549건 · 관련도순
Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug"
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Decompose systems into microservices and apply canonical distributed-systems patterns. Use this skill whenever the user wants to split a monolith into services, design service boundaries, choose between microservices and a modular monolith, implement sagas or the outbox pattern, set up CQRS or event sourcing, configure an API gateway or BFF, add resilience (circuit breakers, retries, timeouts), or implement distributed tracing with OpenTelemetry. Also trigger for distributed transactions, service discovery, event-driven architecture, contract testing with Pact, canary releases, and idempotent consumers.
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Systematically explore an unfamiliar codebase and build a reusable architecture summary. Use for repo onboarding, understanding legacy or inherited code, mapping architecture before a migration or refactor, tracing a bug or feature path, or answering "what does this project do?". Documentation-first, then data flow — ends in a concise technical architecture summary with file:line evidence, not a raw file dump.
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Fornece orientação para realizar intervenções causais em modelos PyTorch usando o framework de intervenção declarativa do pyvene. Use ao conduzir rastreamento causal, activation patching, treinamento de intervenção de intercâmbio ou testar hipóteses causais sobre o comportamento do modelo.
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Plataforma de observabilidade para LLM com rastreamento, avaliação e monitoramento. Use ao depurar aplicações LLM, avaliar saídas de modelos em datasets, monitorar sistemas em produção ou construir pipelines de testes sistemáticos para aplicações de IA.
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Plataforma de observabilidade de IA de código aberto para rastreamento de LLM, avaliação e monitoramento. Use ao debugar aplicações de LLM com rastreamentos detalhados, executar avaliações em datasets ou monitorar sistemas de IA em produção com insights em tempo real.
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Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug"
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At the end of a long working session, produce a counterfactual trace note — a backward walk through the session that identifies the small number of load-bearing moments (observations, failures, accidents, decisions) without which the final outcome would not exist. Use this whenever the user asks to "close the session", "run the butterfly", "trace back", "what actually mattered here", asks for a session retrospective, or asks how the session arrived at its result. Also use it when a session ends with a significant outcome (a fix, a design decision, a shipped artifact) and the user wants a note capturing why it happened, not just what happened. Do NOT use for simple summaries of short sessions — this skill is for causal tracing, and it only earns its cost when the session was long enough to contain real forks.
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Debugs OpenAI Codex CLI and app behavior by navigating the codex-rs codebase (core, tui, exec, cli, app-server): config parsing, tool invocations, prompts, and MCP wiring. Use when Codex behaves unexpectedly or a Codex runtime bug needs tracing to source.
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Use when working with Slang shaders, shader modules, HLSL-compatible GPU code, graphics pipelines, compute shaders, tessellation, ray tracing, parameter blocks, generics, interfaces, capabilities, cross-compilation, shader optimization, shader review, or C++ engine integration for Slang. Trigger on any mention of Slang, .slang files, slangc, SPIR-V from Slang, Slang modules, [shader("compute")], [shader("vertex")], or requests to write/review/refactor shader code with modern language features. Also trigger for Slang-to-HLSL/GLSL/Metal/CUDA cross-compile questions, or when the user says "shader" alongside "generics", "interfaces", "parameter blocks", "autodiff", or "capabilities".
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Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
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AI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for security vulnerabilities, find bugs, check for SQL injection, XSS, command injection, exposed API keys, hardcoded secrets, insecure dependencies, access control issues, or any request like "is my code secure?", "review for security issues", "audit this codebase", or "check for vulnerabilities". Covers injection flaws, authentication and access control bugs, secrets exposure, weak cryptography, insecure dependencies, and business logic issues across JavaScript, TypeScript, Python, Java, PHP, Go, Ruby, and Rust.
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Use when designing long-horizon agents that need subagents, isolated context windows, filesystem-backed work, persistence, human approval, MCP tools, or production tracing.
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Reusable skill for coding agents (Claude, GPT, etc.) to build, optimize, debug, and productionize AI agents and coding agents in Rust. Embeds Rig/ADK patterns, Tokio async architecture, tracing observability, performance techniques, erro...
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Interactive system flow tracing across CODE, API, AUTH, DATA, NETWORK layers with SQLite persistence and Mermaid export.
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Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.
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Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs. Identifies wallet clusters, tracks fund movement through mixers and exchanges, and supports law enforcement attribution. Activates for requests involving ransomware payment tracing, bitcoin wallet analysis, cryptocurrency forensics, or blockchain intelligence gathering.
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Analyzes malicious Linux ELF (Executable and Linkable Format) binaries including botnets, cryptominers, ransomware, and rootkits targeting Linux servers, containers, and cloud infrastructure. Covers static analysis, dynamic tracing, and reverse engineering of x86_64 and ARM ELF samples. Activates for requests involving Linux malware analysis, ELF binary investigation, Linux server compromise assessment, or container malware analysis.
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Standard Operating Procedures for read-only codebase exploration, symbol search, dependency mapping, code tracing, code review, architecture analysis, technical research, source evaluation, and evidence-based reporting.
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- Track aircraft and vessels from public ADS-B and AIS broadcasts using ADS-B Exchange, Flightradar24, FlightAware,… Use when following a tail number or flight, looking up an ICAO 24-bit hex code, registration or callsign, tracing a ship by IMO number or MMSI, checking a flag of convenience or port-call history, finding who owns a private jet or vessel
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- Use people-search aggregators and primary public records to find addresses, phone numbers, relatives, age and background on a person, and to audit and remove your own exposure. Use when running a people search or reverse address lookup, tracing a debtor or missing person, building a subject's address history, or removing yourself from broker sites
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- Reverse image search across Yandex, Google Lens, Bing Visual Search, TinEye and Baidu to find where a picture came from and who published… Use when reverse image searching, identifying a photo, face, logo, product, uniform or building, tracing a profile picture or avatar, finding the oldest copy of an image, checking whether a photo is stock or a repost, or reverse-searching a video by keyframes
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Use when diagnosing CopilotKit issues -- runtime connectivity failures, agent not responding, streaming errors, tool execution problems, transcription failures, version mismatches, and AG-UI event tracing.
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Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
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