2,318 件 ・ 関連度順
概要と使いどころ
Compares build vs buy alternatives with risk-adjusted returns, time-to-value, and execution probability assessment. Use when evaluating growth strategies, comparing M&A vs organic investment, or analyzing make-vs-buy decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Structures exchange offers, consent solicitations, and amend-and-extend transactions as Chapter 11 alternatives. Use when managing out-of-court workouts, designing exchange offers, or structuring pre-negotiated deals.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluates 363 sale processes with stalking horse protections, bid procedures, and credit bidding mechanics. Use when analyzing 363 sales, structuring stalking horse bids, or evaluating asset sale alternatives.
日本語の概要は準備中です。原文の説明を表示しています。
Connect a site's existing WebMCP tools to AgentLane without rebuilding them. Use when a codebase already registers document.modelContext tools — natively or through any SDK — and the developer wants them visible in AgentLane, migrated onto @nekuda/webmcp-sdk with durable stable keys and verified to behave exactly as before.
日本語の概要は準備中です。原文の説明を表示しています。
Initiate a session handoff to transfer context and pending actions to a new terminal session. Executing this skill safely drains tasks and launches a new cross-platform window natively.
日本語の概要は準備中です。原文の説明を表示しています。
Compiler-level code intelligence via native LSP — definitions, references, types, call hierarchies, and diagnostics.
日本語の概要は準備中です。原文の説明を表示しています。
Decision framework for agents to determine WHEN and WHETHER to use Claude Code's native cron scheduler (CronCreate/CronList/CronDelete) vs OS cron, GitHub Actions, or simple Task() delegation.
日本語の概要は準備中です。原文の説明を表示しています。
Expert Electron desktop application development — main/renderer process architecture, IPC communication, native OS APIs (menus, tray, notifications, dialogs), auto-updates, code signing, packaging with electron-builder/forge, security hardening (contextIsolation, sandbox), and performance optimization. Use for building cross-platform desktop apps.
日本語の概要は準備中です。原文の説明を表示しています。
Socratic design refinement before implementation — challenges assumptions, surfaces alternatives, identifies risks before code is written
日本語の概要は準備中です。原文の説明を表示しています。
Try 2-3 different approaches before implementing - don't settle for first design you think of
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used to search, inspect, list, and recover local Codex sessions through Codex's native App Server APIs. Trigger for requests such as find a prior Codex conversation, search Codex transcript text, list recent Codex work, locate matches inside a session, or produce a safe Codex resume command. Do not use for Claude Code sessions, project source-code search, or web search.
日本語の概要は準備中です。原文の説明を表示しています。
Discover, message, and coordinate AI coding agents (Claude Code, Codex CLI) running on the same machine via a shared Unix socket broker backed by SQLite. The broker wakes recipients natively (Claude inbox socket, codex queue) and turn-boundary hooks catch missed wakes. Supports cross-session task delegation, peer summaries, and session lifecycle management. Triggers on 'peer agents', 'cross-session communication', 'message Codex', 'inter-agent messaging', 'coordinate agents'.
日本語の概要は準備中です。原文の説明を表示しています。
Desktop GUI automation via OpenInterpreter — mouse, keyboard, screenshot, and OCR control for native macOS/Linux applications. Three modes: Library (Claude reasons, OI executes), OS subprocess (full autonomous computer use), and Local agent (Ollama, offline). This skill should be used when interacting with desktop apps that have no CLI or API, automating GUI workflows, reading screen content via OCR, or controlling mouse/keyboard.
日本語の概要は準備中です。原文の説明を表示しています。
Inverted orchestration—Codex CLI acts as CTO (planning and reviewing), Claude Code executes with native tools. Use when a task benefits from external architectural oversight before and after implementation.
日本語の概要は準備中です。原文の説明を表示しています。
Research UI component patterns across the component.gallery corpus — 60 canonical component types, ~95 production design systems, 2,600+ examples — plus an AI-era overlay (prompt inputs, tool-call cards, streaming status, citations) and composite patterns (command palette, app shell, agent console). Compare implementations, find alternative component names, ground frontend decisions in real-world precedent. Pairs with minoan-frontend-design for research-then-build workflows. Triggers on component patterns, how do others implement X, design system research, component comparison, AI chat components, agent UI patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Polish screen recordings with Recordly (open-source Screen Studio alternative) — auto-zooms, cursor animations, webcam overlays, styled backgrounds, timeline editing. Also includes Slant: browser-based 3D perspective renderer with 12 animation presets and MP4/GIF export. Triggers on screen recording, demo video, Recordly, screen capture polish, product walkthrough, 3D perspective, Slant.
日本語の概要は準備中です。原文の説明を表示しています。
Git-native issue tracking (beads), coding guidelines, knowledge injection, and spec-driven planning for AI agents. Drop-in replacement for bd/Beads with simpler architecture. Use for: tracking issues/beads with dependencies, creating bugs/features/tasks, planning specs, implementing features from specs, code reviews, committing code, creating PRs, loading coding guidelines (TypeScript, Python, TDD, golden testing, Convex, monorepo patterns), code cleanup, research briefs, architecture docs, agent handoffs, and checking out third-party library source code. Invoke when user mentions: tbd, beads, bd, shortcuts, issues, bugs, tasks, features, epics, todo, tracking, specs, planning, implementation, validation, guidelines, templates, commit, PR, pull request, code review, testing, TDD, test-driven, golden testing, snapshot testing, TypeScript, Python, Convex, monorepo, cleanup, dead code, refactor, handoff, research, architecture, labels, search, checkout library, source code review, or any workflow shortcut.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a product idea needs pressure-testing against alternatives, category, urgency, and distribution.
日本語の概要は準備中です。原文の説明を表示しています。
Design, build, refactor, or review terminal interfaces—full-screen TUIs, interactive prompts, and command-line tools. Use for terminal-app layout and UX, CLI behavior, ncurses-style tools, dashboards, REPLs, fzf-like pickers, and libraries such as Bubble Tea, Ratatui, Textual, or Ink, including requests that name a known TUI such as lazygit, k9s, btop, helix, or yazi instead of saying “TUI.” Do not use for browser or web UI, native GUI, editor or font configuration, or backend and shell work that has no terminal interface.
日本語の概要は準備中です。原文の説明を表示しています。
Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
日本語の概要は準備中です。原文の説明を表示しています。
Compute relative and absolute binding free energies with the Open Free Energy toolkit — the rigorous alchemical alternative to docking scores when a congeneric series needs reliable potency ranking. Use this skill to plan a perturbation network over a ligand set, choose atom mappings, run hybrid-topology or separated-topology protocols, and analyse the result — per-edge ΔΔG with uncertainty, cycle-closure error, and mean unsigned error against measured affinities. Also trigger on OpenFE, alchemical transformation, thermodynamic cycle, RBFE, ABFE, SepTop, lambda window, MBAR, cycle closure, or perturbation map.
日本語の概要は準備中です。原文の説明を表示しています。
Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein and protein-ligand systems with PDBFixer, choose force fields and water models (AMBER14, CHARMM36m, ff19SB, GAFF2, TIP3P), solvate and add ions, run energy minimization, NVT/NPT equilibration and production MD on GPU, then analyze trajectories for RMSD, RMSF, radius of gyration, hydrogen bonds, native contacts, PCA and free energy surfaces. Use this skill for protein stability under mutation, ligand binding-mode and residence-time questions, conformational sampling, membrane proteins, and disordered ensembles. Also trigger on OpenMM, MDAnalysis, mdtraj, Simulation.step, LangevinMiddleIntegrator, PDBFixer, DCD or XTC trajectory, RMSD analysis, or production MD.
日本語の概要は準備中です。原文の説明を表示しています。
Cofold protein-ligand, protein-protein, and nucleic-acid complexes with Boltz-2, and predict binding affinity with its trained affinity head. Use this skill to build Boltz input YAML, run structure prediction with MSAs, pocket constraints, templates, and modified residues, screen compound libraries by cofolding, and interpret confidence scores (pLDDT, pTM, ipTM, PDE) and affinity output (binder probability and log10 IC50). Also trigger on Boltz, Boltz-1, Boltz-2, cofolding, boltz predict, affinity_pred_value, affinity_probability_binary, ipTM, or open-weights AlphaFold3 alternatives.
日本語の概要は準備中です。原文の説明を表示しています。
Pythonic wrapper around RDKit with a simplified interface and sensible defaults. Preferred for standard drug discovery work — SMILES/SELFIES/InChI conversion, molecule standardization and sanitization, descriptors, ECFP and other fingerprints, Tanimoto distance matrices, Butina clustering and diverse subset picking, Bemis-Murcko scaffolds and scaffold splits, BRICS/RECAP fragmentation, 3D conformer generation, SDF/CSV/Excel and cloud I/O, and parallel processing via n_jobs. Returns native rdkit.Chem.Mol objects, so it composes with RDKit throughout. Also trigger on datamol, `import datamol as dm`, dm.to_mol, dm.standardize_mol, dm.cluster_mols, or dm.pick_diverse. For advanced control or custom parameters, use the rdkit skill directly.
日本語の概要は準備中です。原文の説明を表示しています。