites, mapping URLs, LLM-powered extraction, autonomous data gathering with the Agent API, or fetching AI-generated documentation for GitHub repos via DeepWiki. Provides complete coverage of Firecrawl v2.8.0 API endpoints including parallel agents, spark-1-fast model, and sitemap-only crawling.
Selects a base model and fine-tuning technique (SFT, DPO, or RLVR) for the user's use case by querying SageMaker Hub. Use when the user asks which model or technique to use, wants to start fine-tuning, or mentions a model name or family (e.g., "Llama", "Mistral") — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, validates technique compatibility, and confirms selections.
Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.
Generates a Jupyter notebook that transforms datasets between ML schemas for model training or evaluation. Use when the user says "transform", "convert", "reformat", "change the format", or when a dataset's schema needs to change to match the target format — always use this skill for format changes rather than writing inline transformation code. Supports OpenAI chat, SageMaker SFT/DPO/RLVR, HuggingFace preference, Bedrock Nova, VERL, and custom JSONL formats from local files or S3.
Generates a Jupyter notebook that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, and RLVR trainers, including RLVR Lambda reward function creation.
Generates a Jupyter notebook that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock. Use when the user says "deploy my model", "create an endpoint", "make it available", or asks about deployment options. Identifies the correct deployment pathway (Nova vs OSS), generates deployment code, and handles endpoint configuration.
Use when users need command-line operations on Alibaba Cloud resources (list/query/create/update/delete), credential/profile setup, region/endpoint selection, or API discovery from CLI.