spl-to-apl
Translates Splunk SPL queries to Axiom APL. Provides command mappings, function equivalents, and syntax transformations. Use when migrating from Splunk, converting SPL queries, or learning APL equivalents of SP...
发现 devops llm ai 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。
Translates Splunk SPL queries to Axiom APL. Provides command mappings, function equivalents, and syntax transformations. Use when migrating from Splunk, converting SPL queries, or learning APL equivalents of SP...
スキルを作成・更新・プロンプト改善するためのメタスキル。 **collaborative**モードでユーザーと対話しながら共創し、 抽象的なアイデアから具体的な実装まで柔軟に対応する。 **orchestrate**モードでタスクの実行エンジン...
Testing strategy orchestrator. Use when discussing test types, test order, or choosing how to test something. Auto-apply for general testing questions.
Compare Nim and Python scripted agent implementations and align behavior. Use when asked to port or ensure parity between Nim and Python.
Geminiに意見を聞く、セカンドオピニオンを求める。コードレビュー、設計相談、アーキテクチャの相談、別のAIの意見が欲しいときに使用。「Geminiに聞いて」「別の意見」「セカンドオピニオン」などのリクエストで起動。
Create a plan to modularize the AI include chain.
Provides expert guidance for writing and optimizing prompts for large language models. Use this skill when: (1) user mentions "prompt", "prompting", or "prompt engineering", (2) user requests to write, create,...
Locate the latest checkpoint for a run id and provide a follow-up play/eval command. Use when asked to find a checkpoint.
Session memory management for pseudo-code prompting - preserves transformation context, learned patterns, and user preferences across sessions
This skill should be used when the user asks to "segment an image", "identify objects", "extract objects", "generate masks", "find objects in image", or needs AI-powered image segmentation.
Minimal implementation of Recursive Language Models (RLM) using Gemini 2.0 Flash and a local Python REPL. Enables processing of massive contexts via the Gemini CLI.
Capture current session state and generate a handoff prompt for seamless continuation in a new session. Use when context window is filling up, before ending a long session, or when explicitly requested.
A simple example skill demonstrating basic Claude Code skill structure
Initialize the ConKeeper memory system for the current project. Creates the directory structure and starter files for persistent AI context.
汇总所有 Claude Code Skills 的目录与使用指南,支持检查 GitHub 更新。触发词:/skills、技能目录、skill列表、有哪些技能、检查更新
Initialize the ConKeeper memory system for the current project. Creates the directory structure and starter files for persistent AI context.
Synchronize current session state to ConKeeper memory files. Updates context, progress, and decisions based on the conversation.
Initialize the ConKeeper memory system for the current project. Creates the directory structure and starter files for persistent AI context.
This skill should be used when creating custom subagents for Claude Code, configuring specialized AI assistants, or when the user asks about agent creation, agent configuration, or delegating tasks to subagents...
Skills for orchestrating tasks across multiple AI providers and execution environments. Parent skill category containing native-invoke and related delegation patterns.
Create specialized Claude Code agents on-the-fly. Guides through agent definition file creation with proper frontmatter, effective prompts, and tool scoping. USE WHEN user says 'create agent', 'new subagent', '...
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalize...
Utility assistant skill with dry wit and practical capabilities. Triggers when user selects Assistant character or needs help with file management, research, calculations, web searches, task execution, or gen...
Claude Code hooks configuration specialist. Use when creating hooks for tool validation, logging, notifications, or custom automation in Claude Code.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。