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概要と使いどころ
Map a codebase into feature-grouped flowcharts, identify duplicated concerns across features, and propose a unified architecture. Use when asked to "find the ideal path," unify duplicated systems, or audit architecture before a refactor. Emits a proposed unified flowchart plus per-system /make-plan prompts.
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。
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
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。
Automate Dropcontact tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Dropbox Sign tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Better Proposals tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Anthropic Admin tasks via Rube MCP (Composio): API keys, usage, workspaces, and organization management. Always search tools first for current schemas.
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。
Automate Anthropic Admin tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
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 a goal as a project: you coordinate. Use for "agents <task>", "take this to done", "work on this in parallel", "what are my threads doing", "pick up <slug>", "resume <slug>", "keep going until it is merged". Under `/agents` you do the work yourself unless it needs several lanes or a long wait — you judge; the plan line says why. No target you could verify (a file, API, number or measure) → the grill interview first, not threads. Read this skill before proposing anything for `/agents`: without it a proposal is in-session subagents.
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。
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.
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。
Overlay doctrine for the embedded-captions workflow — the caption MODEL (drop / rail / embed) and the rule that captions are an OVERLAY composited on top of the film, never a reserved bottom band you shift content up to avoid. Load when adding captions/subtitles to a talking-head or launch video, when deciding whether a phrase should be dropped, ride the verbatim rail, or be promoted to a scarce embedded climax, when laying out a composition that will carry captions (do NOT reserve a keep-out band), or when centering a composition on the true frame center under captions. Quotes the rail+embed model from embedded-captions and constraint
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。
Assess the impact of a significant change during sprint execution across the PRD, epics, architecture, and UX documents, and produce a sprint change proposal. Use when the user says "correct course" or "propose sprint change"
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。
Audit an Anthropic Cookbook notebook based on a rubric. Use whenever a notebook review or audit is requested.
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。
Supports research proposal preparation and review for NSF, NIH, DOE, DARPA, and Taiwan NSTC, including opportunity-specific requirements, aims, review criteria, budgets, broader impacts, forms, and resubmissions. Use for investigator-authored grant development, compliance matrices, and proposal critiques.
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。
Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.
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。
CommunityToolkit.Mvvm (the MVVM Toolkit) core: source generators ([ObservableProperty], [RelayCommand], [NotifyPropertyChangedFor], [NotifyCanExecuteChangedFor], [NotifyDataErrorInfo]), base classes (ObservableObject / ObservableValidator / ObservableRecipient), commands (RelayCommand / AsyncRelayCommand), and validation. Companion skills: mvvm-toolkit-messenger for pub/sub, mvvm-toolkit-di for Microsoft.Extensions.DependencyInjection wiring. Works across WPF, WinUI 3, MAUI, Uno, and Avalonia.
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。
Migrates Oracle PL/SQL stored procedures to PostgreSQL PL/pgSQL. Translates Oracle-specific syntax, preserves method signatures and type-anchored parameters, leverages orafce where appropriate, and applies explicit collation mapping (`COLLATE "C"` only when appropriate, locale collations when required). Use when converting Oracle stored procedures or functions to PostgreSQL equivalents during a database migration.
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。
Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations or working with already-completed data packs.
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 DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.
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。
Iterate on the Cardputer-Adv MicroPython app bundle (Claude Buddy, Snake, Hello) after the device is already provisioned via m5-onboard. Use when the user wants to add a new app, push a single changed .py without re-flashing, watch device serial logs, or run a one-shot REPL command. Trigger on "add an app", "push to the cardputer", "tail the device", "run on the device", or follow-up work after /maker-setup.
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。
End-to-end onboarding for a freshly-plugged-in M5Stack ESP32 device (Cardputer, Cardputer-Adv, Core, CoreS3, Stick) — detect on USB, flash UIFlow 2.0 firmware, and install the Claude Buddy MicroPython app bundle. Use whenever the user plugs in or wants to flash/provision/reset an M5Stack or ESP32 board, or says "m5-onboard go".
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。
Detects typosquatting attacks in npm and PyPI package registries by analyzing package name similarity using Levenshtein distance and other string metrics, examining publish date heuristics to identify recently created packages mimicking established ones, and flagging download count anomalies where suspicious packages have disproportionately low usage compared to their legitimate targets. The analyst queries the PyPI JSON API and npm registry API to gather package metadata for automated comparison. Activates for requests involving package typosquatting detection, dependency confusion analysis, malicious package identification, or software supply chain threat hunting in package registries.
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。
Detect command-and-control (C2) traffic tunneled over DNS from tools like Iodine, dnscat2, dns2tcp, and Cobalt Strike DNS beacon, using Shannon entropy analysis of query subdomains, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signatures. Use when investigating suspected DNS tunneling, classifying DGA domains, detecting DNS beaconing, or building DNS anomaly rules for a SOC/SIEM.
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。
Systematically deobfuscates multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure. Use during incident response or malware analysis when a PowerShell script is obfuscated with encoding, string manipulation, or invocation tricks and you need to recover the underlying commands, dropped payloads, or C2 endpoints.
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。