「spy」の検索結果

Neutral, framework-agnostic decision tree for project kickoff: "which agent / RAG / LLM framework should I reach for?" Synthesizes the ecosystem sections of 7 landmark-project SOPs (LangGraph, LlamaIndex, DSPy, CrewAI, vLLM, Aider, Dify) into one layered rubric. Core stance: frameworks are LAYERS, not competitors — a real project usually combines DSPy (compile) + LlamaIndex (retrieve) + LangGraph (orchestrate) + vLLM (serve), and you choose ONE per layer, not one to rule all. Use when starting any LLM/agent/RAG project, or whenever the "which framework?" question is asked. Deliberately neutral — unlike vendor docs and the LangChain-biased `framework-selection` on skill.sh, this skill has no horse in the race.

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Play board games on ShellGames.ai — Chess, Poker, Ludo, Tycoon, Memory, and Spymaster. Use when the agent wants to play games against humans or other AI agents, join tournaments, chat with players, check leaderboards, or manage a ShellGames account. Triggers on "play chess/poker/ludo/memory", "shellgames", "join game", "tournament", "play against", "board game", "tycoon", "spymaster".

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.NET / C# 二进制逆向。当目标是 .NET assembly（PE 头含 CLR、.exe/.dll 托管程序）、C# 编译产物（含 NativeAOT）、红队 Sharp* 工具（Rubeus / SharpHound / SharpHound 等）、.NET 混淆程序（ConfuserEx / SmartAssembly / Babel / Eazfuscator）、.NET loader / info-stealer / 套壳 malware 时使用。优先用 dnSpyEx + de4dot，需要 AI 直接操作时联动 dnSpy MCP。不用于纯 native 二进制（走 reverse-engineering / ida-reverse）。

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Downloads a competitor's live ad creatives — the actual MP4s and JPEGs — from the Meta Ad Library into a local swipe folder, through the Novoads API. One sweep per competitor, priced by a live estimate before anything is charged, media pulled the moment the response lands because the CDN links expire, and every ad carried with its permanent Ad Library URL, the page running it, and how many audiences the creative is running against, closing with the three most established and why. Use when asked to spy on competitors, find what ads a brand is running, pull a competitor's video or static creatives, build or refresh a swipe file, check who is outspending you on Meta, or source a reference ad to recreate. It finds, ranks and files ads; it does not rebuild them — a static becomes your own ads, or a reusable template, via clone-image-ad. It writes no craft analysis and no creative brief. A sweep that finds nothing is a result, never an apology.

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Program language models instead of prompting them — DSPy signatures, modules, and optimizers that tune prompts automatically.

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。

Declarative programming framework for optimizing LLM prompts through compilation and automatic tuning

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DSPy: declarative LM programs, auto-optimize prompts, RAG.

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Jest best practices, patterns, and API guidance for JavaScript/TypeScript testing. Covers mock design, async testing, matchers, timer mocks, snapshots, module mocking, configuration, and CI optimization. Baseline: jest ^30.0.0. Triggers on: jest imports, describe, it, test, expect, jest.fn, jest.mock, jest.spyOn, mentions of "jest", "unit test", "test suite", or "mock".

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Vitest (Vite ネイティブテストフレームワーク) リファレンス。 test, describe, it, expect, vi.fn, vi.mock, vi.spyOn、 beforeEach / afterEach / beforeAll / afterAll、coverage (v8 / istanbul)、snapshot、 vitest.config.ts、ワークスペース、ブラウザモード、UI モード、bench。

テスト品質のレビュー（bun:test）。`bun test` の全通過、エンティティのビルダー直接検証と createTestDb による実 SQLite E2E の使い分け、実ネットワーク（JRA）非依存、回帰テストの存在（ImportData の一致条件・枠番の JRA 割当規則・生年計算）、回帰テストの削除/skip 化の禁止、新機能・バグ修正へのテスト追随、契約の検証 vs 実装詳細への過剰結合、console spy と一時ファイルの後始末を検証。Use when user says 'テストレビュー', 'review test', 'テスト品質チェック', or 'カバレッジ確認'.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

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Using NSubstitute to create test doubles (Mock, Stub, Spy) specialized skill. Used when isolating external dependencies, simulating interface behavior, and validating method calls. Covers Substitute.For, Returns, Received, Throws and complete guidance. Keywords: mock, stub, spy, nsubstitute, mock, test double, test double, IRepository, IService, Substitute.For, Returns, Received, Throws, Arg.Any, Arg.Is, isolate dependencies, simulate external services, dependency injection testing

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Debug hanging issues in SGLang distributed inference (TP/PP/DP/EP). Covers identifying hang locations via py-spy/watchdog/cuda coredump, per-rank logging to find state divergence, binary-search methodology for locating the first diverge point, and fix patterns. Use when a multi-GPU SGLang run hangs, freezes, or times out during collective operations.

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Build an automated adversary infrastructure tracking system in Python (dnspython, python-whois, shodan, networkx) that pivots across passive DNS, certificate transparency logs, WHOIS records, and IP enrichment to map threat-actor C2 networks and flag newly registered domains matching known patterns. Use when pivoting from known indicators to discover related C2 infrastructure or maintaining a continuously updated map of a threat actor's network.

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Research competitor paid-ad presence, messaging, creative, formats, landing pages, keyword and auction signals, transparent ad libraries, and strategic gaps across supported platforms. Use for competitor ads, ad libraries, ad spy, competitive PPC analysis, competitor creative, Google Ads Transparency, Meta Ad Library, or paid-media competitor research.

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Comprehensive Linux privilege escalation methodology for offensive security engagements. Covers the full attack surface from a low-privilege shell to root: SUID/SGID binary abuse via GTFOBins, Linux capabilities exploitation (cap_setuid, cap_dac_override, cap_dac_read_search), sudo misconfigurations including NOPASSWD rules and Baron Samedit (CVE-2021-3156), cron job abuse through writable scripts, PATH hijacking, and wildcard injection with tar/rsync/chown. Includes writable /etc/passwd attacks, NFS no_root_squash exploitation, kernel exploits (DirtyPipe CVE-2022-0847, DirtyCow CVE-2016-5195, PwnKit CVE-2021-4034), Docker group container escapes, LD_PRELOAD and LD_LIBRARY_PATH hijacking for shared library injection, systemd service misconfigurations, and sensitive file enumeration for credential harvesting. Integrates automated enumeration with LinPEAS, linux-exploit-suggester, pspy for process monitoring, and GTFOBins for binary exploitation. Each technique includes detection signatures and defender-side visibility to support purple team operations. Maps to MITRE ATT&CK T1548 (Abuse Elevation Control Mechanism) and related sub-techniques. Designed for authorized penetration testing, red team engagements, and CTF competitions where you hold a low-privilege shell and need to escalate to root.

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Read how a game actually works so a mod can hook it. Decompile .NET/Mono (ILSpy), IL2CPP (Cpp2IL, Il2CppDumper), Java (Vineflower) and native code (Ghidra, IDA, via MCP servers); dump data and asset formats; reverse-engineer a binary file format and prove it with a round trip; read live memory (Cheat Engine, Frida, x64dbg); find render passes (RenderDoc). Use when a mod needs game internals, e.g. "how does the boss AI work", "find the damage function", "what format is this .sld/.pak/.dat", "where is the player position in memory".

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Detect structural macro regime transitions (1-2 year horizon) using cross-asset ratio analysis. Analyze RSP/SPY concentration, yield curve, credit conditions, size factor, equity-bond relationship, and sector rotation to identify regime shifts between Concentration, Broadening, Contraction, Inflationary, and Transitional states. Run when user asks about macro regime, market regime change, structural rotation, or long-term market positioning.

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Detect IBD-style Distribution Days for QQQ/SPY (close down at least 0.2% on higher volume), track 25-session expiration and 5% invalidation, count d5/d15/d25 clusters, classify market risk (NORMAL/CAUTION/HIGH/SEVERE), and emit TQQQ/QQQ exposure recommendations. Use after market close, before TQQQ exposure changes, or as input to FTD/market-state frameworks. Does not execute trades.

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An overview of the core model API of SeisBench, a Python framework for training and applying machine learning algorithms to seismic data. It is useful for annotating waveforms using pretrained SOTA ML models, for tasks like phase picking, earthquake detection, waveform denoising and depth estimation. For any waveform, you can manipulate it into an obspy stream object and it will work seamlessly with seisbench models.

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Reverse-engineer how competitors do programmatic SEO. Detects URL pattern clusters (vs/, integrations/, for-{industry}/), estimates page count per pattern, analyzes template quality, infers which patterns actually drive traffic, and identifies gaps you can exploit. Outputs a competitive pSEO landscape report.

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Understand implementation details of .NET code by decompiling assemblies. Use when you want to see how a .NET API works internally, inspect NuGet package source, view framework implementation, or understand compiled .NET binaries.

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Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.

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Answer prediction questions using market trading data, not opinions. Use when the user asks probability questions about geopolitics, economics, markets, industries, or any topic where real money is being traded on the outcome. Examples: 'What's the probability of WW3?', 'Will there be a recession?', 'Is AI in a bubble?', 'When will the Russia-Ukraine war end?', 'Is it a good time to buy gold?', 'Will SPY drop 5% this month?', 'Is NVDA options premium overpriced?'. The skill reads prices from prediction markets, commodities, equities, options chains, derivatives, yield curves, and currencies, then cross-validates multiple signals to produce a structured probability report.

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。