Loading...
Loading...
Found 33 Skills
Delegate tasks to parallel worktree agents using worktrunk (wt). Use when asked to "spawn agents", "run in parallel", "delegate to worktrees", or split work across multiple Claude/OpenCode sessions.
Word Flow: Conduct in-depth word analysis and generate infographic cards in one go. It accepts one or more English words, runs ljg-word (which generates in-depth semantic analysis) and then ljg-card -i (which generates infographic PNGs). Use this when the user says '词卡', 'word card', 'word flow', or provides English words and wants both analysis and visual cards.
Expert in modern, cross-platform PowerShell Core. Specializes in Linux/macOS automation, parallel processing, REST API integration, and modern scripting patterns. Use for cross-platform automation and modern PowerShell features. Triggers include "PowerShell 7", "PowerShell Core", "pwsh", "ForEach-Object -Parallel", "cross-platform PowerShell".
Invoke parallel document-specialist agents for external web searches and documentation lookup
Lead qualification engine with conversational intake. Asks structured questions to understand your qualification criteria, generates a reusable qualification prompt, then batch-enriches leads via Apify LinkedIn scraping and scores them with parallel processing. Outputs qualified/disqualified verdicts with confidence scores and reasoning to Google Sheets (via Rube) or CSV. Supports calibration mode for prompt refinement.
Paper Workflow: Read papers and create reading cards in one go. Accepts one or more arXiv links, paper URLs, PDFs, or paper titles. For each paper, it runs ljg-paper (generates org-format analysis) followed by ljg-card -l (generates long-form reading card PNG). Trigger this workflow when the user says '论文流', 'paper flow', '读论文并做卡片', '论文卡片', or provides multiple papers and requires both analysis and reading cards.
Resolve PR review feedback by evaluating validity and fixing issues in parallel. Use when addressing PR review comments, resolving review threads, or fixing code review feedback.
Master skill for parallel subagent-driven execution with automatic fallback to single-agent sequential mode. Use when implementing plans with multiple independent sub-phases (SP1, SP2...) to dispatch parallel subagents, or when requiring code review between implementation and testing.
Resolve all PR comments using parallel processing. Use when addressing PR review feedback, resolving review threads, or batch-fixing PR comments.
Illustre automatiquement le journal d'une aventure BFRPG en générant des images pour les moments clés (combats, explorations, découvertes). Utilise la génération parallèle pour une performance optimale.
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
Reviewing one Task's diff on two axes in parallel sub-agents — Spec (does the code do what the spec and the ticket asked?) and Standards (does it follow the repo's conventions, the test rules and the smell baseline?) — and reporting them side by side. The reviewer step of /archie-implement.