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Use when the user asks about Russian state-sponsored cyber operations or specific actors (APT28/Fancy Bear, Sandworm, Cozy Bear/APT29, Turla, GRU-affiliated hacktivist fronts like CARR/NoName057), wartime ICS/OT campaigns, or pro-RU information operations. Self-updating knowledge cell.

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 about phishing campaigns, social-engineering techniques, BEC (business email compromise), pretexting, AiTM (adversary-in-the-middle) kits, or specific phishing-kit families. Self-updating knowledge cell.

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 about supply-chain attacks, third-party / vendor compromise (SolarWinds, Kaseya, 3CX, MOVEit, XZ-utils-style), software-bill-of-materials risks, or library / dependency-injection attacks. Self-updating knowledge cell.

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 about North Korean state-sponsored cyber operations or specific DPRK actors (Lazarus, APT38, BlueNoroff, Andariel, Kimsuky, etc.), revenue-generation campaigns, IT-worker schemes, or DPRK targeting of cryptocurrency / supply chain. Self-updating knowledge cell.

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 about Chinese state-sponsored cyber operations or specific PRC-aligned actors (APT41, Volt Typhoon, Mustang Panda, APT10, APT31, Salt Typhoon, etc.), MSS/PLA-attributed campaigns, or PRC sector targeting. Self-updating knowledge cell.

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 about infostealer families (LummaC2, RedLine, Vidar, Stealc, Raccoon, Rhadamanthys, etc.), log marketplaces (Russian Market, Genesis successors, BidenCash, Hudson Rock corpus), or stealer-driven incidents and credential exposure. Self-updating knowledge cell.

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 about initial access brokers (IABs), the access-listing market, ransomware-feeding-IAB pipelines, specific broker handles, or how access is priced and packaged. Self-updating knowledge cell.

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 about carding, BIN attacks, payment-card breach markets, fullz/CVV2 trade, autoshops (BidenCash, Brian's Club, Russianmarket, B1ack's Stash), or financial-fraud TTPs. Self-updating knowledge cell.

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 about Iranian state-sponsored cyber operations or specific IRGC/MOIS-aligned actors (APT35/Charming Kitten, APT34/OilRig, MuddyWater, Imperial Kitten, etc.), wiper campaigns, front-group hacktivist personas (Handala, Cyber Av3ngers), or anti-Iran operations such as Predatory Sparrow. Self-updating knowledge cell.

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 you need to answer "which attacker techniques do our controls actually stop, and how well?", "what controls should I have for this threat?", or "what telemetry should I collect to detect it?" — joining a customer's or your own security control baseline to ATT&CK techniques using a public, versioned evidence base of 9,545 control-to-technique mappings from six sources. Produces four ranked lists (addressed strongly, addressed weakly, real gaps, and techniques no control anywhere addresses). Use for control gap analysis, security programme prioritisation, board reporting on coverage, or the Resistance Strength side of a FAIR risk assessment. Invoke after /threat-actor-profiling or /lookup-liberty91 has produced a technique list.

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。

Dark web intelligence collection methodology — vendor-first access posture, sourced reference lists for 35+ underground forums and 30+ Telegram channels, OPSEC primer, passive-monitoring strategy, and bundled Python CLIs for onion-indexer search, Telegram channel monitoring, and local keyword matching. Use when the user wants to design or run dark-web collection, build a selector list, pick a vendor, or set up monitoring 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。

Use when the user asks about hacktivist activity (Killnet, NoName057(16), IT Army of Ukraine, Anonymous Sudan, RipperSec, CARR, etc.), DDoS-claiming groups, politically-motivated cyber operations, or wartime cyber-ops chatter. Self-updating knowledge cell.

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 and remove the tells of AI-generated writing in BOTH English and Spanish, and read back the evidence honestly. Use when the user asks to "de-AI" / "humanize" / "un-slop" a draft, to examine whether text carries the tells (delve, tapestry, "it's not just X, it's Y", "here's the thing", em-dash overuse, an assistant's own closing line left in the document), to compare documents for overlap, or mentions signs-of-ai / SignsOfAI. Backed by the SignsOfAI engine — for a measured 0–100 score, sentence-rhythm burstiness, originality, citations, a writer baseline or perplexity, hand off to that engine (web app, CLI or MCP server) as described below. It cannot determine who wrote a text and must never imply that it can.

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, adapt, and apply specified discussions, feedback, findings, or references to existing project work. Preserve coverage, corrections, and selected intent; judge fit and carry adopted effects through the authorized result. Includes technical review feedback; incidental sources or understanding material without a target-work adoption question need no separate incorporation workflow.

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 when building AI agents using prompt-native architecture where features are defined in prompts, not code. Use it when creating autonomous agents, designing MCP servers, implementing self-modifying systems, or adopting the "trust the agent's intelligence" philosophy.

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 applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.

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/update .agent/constitution.md. Use when commands/boundaries/constraints must be confirmed before baseline or code changes. Draft v0 from repo evidence, then interview user.

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。

Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.

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 specialized agent experts with pre-loaded domain knowledge using the Act-Learn-Reuse pattern. Use when building domain-specific agents that maintain mental models via expertise files and self-improve 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。

Use when creating, improving, or troubleshooting Claude Code subagents. Expert guidance on agent design, system prompts, tool access, model selection, and best practices for building specialized AI assistants.

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。

Guide for creating effective Claude Code agents. This skill should be used when users want to create a new agent (or update an existing agent) that configures Claude with specialized system prompts, tool restrictions, model selection, and MCP/skill integrations.

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。

Validates agent configurations for model selection, tool permissions, focus areas, and approach quality. Use when reviewing, auditing, improving agents, or learning agent best practices.

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 you need to install the embedded robot agents into either .cursor/agents or .claude/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. This should trigger for requests such as Install embedded agents; Bootstrap .cursor/agents; Bootstrap .claude/agents; Copy robot agents. Part of cursor-rules-java project

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。

Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection

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。