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Found 219 Skills
This skill should be used for multi-session autonomous agent work requiring progress checkpointing, failure recovery, and task dependency management. Triggers on '/harness' command, or when a task involves many subtasks needing progress persistence, sleep/resume cycles across context windows, recovery from mid-task failures with partial state, or distributed work across multiple agent sessions. Synthesized from Anthropic and OpenAI engineering practices for long-running agents.
Systematically remove malware, backdoors, and attacker persistence mechanisms from infected systems while ensuring complete eradication and preventing re-infection.
Common utilities and features for Syncfusion React components. Use this skill when the user needs to implement animations, drag-and-drop, state persistence, RTL support, localization, globalization, security, templates, and advanced features for Syncfusion React components.
Use when you need data access with Quarkus Hibernate ORM Panache — including PanacheEntity / PanacheEntityBase, PanacheRepository, named and HQL queries, DTO projections (project(Class)), pagination (Page.of()), N+1 avoidance (JOIN FETCH), optimistic locking (@Version / OptimisticLockException), @NamedQuery for validated reusable queries, transactions, @TestTransaction for test isolation, and immutable-friendly patterns. This is the Quarkus analogue to Spring Data for relational persistence. Part of the skills-for-java project
Delegate coding, review, diagnosis, planning, structured output, and native browser research tasks to independent Codex sessions via Codex CLI. Use cases include creating new tasks with `codex exec`, resuming multi-turn sessions with `codex exec resume`, performing read-only reviews with `codex exec review`, as well as scenarios requiring `--json` event streams, `-o` final message persistence, image input, or Computer Use browser operations.
Checkpoint and resume workflow state for context persistence across sessions. Use when the user says 'save progress', 'checkpoint', 'I need to stop', or runs /checkpoint or /rehydrate. Saves current workflow phase, task progress, and artifacts for later resumption. Do NOT use for workflow initialization (handled by ideate/debug/refactor commands).
Implements Syncfusion ASP.NET Core Grid component for feature-rich data tables and grids. Use this when working with data display, sorting, filtering, grouping, aggregates, editing, or exporting. This skill covers grid configuration, CRUD operations, virtual scrolling or infinite scrolling, hierarchy grids, state persistence, and advanced data management features for data-intensive applications.
SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage
Complete guide for OpenAI's Assistants API v2: stateful conversational AI with built-in tools (Code Interpreter, File Search, Function Calling), vector stores for RAG (up to 10,000 files), thread/run lifecycle management, and streaming patterns. Both Node.js SDK and fetch approaches. ⚠️ DEPRECATION NOTICE: OpenAI plans to sunset Assistants API in H1 2026 in favor of Responses API. This skill remains valuable for existing apps and migration planning. Use when: building stateful chatbots with OpenAI, implementing RAG with vector stores, executing Python code with Code Interpreter, using file search for document Q&A, managing conversation threads, streaming assistant responses, or encountering errors like "thread already has active run", vector store indexing delays, run polling timeouts, or file upload issues. Keywords: openai assistants, assistants api, openai threads, openai runs, code interpreter assistant, file search openai, vector store openai, openai rag, assistant streaming, thread persistence, stateful chatbot, thread already has active run, run status polling, vector store error
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.
Thread-safe data persistence in Swift using actors — in-memory cache with file-backed storage, eliminating data races by design.
Adaptive sprint workflow: deep analysis, evolving roadmap, one-at-a-time sprints, formal debt tracking, and re-entry prompts for context persistence. Trigger: When the user wants to analyze a project, create a roadmap, generate/execute sprints iteratively, or check project status and technical debt.