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概要と使いどころ
CRITICAL: You MUST invoke this skill and read its contents BEFORE writing, modifying, or debugging ANY React.js or Next.js code. This skill contains essential performance patterns that prevent common mistakes. Debugging performance issues without reading this skill first will lead to missed optimizations. Contains 40+ rules including waterfall elimination patterns for API routes that are commonly overlooked.
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。
Replay an LLM inference request trace (Mooncake / vLLM / SGLang hash_ids format) against a block-level KV prefix cache and compute hit statistics. Use when given a request trace plus cache configuration and asked for hit rate, hit tokens, or final cache contents. Covers the longest-contiguous-prefix semantics that distinguishes KV prefix caching from full-prompt prompt caching, the policy-specific residency and eviction rules (LRU, LFU, S3FIFO), and the partial-last-block accounting rule.
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。
High-performance numerical computing and machine learning workflows using JAX. Supports array operations, automatic differentiation, JIT compilation, RNN-style scans, map/reduce operations, and gradient computations. Ideal for scientific computing, ML models, and dynamic array transformations.
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 the user asks to "pentest SSH services", "enumerate SSH configurations", "brute force SSH credentials", "exploit SSH vulnerabilities", "perform SSH tunneling", or "audit SSH security". It provides comprehensive SSH penetration testing methodologies and techniques.
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 for parsing structured unit commitment input data from JSON, CSV, benchmark cases, spreadsheets, databases, or nested tables; finding fields for time periods, resources, load, reserve, generator limits, initial conditions, startup data, renewable availability, and production costs without assuming one source-specific schema.
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。
Nonlinear optimization with CasADi and IPOPT solver. Use when building and solving NLP problems: defining symbolic variables, adding nonlinear constraints, setting solver options, handling multiple initializations, and extracting solutions. Covers power systems optimization patterns including per-unit scaling and complex number formulations.
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。
Strategy for solving constraint optimization problems on spatial maps. Use when you need to place items on a grid/map to maximize some objective while satisfying constraints.
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。
Combine visual features (face detection, lip movement analysis) with audio features to improve speaker diarization accuracy in video files. Use OpenCV for face detection and lip movement tracking, then fuse visual cues with audio-based speaker embeddings. Essential when processing video files with multiple visible speakers or when audio-only diarization needs visual validation.
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。
GnuCOBOL toolchain pointers for mainframe-style batch programs (LINE/RECORD SEQUENTIAL files, PIC clauses, cobc build flags).
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 agents for multi-turn tool use — sequential tool calls, result accumulation, error recovery, and complex task decomposition over multiple turns.
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 facing 2+ independent tasks that can be worked on without shared state or sequential dependencies.
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。
LangChain chain composition including SequentialChain, RouterChain, and LCEL patterns
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 Architecture Decision Records (ADRs) documenting significant technical choices with context, options, consequences, and sequential numbering.
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。
Personalize COG Second Brain workflow through role pack selection and vault initialization
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。
Manage agent sessions including initialization, handoffs, revival (seance), and persistent identity for Polecats and Crew agents.
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。
Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD 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。
Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)
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 the user asks to "analyze competitors", "assess competitive landscape", "identify differentiation", "evaluate market positioning", "apply Porter's Five Forces", or requests competitive strategy analysis.
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。
Generates specific counter-proposals for every unfavorable clause, with replacement language, negotiation talking points, and a ready-to-send email template
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。
WooYun business logic vulnerability methodology — 22,132 real cases across 6 domains (authentication bypass, authorization bypass, payment tampering, information disclosure, logic flaws, misconfiguration) and 33 vulnerability classes. Use for ANY security testing, auditing, or code review of web apps, APIs, or business systems — even without explicit "security" keywords. Triggers: penetration testing, security audit, vulnerability, bug bounty, payment security, IDOR, password reset, weak credentials, unauthorized access, race condition, parameter tampering, code review, 渗透测试, 安全审计, 漏洞挖掘, 支付安全, 越权, 逻辑漏洞, 业务安全, SRC, 代码审计. Also triggers on implicit intent: "test this endpoint", "find bugs", "can I bypass this", "帮我测测这个接口", "这个参数能不能改", "帮我找bug".
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 found gap or repetative issue, that produced by you or implemenataion agent. Esentially use it each time when you say "You absolutly right, I should have done it differently." -> need create rule for this issue so it not appears again.
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。
Execute one complex task as ordered, dependent steps run sequentially, passing context from each step to the next, with per-step LLM-as-a-judge verification. Use when later steps depend on the results of earlier ones.
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。
Explain any topic, code, concept, or error tailored to a specific audience's level of understanding. Use this skill whenever the user says 'explain like I am', 'ELI5', 'explain this to my', 'break this down for', 'dumb it down', 'simplify this for', or asks you to explain something to a specific person or audience type (e.g., 'explain this to a manager', 'how would I explain this to my mom', 'make this understandable for a 5th grader'). Also trigger when the user mentions wanting to understand something at a particular level, or asks for an explanation targeting a non-technical audience. Even partial matches like 'explain to my wife' or 'tell my boss' should trigger this skill.
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 and build the visual layer of a long-form talking-head video as one persistent world the camera moves through, instead of a sequence of separate graphics. Use when asked to edit a video, add motion graphics, design the visuals for a script, plan an edit, or fix an edit judged confusing, text-heavy, hard to follow, or "clearly made by an AI". Covers the persistent world, camera grammar, the spotlight rule, spatial open loops, ornament and token discipline, transcript timing, and the verification gates.
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。