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概要と使いどころ
Good-faith adversarial scrutiny of an idea or plan. Spawns critical skeptics across relevant lenses, pairs them with an advocate defending the idea, and synthesizes the exchange into a report. Produces feedback only — no code, no tickets, no artifacts.
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Prospective failure imagination for a plan, decision, or running system. Operates in two modes — **plan mode** (a plan has not yet been committed to; imagine its catastrophic failure broadly) and **scenario mode** (a specific catastrophic scenario is posed against an existing system; investigate causes against the actual code and architecture). Spawns parallel pre-mortemers in isolation across three categories of lens: standard failure classes (technical, operational, estimation, scope, adoption, dependency, team, incentive, detection, reversibility, adversarial), 0-3 ad-hoc target-specific lenses the orchestrator names when warranted, and a first-principles lens that always runs to catch what the prescribed taxonomy misses. Synthesizes into a prioritized risk register with early-warning signals. Produces feedback only — no code, no tickets, no artifacts.
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。
Comprehensive test suite review across five phases. Surveys unit coverage, integration coverage, E2E (browser) coverage for webapps, fuzz coverage, and test quality — in that order. Advisory only — produces findings and proposes tickets; does not implement test 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。
Multi-ticket batch workflow. Takes a batch of tickets, plans execution order, implements each via /implement in autonomous mode, runs cross-cutting quality passes, and presents results for final review.
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。
Verify that browser profiles are actually isolated from one another instead of assuming it - confirm each profile's timezone agrees with its own exit IP, that WebRTC exposes only the proxy, that canvas and WebGL hashes stay identical across relaunches of one profile, and that no two profiles share a persona, a cookie jar, or an address. Use when several of your own accounts or test identities run from one machine and the setup needs checking, when a profile tested clean but something still looks off, when choosing which detection suites to run (CreepJS, whoer, browserleaks WebRTC, pixelscan, liarjs), when auditing what a vendor runtime does with API and proxy credentials, or when asking which layers browser isolation cannot cover at all. Also for 'profile isolation check', 'fingerprint consistency test', 'timezone mismatch', 'WebRTC leak', 'canvas hash unstable', 'account association', 'temporary profile', '防关联', '多账号', '隔离自检'. The SDK is anti-detect-browser; MCP is browser-mcp-agent.
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 the same scrape or task across many accounts at once - each in its own browser profile with its own fingerprint, cookies and exit IP - and read data from sites that need a session or that answer a plain HTTP scraper with a captcha while answering a real browser. One command per site returns JSON, so there are no selectors to write or repair: Amazon and Walmart search, Google and DuckDuckGo results, Reddit posts and comments, X timeline, Medium, Yelp, Indeed job listings, Hacker News, GitHub, PyPI, npm, plus exit-IP and fingerprint checks. Use for multi-account operations you are authorized to run, price and listing monitoring per region, SERP collection, logged-in data, and scrapers that keep breaking. Also for 'scrape amazon', 'google search results', 'reddit data', 'scrape logged in site', 'run task on many accounts', 'site blocks my scraper', 'scraping without selectors'. Node or Python.
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。
Drive Chromium from standard Playwright APIs with a real-device fingerprint applied in the kernel, one persistent isolated profile per identity, and a per-profile proxy whose exit IP sets timezone and WebRTC - JavaScript (npm 'anti-detect-browser') or Python (PyPI 'antibrow'). Use when sessions must stay logged in across runs and stay separate, when a scraper or agent is blocked by an incoherent headless fingerprint, when checking ads or pricing from another region, when a page must be reached as a phone rather than a desktop, when automation mints a profile per task, when running several of your own accounts from one machine, or when testing how your own bot detection scores a real device. Also for 'antibrow', 'fingerprint browser', 'multi-account browser', '防关联', '多账号', '安卓模拟', 'Android profile', 'mobile fingerprint', 'temporary profile', 'CreepJS', 'residential proxy', 'browser-use', 'crawl4ai'. MCP control is browser-mcp-agent; isolation is multi-account-isolation.
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 monitoring Crewrift evaluations, rounds, or rankings across turns with a persistent poller.
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。
Apply these opinionated .NET 8 architecture conventions whenever structuring or reviewing a backend service: clean architecture layering and which direction dependencies point, when CQRS with MediatR is worth it, cross-cutting concerns as pipeline behaviours, minimal APIs grouped by feature, keeping DbContext in Infrastructure, health checks and structured logging, WebApplicationFactory integration tests, and when AOT pays off.
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。
Capture a solved, verified problem as a durable learning in `docs/solutions/` so the next agent or engineer does not repeat the mistake or redo the investigation, and keep the `CONCEPTS.md` glossary in step. Use after a fix, debugging session, or design decision whose reasoning is not readable from the final code, tests, or existing docs — "document this", "write up what we learned", "capture this learning", "add it to solutions", "that worked, save it for next time". Writes nothing for routine fixes the code already explains. For auditing or cleaning up existing learnings, use `learn-with-docs-refresh`.
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。
Write a short, fact-checked reply that answers a colleague's question in one meaning only, ready to copy and paste. The input is their pasted message. Check the claims against the code first, use the project glossary terms, and print only the reply in chat. Read-only — no writes to code, the issue tracker, GitHub, chat or any MCP. Use on "/cortex-communication:answer-buzzkill", "help me answer", "reply to this question", or when the user pastes a colleague's question and asks for an answer in the same manner.
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 and maintain the learnings in `docs/solutions/` against the current codebase — fix drifted paths and links, merge overlapping docs, replace guidance the code no longer supports, delete obsolete docs, reconcile the `CONCEPTS.md` glossary, then report and commit. Also bootstraps `CONCEPTS.md` on request and, when asked, culls docs whose reasoning the code already explains. Use for "refresh the learnings", "audit docs/solutions", "are our solution docs still accurate", "clean up / prune the learnings", "create a CONCEPTS.md", or after a refactor, rename, migration, or dependency upgrade that likely invalidated documented solutions. Not for capturing a new learning — use `learn-with-docs`.
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。
Trust-boundary security audit of cqs — fans out unbiddable-auditor agents across 6 categories (RT-INJ/RT-FS/RT-RES/RT-DATA/RT-RELAY/RT-EXFIL), attacker mindset, run-the-attack PoC + regression guard.
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。
Operate across Google Drive, Docs, Sheets, and Slides as one workflow surface for plans, trackers, decks, and shared documents. Use when the user needs to find, summarize, edit, migrate, or clean up Google Workspace assets without dropping to raw tool calls.
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。
Prevent silent decimal mismatch bugs across EVM chains. Covers runtime decimal lookup, chain-aware caching, bridged-token precision drift, and safe normalization for bots, dashboards, and DeFi tools.
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。
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development 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。
Patterns for robust error handling across TypeScript, Python, and Go. Covers typed errors, error boundaries, retries, circuit breakers, and user-facing error messages.
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 a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants voice consistency without generic AI writing tropes.
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 platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
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。
Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).
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。
Persistent per-project memory for Claude Code. Auto-loads project context on session start, tracks sessions with git activity, and writes to native memory. Commands run deterministic Node.js scripts — behavior is consistent across model versions.
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。
Codified expertise for customs documentation, tariff classification, duty optimization, restricted party screening, and regulatory compliance across multiple jurisdictions. Informed by trade compliance specialists with 15+ years experience. Includes HS classification logic, Incoterms application, FTA utilization, and penalty mitigation. Use when handling customs clearance, tariff classification, trade compliance, import/export documentation, or duty optimization.
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。
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
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。
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.
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。