「detect」の検索結果

Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".

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。

Integrate API quality gates into CI — linting, breaking change detection, and coverage checks. Use when asked to "add API checks to CI", "detect breaking changes in CI", or "set up an API quality gate".

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。

Design a dependency scanning program — CVE detection, license checks, and CI gates. Use when asked to "scan our dependencies", "set up CVE detection", or "add a dependency CI gate".

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 existing security controls and detection coverage — find gaps against MITRE ATT&CK. Use when asked to "audit our detection coverage", "where are our security control gaps", or "check our MITRE coverage".

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 the current project to a live HTTPS URL via Cybrix. Activates on any request to make the current project public, get a URL for it, deploy it, ship it, host it, publish it, put it online, or make it live — including casual phrasings like "send this to the internet", "share this as a link", "give me a URL", "make this accessible online". Activates whether the user mentions Cybrix by name or not (when no other host like Vercel, Netlify, Cloudflare Pages, Railway, or Render is named). Also activates on equivalent phrases in other languages — Russian ("задеплой", "опубликуй", "выложи в сеть", "запушь это в инет", "сделай ссылку"), Spanish ("despliega esto", "publica esto", "ponlo en línea"), German ("deploy das mal", "stelle das online"), and other common languages where the intent is clearly to make a project publicly accessible via URL. Uses heuristic detection to determine if a project is static or needs a server runtime — works with any framework, not just a known list. Automatically detects and handles environment variables so the build receives everything it needs. Returns a live URL on *.cbrx.cc or a user-configured custom domain. Does NOT activate when the user explicitly names a different host (Vercel, Netlify, Cloudflare, Railway, Render).

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。

Botnet architecture taxonomy, detection techniques, and defensive analysis. Covers C2 topologies, DGA analysis, fast-flux detection, P2P overlay mapping, blockchain C2, and ML-based traffic fingerprinting. Defensive research for understanding and countering distributed malicious 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 writing Python scripts that must run on Windows, Linux, and macOS — especially when Rich or Typer output breaks on Windows, when dealing with Unicode/encoding errors, ANSI escape handling, terminal detection, path separators, or console color support. Provides verified cross-platform patterns covering stdout/stderr encoding guards, Windows console quirks, terminal capability detection, and portable I/O for CLI, TUI (Rich/Textual), and GUI environments.

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 returns authorization, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management. Informed by returns operations managers with 15+ years experience. Includes grading frameworks, disposition economics, fraud pattern recognition, and vendor recovery processes. Use when handling product returns, reverse logistics, refund decisions, return fraud detection, or warranty claims.

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 resume parsing (detect format → extract fields). Uses a combination of format detection, text extraction, and LLM parsing to normalize resume 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。

Optional power-up — detects oversized codebases/docs and suggests tobi/qmd for local semantic search. Bridges cm-continuity (working memory) with long-term document retrieval. Zero-config detection, non-intrusive suggestion.

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。

Monitors AWS CloudFormation stacks for configuration drift using the AWS SDK DetectStackDrift and DescribeStackResourceDrifts APIs. Generates remediation templates and integrates with AWS Config rules for continuous compliance.

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 SEO analysis for any website or business type. Performs full site audits, single-page deep analysis, technical SEO checks (crawlability, indexability, Core Web Vitals with INP), schema markup detection/validation/generation, content quality assessment (E-E-A-T framework per Dec 2025 update extending to all competitive queries), image optimization, sitemap analysis, and Generative Engine Optimization (GEO) for AI Overviews, ChatGPT, and Perplexity citations. Analyzes AI crawler accessibility (GPTBot, ClaudeBot, PerplexityBot), llms.txt compliance, brand mention signals, and passage-level citability. Industry detection for SaaS, e-commerce, local business, publishers, agencies. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "page speed", "structured 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。

Detect which external metric sources apply to this product (GitHub, Plausible, Stripe, etc.) and configure adapters. Retrofit entry point for projects that started before v0.14; also runnable to refresh source list when the product grows.

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。

Builds regime detection models with hidden Markov, threshold, and Bayesian change-point methodologies for strategy adaptation. Use when modeling regime changes, detecting market shifts, or adapting strategies to market conditions.

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。

Structures backtesting methodology with out-of-sample testing, cross-validation, and overfitting detection techniques. Use when validating backtests, detecting overfitting, or ensuring backtest robustness.

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。

Parse Claude Code JSONL session logs from ~/.claude/projects/ for tool call inventory, token costs, error detection, subagent traces, and compaction detection

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。

Automated security scanning pipeline covering SAST (Semgrep), SCA (OWASP dependency-check), SBOM generation (Syft), vulnerability scanning (Grype), and secrets detection (detect-secrets). Invoked by security-architect for pre-commit gates, CI integration, and finding triage.

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。

Configurable regex-based alert system for detecting patterns in tool calls and session activity. Supports error triggers, content regex matching, token threshold triggers, and pattern detection with configurable actions.

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 online forums (Reddit, HN, ProductHunt) for recurring user pain points, feature requests, and unmet needs. Invoke for market research, pain-point discovery, trend detection, and competitive intelligence. Designed for scheduled execution via CronCreate.

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。

Customer feedback analysis — sentiment detection, NPS/CSAT frameworks, feature request clustering, support ticket triage, churn signal detection, and feedback-to-roadmap translation

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 Claude Code context compaction events in session JSONL logs. Identifies compaction boundaries, measures token delta before/after, reports compaction events with timestamps and token impact.

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。

Trains the HUMAN user's critical thinking through four modes: drill (argument-analysis items with a single defensible answer, judge stance), scene (Socratic exploration of synthetic scenes or user-supplied material, no verdicts on interpretations; includes a configure track — design the information request and verification plan for a decision before any analysis), expedition (guided audit of impossible-tier problems from verified packs), and detective (a runtime-generated multi-layer case worked as an escape room, guide-and-judge stance). Use when the user wants to practice critical thinking, analyze arguments, hunt assumptions, examine bias, train reasoning, or decide what information a decision needs first. Triggers: critical thinking practice, train my thinking, drill, scene, byom, configure, information plan, what would I need to know, spot manipulation tactics, scam literacy, 批判思考練習, 話術辨識, detective, 查案, 破案, 偵探.

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。

Stealth headless browser with CDP server for anti-fingerprint browsing, parallel scraping, and low-memory CDP automation. This skill should be used when stealth browsing, anti-detection scraping, headless CDP automation with fingerprint protection, or tracker-free page fetching is needed. Triggers on 'stealth browse', 'anti-fingerprint', 'obscura', 'stealth CDP', 'undetectable scraping', 'headless stealth', 'tracker-free browsing'.

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。

Evaluates whether work-in-design is ready to hand off from a chat design conversation to autonomous execution (Claude Code, n8n, agent runtime). Runs a 7-condition gate: spec stability, verification surface, invariants, pump-primer, work decomposition, rollback cost, token budget headroom. Three invocation modes — deliberate (caller provides work_context, returns JSON verdict), proactive sensing (Claude detects handoff signals in design conversation and offers the check), conversational walkthrough (Claude walks the 7 conditions as discussion topics). Returns structured JSON in all modes. Use when designing a Claude Code deployment, scoping an autonomous run, or deciding next move. Trigger on: "ready to hand off," "ready for execution," "is this CC-ready," "handoff check," "walk me through readiness," "are we ready to ship this," "should I just hand this off," or proactive detection. Do NOT use for evaluating completed work, runtime selection, or prompt quality. Profile-agnostic.

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。