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概要と使いどころ
Format string exploitation playbook. Use when printf-family functions receive user-controlled format strings, enabling arbitrary stack reads (%p/%s), arbitrary memory writes (%n/%hn/%hhn), GOT/hook overwrites, and canary/libc/PIE leaks.
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。
Talk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less. Use when the user mentions "customer interviews", "validate my idea", "users say they want it but dont buy", "leading questions", "The Mom Test", "customer feedback bias", or "interview script". Also trigger when preparing user-research questions, interpreting ambiguous feedback, or designing customer-discovery that avoids false positives. Covers commitment and advancement, avoiding compliments, and extracting signal from noise. For product-market fit, see jobs-to-be-done. For rapid prototype testing, see design-sprint.
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Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", "test assumptions", "innovation accounting", "build-measure-learn", "minimum viable experiment", "should we pivot", "test a business idea cheaply", or "build the smallest version first". Also trigger when deciding what to include in a first version, measuring startup progress, or evaluating whether to change direction on a product bet. Covers innovation accounting and actionable metrics. For 5-day prototype testing, see design-sprint. For customer motivation analysis, see jobs-to-be-done.
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Guided journey from a raw app idea to a validated, cleanly architected first version that ships on a sustainable cadence. Orchestrates ten skills phase by phase - lean-startup, design-sprint, clean-architecture, domain-driven-design, clean-code, pragmatic-programmer, system-design, ios-hig-design, 37signals-way, software-design-philosophy - asking the user questions at every decision point and recording results in the project docs/ folder (PRODUCT.md, ARCHITECTURE.md, EXPERIMENTS.md, CREATE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to build a new app, validate an idea before writing code, architect an MVP that will not need a rewrite, or says 'help me build my app the right way'. App already exists: use improve-app or grow-app. Business idea not yet validated: run create-business first. Marketing site only: use create-website. Architecture-only question: design-code-architecture. For one framework in isolation, invoke that skill directly.
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。
Guided journey from raw idea to a validated, positioned, priced business with a chosen beachhead. Orchestrates ten skills phase by phase - jobs-to-be-done, mom-test, design-sprint, lean-startup, good-strategy-bad-strategy, blue-ocean-strategy, obviously-awesome, hundred-million-offers, monetizing-innovation, crossing-the-chasm - asking the user questions at every decision point and recording results in the project docs/ folder (CUSTOMER.md, POSITIONING.md, OFFER.md, CREATE-BUSINESS-PLAN.md) so the journey resumes across sessions. Use when the user wants to start a new business, validate a startup idea, find product-market fit before building, or says 'I have an idea for a company'. Do not use once the business has paying customers: use grow-business to add revenue and customers, or improve-business to fix strategy and operations. For building the product itself use create-app or create-website. For one framework in isolation, invoke that skill directly.
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。
Discover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or "functional vs emotional jobs". Also trigger when investigating why users choose competitors, designing features around real customer needs, or reframing a value proposition. Covers JTBD interviews, competition analysis, and jobs-oriented roadmaps. For product positioning, see obviously-awesome. For rapid validation, see design-sprint. For non-leading interview technique, see mom-test.
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。
Semantic topic cluster planning and automated execution engine for claude-blog. Performs SERP-based keyword research, groups keywords by search intent and SERP overlap, builds a hub-and-spoke cluster architecture, generates an interactive SVG cluster map, and executes the full cluster by orchestrating blog-write calls with shared cluster context and automatic internal-link injection. Fills the strategy-to-execution gap: blog-strategy plans the blueprint, blog-cluster builds the house. Use when user says "blog cluster", "topic cluster", "content cluster", "cluster plan", "cluster execute", "pillar content", "hub and spoke", "content ecosystem", "cluster map".
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。
Semantic topic cluster planning and automated execution engine for claude-blog. Performs SERP-based keyword research, groups keywords by search intent and SERP overlap, builds a hub-and-spoke cluster architecture, generates an interactive SVG cluster map, and executes the full cluster by orchestrating blog-write calls with shared cluster context and automatic internal-link injection. Fills the strategy-to-execution gap: blog-strategy plans the blueprint, blog-cluster builds the house. Use when user says "blog cluster", "topic cluster", "content cluster", "cluster plan", "cluster execute", "cluster map".
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 this skill when designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, realtime voice agents, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.
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。
Strip the machine fingerprint out of any draft - em dashes, AI slop words, invisible watermark characters - and score it against a five-check detection panel before it goes out. Use whenever text needs to sound human, when the user says humanize, "does this sound like AI", "remove the em dashes", "de-slop this", "will this get flagged", or before any LinkedIn post, comment, reply or DM is shown to the user.
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。
Aligns learning material to the standard it claims — choosing the right framework for the grade and subject, citing standards by code rather than reproducing their text, and telling a real alignment from a decorative one. Use this to align a worksheet, lesson or workbook to Common Core, NGSS or a state framework, to check an alignment claim before publishing, or to decide what may lawfully be printed on the cover.
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。
NGS analysis toolkit. Used for BAM to bigWig conversion, quality control (correlation, PCA, fingerprint plots), heatmaps/feature plots (TSS, peaks), suitable for ChIP-seq, RNA-seq, ATAC-seq visualization.
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 this skill when converting academic papers to promotional and presentation formats, including interactive websites (Paper2Web), presentation videos (Paper2Video), and conference posters (Paper2Poster). This skill is suitable for paper dissemination, conference preparation, creating explorable academic homepages, generating video abstracts, or producing printable posters from LaTeX or PDF source.
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 evidence-discovery and validation workflows for drug repurposing studies by integrating disease mechanisms, drug-target logic, expression reversal, real-world evidence, and validation routes into a closed-loop study blueprint.
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。
Designs studies for predicting treatment response or resistance in biomedical and clinical research. Always use this skill when the user needs a treatment-response or resistance prediction study blueprint rather than a prognostic biomarker protocol, diagnostic test design, causal treatment-effect estimation, or a completed manuscript. Focus on responder definition, treatment context, baseline comparability, feature integration strategy, model development logic, validation architecture, and interpretation boundaries. Do not invent response rates, cohort size, assay readiness, regimen uniformity, literature support, or validation access.
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。
Designs discovery, modeling, and validation workflows for prognostic biomarkers in biomedical and clinical research. Always use this skill when the user needs a prognostic biomarker study blueprint rather than a diagnostic test protocol, predictive biomarker design, treatment recommendation, or a completed manuscript. Focus on endpoint family, follow-up horizon, time scale, candidate marker strategy, model-building logic, risk stratification framework, and internal/external validation requirements. Do not invent cohort size, event rate, assay readiness, literature support, or validation access.
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。
Optimize Python code for reduced memory usage and improved memory efficiency. Use when asked to reduce memory footprint, fix memory leaks, optimize data structures for memory, handle large datasets efficiently, or diagnose memory issues. Covers object sizing, generator patterns, efficient data structures, and memory profiling strategies.
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。
Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.
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。
Reference for COBOL COMP-3 (packed decimal / BCD) numeric storage -- layout on disk, declaring it in the FD, and pitfalls when carrying the decoded value through working storage and into later arithmetic. Useful when an input record holds a balance, rate, or carry-forward as packed decimal rather than a printable digit string.
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。
dontbesilent AI 写作特征识别。扫描文案中的 AI 生成痕迹，输出检测报告。默认只诊断不改。 触发方式：/dbs-ai-check、/AI检测、「帮我看看有没有 AI 味」「检测一下 AI 特征」 AI writing fingerprint detection. Scans copy for AI-generated patterns and outputs a diagnostic report. Diagnosis only by default. Trigger: /dbs-ai-check, "check for AI writing", "does this sound like AI"
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。
Turn an approved measurement charter, ICPs, and buyer jobs into a budget-aware prompt coverage blueprint across proximity bands, aided status, information acts, journey states, roles, locales, evidence grades, partitions, and measurement lanes. Use before prompt wording to define required, optional, and prohibited canonical intent cells.
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。
Read-only backlog planning for Azure DevOps, GitHub, and Jira. Use to discover, triage, sprint-plan, or resume without mutating a tracker.
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。
Set up player input in Unreal Engine 5 with Enhanced Input: Input Actions, Input Mapping Contexts, modifiers and triggers, adding the mapping context, and binding actions by ETriggerEvent. Use when wiring movement/look/jump input, creating IA_/IMC_ assets, binding in C++ or Blueprints, or when the user mentions Enhanced Input, Input Mapping Context, Input Action, IA_/IMC_, or ETriggerEvent.
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 Unreal Engine 5 C++ gameplay code: the UCLASS/UPROPERTY/UFUNCTION reflection macros, the Gameplay Framework (GameMode, Pawn, Character, PlayerController, Actor components), and the module Build.cs. Use when writing or debugging UE C++, deriving from AActor/ACharacter/ AGameModeBase, exposing properties to the editor or Blueprints, or when the user mentions Unreal C++, UCLASS, GENERATED_BODY, GameMode, ACharacter, or .Build.cs.
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。