「sic」の検索結果

A hybrid memory system that provides persistent, searchable knowledge management for AI 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。

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Active Directory, Kerberos, LDAP, OAuth, enterprise messaging, Windows host forensics, credential material, and lateral-movement challenges. Use when the user asks to trace tickets or tokens, inspect mailbox rules, analyze Windows host evidence, understand an AD trust path, or explain a lateral-movement chain across sandbox-linked nodes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.

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 for authorized RF/SDR security research including signal identification, replay feasibility study in shielded labs, and wireless protocol analysis outside classic Wi-Fi.

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。

Experimental (preview) Pester skill for migrating classic Should -Be (v5) assertion syntax to the new Should-* (v6) assertions (note the hyphen, no space), e.g. `Should -Be` -> `Should-Be`, `Should -Not -Be` -> `Should-NotBe`. Tracks Pester 6, which is still a release candidate, so this guidance may change; verified against Pester 6.0.0-rc2. Use when converting Pester v5 assertions to Pester v6 Should-* operators, modernizing a Pester test suite, or when a user asks to migrate, convert, or rewrite `Should -...` calls in .Tests.ps1 / PowerShell files.

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 skill for building web-based game engines and games using HTML5, Canvas, WebGL, and JavaScript. Use when asked to create games, build game engines, implement game physics, handle collision detection, set up game loops, manage sprites, add game controls, or work with 2D/3D rendering. Covers techniques for platformers, breakout-style games, maze games, tilemaps, audio, multiplayer via WebRTC, and publishing games.

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 skill for writing FreeCAD Python scripts, macros, and automation. Use when asked to create FreeCAD models, parametric objects, Part/Mesh/Sketcher scripts, workbench tools, GUI dialogs with PySide, Coin3D scenegraph manipulation, or any FreeCAD Python API task. Covers FreeCAD scripting basics, geometry creation, FeaturePython objects, interface tools, and macro development.

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。

Complete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integration

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 Model Context Protocol (MCP) servers in C#/.NET against the current ModelContextProtocol 2.x NuGet packages. Helps with cases the model gets wrong without guidance — stale versions (0.x preview or 1.x-era defaults), the v2 stateless-by-default HTTP flip, the 2026-07-28 spec deprecations (roots/sampling/logging), MCP Apps and Tasks extension packages, elicitation URL mode, per-session HTTP wiring, OAuth and reverse-proxy deploy specifics, and debugging MapMcp / STDIO / Streamable-HTTP errors. Also covers STDIO and Streamable HTTP transports (SSE is deprecated), tools, prompts, resources, completions, and a basic .NET MCP client. Trigger when the user says or implies any .NET MCP server work: ModelContextProtocol, McpServerTool, MapMcp, WithStdioServerTransport, "MCP server in C#", "MCP tool in dotnet", "expose this as MCP", or names a primitive (prompt/resource/elicitation/MCP App) in a .NET context. Skip for MCP work in other languages.

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。

Core technical indicator collection (trend EMA/ADX + mean-reversion BB/RSI + volume-price OBV/volume ratio), generates a composite signal via three-dimensional voting. Pure pandas implementation for any OHLCV data.

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。

Deep research framework for pre-IPO / private companies (Ant Group, SpaceX, Stripe, ByteDance...). Six analyst lenses — business model, financial forensics, competitive landscape, risk & governance, tech & IP, alternative-data signals — run in parallel via run_swarm, then cross-validated for signal consistency before any verdict. Built around the core challenge of private-company work: information is scarce, so every data point carries a confidence label (high / medium / low), inference is shown separately from fact, and 'I don't know' is a valid output. Outputs a fair-value range, exit-path analysis, and an information-gap map. Use for any unlisted company where you need to judge what the business is actually worth.

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。

Advanced options strategies: volatility-surface modeling (SABR / Local Vol), dynamic Greeks rebalancing, calendar spreads, volatility arbitrage and skew trading, and option market-making basics.

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。

Named investor reasoning frameworks packaged as reusable analytical lenses — 12 lenses (deep value, quality franchise, inversion, scuttlebutt growth, GARP, cycle positioning, debt cycle, forensic short, cost drag, right-business, weak-system contrarian, three questions) that stack on top of evidence already gathered, each with ordered priority signals, hard disqualifiers, and documented failure modes.

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。

Candlestick pattern recognition engine, pure pandas vectorized implementation of 15 classic candlestick patterns (5 single-candle + 5 double-candle + 4 triple-candle + 1 trend confirmation), generating a composite signal from bullish/bearish pattern scores.

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。

Supply-chain bottleneck arbitrage. Given a super-trend (AI infra, energy transition, defense, semiconductor reshoring, space economy), decompose its physical supply chain down to Layer 2/3 choke points (optics, lasers, InP/SOI substrates, IC substrates, probe cards, specialty fiberglass...) and surface under-the-radar listed companies sitting on each bottleneck. Scores each link on 6 scarcity criteria, applies mandatory valuation gates (PS/PE/safety-margin) via the financial_rigor tool, and Munger-style reverse-validates. Outputs a ranked bottleneck opportunity board. Use when the user wants hidden beneficiaries of a structural trend rather than already-priced leaders.

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。

Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Supports both basic forecasting and advanced covariate forecasting (XReg) with dynamic and static exogenous variables. Automatically checks system RAM/GPU before loading the model, validates dataset fit before processing, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model and handle your specific dataset.

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 map and remove malware, backdoors, and attacker persistence mechanisms (registry Run keys, scheduled tasks, WMI subscriptions, services, cron/init.d) from infected Windows and Linux systems using Autoruns, EDR/AV, and YARA, restoring a clean state while preventing re-infection. Use after containment and forensic analysis have identified all compromised systems and persistence mechanisms and you are ready to eradicate and recover.

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。

Detect lateral movement in network traffic using Zeek (formerly Bro) log analysis. Parses conn.log, smb_mapping.log, smb_files.log, dce_rpc.log, kerberos.log, and ntlm.log to identify SMB file transfers, NTLM account spray activity, remote service execution, and anomalous internal connections.

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。

Deploys anomaly detection for OT/ICS environments using machine learning on OT network baselines, physics-based process models, and Modbus/DNP3/OPC UA traffic analysis to flag deviations, rogue devices, and mismatches against historian data. Use for continuous OT monitoring, baselining deterministic SCADA polling, or investigating alerts from Nozomi Guardian/Dragos needing deeper protocol 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。

Configures Hardware Security Modules for cryptographic key storage using the PKCS#11 standard interface, covering key generation, signing, encryption, and key management on physical HSMs and SoftHSM2 for development. Use when protecting cryptographic keys so they never leave a hardened device boundary, or when building and testing PKCS#11-based key management workflows.

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。

Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation. Use when enabling audit policies for logon events, process creation, privilege use, and object access to feed SIEM detection rules. Activates for requests involving Windows audit policy, event log configuration, security logging, or detection-oriented logging.

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。