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Found 9,575 Skills
Use this skill for ANY multi-pane or multi-agent terminal orchestration in cmux. Required when the user wants to: run things in parallel in separate terminal panes, split the terminal, spawn a sub-agent (Claude Code, Codex) in another pane, fan out tasks across splits, send keystrokes or text to another pane (including ctrl-c), read terminal output from another pane, update sidebar status or progress bar, open a URL in cmux's built-in browser pane, or display markdown preview alongside the terminal. The cmux CLI is the ONLY way to do these things — Bash cannot split panes or spawn agents. Trigger phrases: 'in parallel', 'split pane', 'spawn agent', 'fan out', 'new pane', 'browser pane', 'sidebar', 'send to pane', 'read from pane', 'show the plan', 'ctrl-c to', '分屏', '并行', '开个 pane'. NOT for: single command execution, basic bash operations, or questions about tmux.
Monitor background processes from Claude Code using sentinel files, heartbeat liveness, and subagent polling. Best practices and anti-patterns for autonomous loops that need to kick off work, detect completion/failure/hang/timeout, and resume the main context without wasting tokens. TRIGGERS - monitor background process, sentinel file, heartbeat monitoring, process supervision, agentic loop monitor, background task health, detect hung process, poll for completion, watchdog pattern, process liveness, monitor long-running task, agent poll loop, circuit breaker pattern.
Transforms Claude from a 'Graphic Designer' into a 'Design Thinker'. Trigger this skill whenever the user asks for design, redesign, creation of graphics, layouts, UI/UX, or any creative asset. Use this skill even if the user provides a direct request like 'make a flyer' or 'redesign my site'. The goal is to ask critical questions and solve the underlying problem before touching any visual elements.
Use when preparing or verifying a host for Moshi remote coding. Trigger this for SSH or preferably Mosh readiness, non-interactive shell PATH issues, tmux defaults, creating a tmux project session rooted at a chosen directory, installing Moshi agent hooks for Claude Code or Codex CLI, or offering the optional `moshi DIR` shell helper.
Ingest any raw text data, conversation logs, chat exports, or unstructured documents into the Obsidian wiki. Use this skill when the user wants to process data that isn't standard documents or Claude history — things like ChatGPT exports, Slack threads, Discord logs, meeting transcripts, journal entries, CSV data, browser bookmarks, email archives, or any raw text dump. Triggers on "ingest this data", "process these logs", "add this export to the wiki", "import my chat history from X". This is the catch-all for any text source not covered by the more specific ingest skills.
Use this skill when the user asks to "evaluate MCP tools", "test tool selection", "improve tool descriptions", "check MCP schema quality", "eval my MCP server", or wants to measure whether Claude uses their MCP tools correctly. Tests tool selection accuracy, analyzes schema quality, and iteratively optimizes descriptions. Companion to build-mcp-server.
A method for iteratively improving text instructions for agents (skills / slash commands / task prompts / CLAUDE.md sections / code generation prompts) by having unbiased executors run them, then evaluating from both perspectives (executor self-report + instruction-side metrics). Repeat until improvement plateaus. Use immediately after creating or significantly revising a prompt or skill, or when you suspect the reason an agent isn't behaving as expected is due to ambiguity in the instructions.
Query AI coding agent usage, costs, and token consumption. Supports Claude Code, Codex CLI, OpenClaw, and OpenCode. Ask about spending, token usage, model costs, session history, API call counts. Actions: check usage, show cost, compare models, list sessions, analyze spending, token breakdown. Time ranges: today, this week, this month, this year, last N days, custom dates.
Read and parse DLIS (Digital Log Interchange Standard) and LIS (Log Information Standard) well log files. Use when Claude needs to: (1) Read/parse DLIS or LIS files, (2) Extract well log curves as numpy arrays, (3) Access file metadata and origin information, (4) Handle multi-frame or multi-file DLIS, (5) Convert DLIS to LAS or DataFrame, (6) Work with RP66 format well logs, (7) Process array or image log data.
Read, write, and manipulate LAS (Log ASCII Standard) well log files for borehole geophysical and petrophysical data. Use when Claude needs to: (1) Read/parse LAS 1.2 or 2.0 files, (2) Extract well headers or curve data, (3) Convert LAS to DataFrame/CSV/Excel, (4) Create new LAS files from arrays, (5) Modify existing LAS files, (6) Handle problematic or malformed LAS files, (7) Batch process multiple well files.
Use when creating a plan using Plan model and enhancing structured design plans in Cursor Plan mode for Java implementations. Use when the user wants to create a plan, design an implementation, structure a development plan, or use plan mode for outside-in TDD, feature implementation, or refactoring work. This should trigger for requests such as Create a plan with Cursor Plan mode; Write a plan with Claude Plan mode; Design an implementation plan; Structure a development plan. Part of cursor-rules-java project
Fast, accurate code search for AI agents using ~98% fewer tokens than grep+read. Indexes any local or remote repository in under a second (~250ms on CPU, no GPU or API key needed). Supports natural-language and symbol queries, semantic similar-code discovery, and MCP server integration for Claude Code, Codex, Cursor, and OpenCode. Python library available for programmatic use. Triggers on: semble, code search, semantic code search, semble search, token-efficient search, find code, code search mcp, agent code search, semble find-related, semble savings.