347 件 ・ 関連度順
概要と使いどころ
Standard Operating Procedures for read-only codebase exploration, symbol search, dependency mapping, code tracing, code review, architecture analysis, technical research, source evaluation, and evidence-based reporting.
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。
Performs runtime mobile security exploration of iOS applications using Objection, a Frida-powered toolkit that enables security testers to interact with app internals without jailbreaking. Use when assessing iOS app security posture, bypassing client-side protections, dumping keychain items, inspecting filesystem storage, and evaluating runtime behavior. Activates for requests involving iOS security testing, Objection runtime analysis, Frida-based iOS assessment, or mobile runtime exploration.
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 a live Jupyter kernel for stateful, iterative Python execution via hamelnb. Load this skill when the task involves exploration, iteration, or inspecting intermediate results — data science, ML experimentation, API exploration, or building up complex code step-by-step. Uses terminal to run CLI commands against a live Jupyter kernel. No new tools required.
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。
Performs runtime mobile security exploration of iOS applications using Objection, a Frida-powered toolkit that enables security testers to interact with app internals without jailbreaking. Use when assessing iOS app security posture, bypassing client-side protections, dumping keychain items, inspecting filesystem storage, and evaluating runtime behavior. Activates for requests involving iOS security testing, Objection runtime analysis, Frida-based iOS assessment, or mobile runtime exploration.
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。
An innate exploratory drive that guarantees no graph node remains permanently invisible to an agent population. After a warm-up period (step > 3), each agent fires a coverage scan with probability |unseen_nodes| / |all_nodes|. When triggered, the agent teleports directly to the globally unseen node with the highest belief uncertainty, works it, and returns control to the normal action-selection loop. Probability is self-annealing: it starts near 1.0 when almost everything is unseen and decays toward 0.0 as coverage saturates, requiring no manual schedule. The mechanism is "innate" (hard-coded into the agent step loop) as distinct from the "adaptive" EFE path, which requires local neighbors and learned precision weights. Together they form a two-layer exploration architecture: adaptive for locally-guided foraging, innate for topological completeness.
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。
候補の探索や比較を繰り返し、試行の根拠と判断を追記型の台帳に残すスキル。前回との整合性や再検証の結果を確認し、実取引や本番操作へ進む条件を明確にします。
発表用のメモやPowerPointから、ブラウザで動くHTMLスライドを作ります。見本でデザインを選び、画面に収まるレイアウトとアニメーションを整えます。
エミュレーター上のPokemonをAIに操作させ、移動や会話、バトルを進めるスキル。画面とメモリ内の状態を確認しながら遊び、ブラウザーでの観戦や保存・再開も扱います。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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。
A hand-drawn wireframe exploration — graph-paper background, marker / pencil tone, multiple tab labels for variants, sticky-note annotations, scribbled chart placeholders, hatched fills. Reads like a designer's whiteboard before any pixels are committed. Use when the brief asks for "wireframe", "sketch wireframe", "hand-drawn", "lo-fi", "whiteboard", "草稿", or "手绘原型".
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。
Real-time and streaming AI image generation via fal.ai. Suited for moodboard exploration, draft variations, and rapid creative iteration.
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。
Transform rough ideas into fully-formed designs through structured questioning and alternative exploration. Useful early in concept work.
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 this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.
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。
ACTIVATES ONLY on an explicit user request for the ulw-plan workflow: the user themselves saying ulw-plan, ulw plan, /skill:ulw-plan, or asking in their own words for a work plan before coding. NEVER self-activates: a bare ulw/ultrawork run, an agent-side routing decision, or reading this file is not a request, and the plan-gated reviewers (metis/momus) stay locked without a user request plus a written .omo/plans plan file. Explore-first planning consultant (Prometheus) that grounds in the codebase, asks only the forks exploration cannot resolve - or researches them to best practice when the intent is fuzzy - waits for explicit approval, then writes ONE decision-complete work plan a worker executes with zero further interview. Triggers: ulw-plan, ulw plan, plan this, make a plan, plan before coding, interview me, break this down, start planning, plan mode.
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。
Queries 20+ bioinformatics resources through CLI/Python. Supports quick lookups of gene info, BLAST/BLAT, viral sequence downloads, PDB/mmCIF structures, G2P residue annotations, enrichment analysis, OpenTargets, COSMIC, CELLxGENE, and 8cube mouse specificity/expression data. Best for interactive exploration and simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
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。
Analyzes, manipulates, compares, annotates, and visualizes phylogenetic or other hierarchical trees with ETE 4. Supports Newick/Nexus tree I/O, topology edits and pattern matching, Robinson-Foulds comparisons, gene-tree evolutionary events and reconciliation, NCBI/GTDB taxonomy, SmartView exploration, and publication rendering. Applies to existing trees after alignment and phylogenetic inference, rather than inferring trees from raw sequences.
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。
Website exploration for testing using Playwright MCP
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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。
Create stunning, animation-rich HTML presentations from scratch or by converting PowerPoint files. Use when the user wants to build a presentation, convert a PPT/PPTX to web, or create slides for a talk/pitch. Helps non-designers discover their aesthetic through visual exploration rather than abstract choices.
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。
Get structured design feedback on usability, hierarchy, and consistency. Trigger with "review this design", "critique this mockup", "what do you think of this screen?", or when sharing a Figma link or screenshot for feedback at any stage from exploration to final polish.
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 the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.
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。
Create a structured customer interview script with JTBD probing questions, warm-up, core exploration, and wrap-up sections. Follows The Mom Test principles — no leading questions, no pitching, focus on past behavior. Use when preparing for user interviews, creating interview guides, or planning discovery research.
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。
Guided concept ideation using professional studio techniques, player psychology, creative exploration.
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。
Evolutionary explanation-discovery engine for hard-to-vary causal theories of unknown phenomena. USE WHEN develop a new theory, explain a mystery, solve an explanatory gap, discover a mechanism, consciousness, origin, or scientific breakthrough. Also use for multi-cycle creative exploration. NOT FOR a single-pass divergent brainstorm (use BeCreative) or delivery validation alone (use Evals).
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。