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370 件 ・ 関連度順

概要と使いどころ

Applies Geoffrey Moore's chasm-crossing strategy for B2B tech products moving from visionary early adopters to pragmatist mainstream. Use when a product has early traction but stalls before mainstream adoption, when planning a beachhead/niche strategy, when designing whole-product offerings, when positioning against established competitors, or when scaling from innovator usage to industry standard. Triggers include 'stuck between early adopters and mainstream', 'we need a beachhead', 'pragmatist customers won't buy', 'how do we go from 10 to 1000 customers'. NOT for PLG/freemium SaaS (Slack, Notion, Cursor), pure consumer apps, two-sided marketplaces, or AI-native products with bottoms-up viral adoption - their dynamics break the visionary-to-pragmatist sequence.

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。

getagentseal/founder-playbook7512026年10月7日 更新

Core idioms, style guides, and best practices for writing idiomatic Go code. Use when writing Go code following official style guides and idiomatic 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。

HoangNguyen0403/agent-skills-standard5752026年10月12日 更新

Dart code quality conventions: naming, const/final/var hierarchy, single quotes, trailing commas, collection idioms, tear-offs, and import organization. Use only for Dart style-focused changes or reviews; never activate for configuration-only lint setup, unrelated feature work, or widget tests.

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。

HoangNguyen0403/agent-skills-standard5752026年10月12日 更新

Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.

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。

vibeeval/vibecosystem5332026年8月9日 更新

Hierarchical memory organization for multi-session context retention. Wings (projects) > Rooms (domains) > Drawers (decisions). Semantic search across all memories with zero cloud dependency.

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。

vibeeval/vibecosystem5332026年8月9日 更新

火山引擎市场洞察助手。帮助用户获取品牌在各大社交平台和媒体渠道上的公开内容数据,通过 AI 筛选出真正值得关注的信息,并发现潜在商机线索。当用户提到以下任何场景时使用此技能:想知道最近网上有没有人在讨论自己的品牌或产品、想看看竞品最近在社交媒体上有什么动态、想了解某个话题或事件在网上的讨论热度和趋势、想定期获取和自己业务相关的行业资讯和热点内容、想把筛选后的内容数据接入自己的系统做进一步分析、想查看自己账号下有哪些监测任务或拉取某个任务的数据、想了解最新的中东局势关税贸易战AI大模型等热点话题的网络讨论、想查询商机线索信息获取 ACOR 评估竞争分析公司画像、提到火山引擎市场洞察 Volcengine Insight PullPost ListCustomSubsTask QueryClueInfo。即使用户没有直接提到"市场洞察",只要涉及品牌声量追踪、行业动态了解、热点事件网络讨论、公开内容数据获取、商机查询与分析等需求,都应触发此技能。

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。

bytedance/agentkit-samples4712026年10月12日 更新

Use when you need to review, improve, or troubleshoot a Maven pom.xml file — including dependency management with BOMs, plugin configuration, version centralization, multi-module project structure, build profiles, or any situation where you want to align your Maven setup with industry best practices. This should trigger for requests such as Review pom.xml to improve it; Apply Maven best practices to pom.xml; Improve Maven POM configuration; Review Maven dependency management and plugin configuration; Modernize Maven build conventions for a Java project. Part of Plinth Toolkit

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。

jabrena/plinth4482026年10月13日 更新

Use when you need to refactor Java code to adopt modern Java features (Java 8+) — including migrating anonymous classes to lambdas, replacing Iterator loops with Stream API, adopting Optional for null safety, switching from legacy Date/Calendar to java.time, using collection factory methods, applying text blocks, var inference, or leveraging Java 25 features like flexible constructor bodies and module import declarations. This should trigger for requests such as Review Java code for modern Java development; Apply best practices for modern Java development in Java code; Modernize Java code with records pattern matching or switch expressions; Replace legacy idioms with modern Java features; Adopt Java 8+ language features safely. Part of Plinth Toolkit

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。

jabrena/plinth4482026年10月13日 更新

Annotate bacterial and archaeal genomes and plasmids with Bakta's Prodigal/HMM/diamond pipeline. Identifies CDS, ncRNA, tRNA, rRNA, tmRNA, sORFs, CRISPR arrays, oriC/oriV/oriT, and gaps against a curated UniRef-derived database. Produces NCBI-compatible GFF3, GenBank, EMBL, JSON, FASTA, TSV, and a circular genome plot. Use Prokka for legacy pipelines or non-bacterial kingdoms; PGAP for NCBI GenBank submission.

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。

jaechang-hits/SciAgent-Skills3782026年9月29日 更新

Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface: 6 tools with --full (adds check_action); 13 tools with AR_EXTRAS=1 --full. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.

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。

Goldentrii/AgentRecall-X3722026年10月14日 更新

Extract structured data from construction PDFs. Convert specifications, BOMs, schedules, and reports from PDF to Excel/CSV/JSON. Use OCR for scanned documents and pdfplumber for native PDFs.

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。

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3492026年8月22日 更新

Manages direct communication to affected data subjects following a personal data breach under GDPR Article 34 when the breach is likely to result in a high risk to their rights and freedoms. Covers the high risk threshold, required notification content per Art. 34(2), exemptions under Art. 34(3), and breach notification letter templates for five scenarios. Keywords: data subject notification, Article 34, high risk, breach communication, GDPR.

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。

mukul975/Privacy-Data-Protection-Skills3032026年3月17日 更新

Liminal space and Backrooms art direction for Blender with empty transitional architecture, wrong familiarity, and endless repetition.

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。

arjun988/blender-skills2962026年7月11日 更新

Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.

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。

K-Dense-AI/mimeo2832026年9月3日 更新

Scan code, dependencies, containers, IaC and SBOMs with Snyk via its first-party MCP server: authenticate, trust a folder, run the right scanner, read the findings, fix and re-scan. Includes package-health checks before adding a dependency.

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。

NousResearch/hermes-official-plugins2532026年10月13日 更新

Analyze formal verification artifacts (Isabelle, Coq, Dafny, etc.) and produce structured reports identifying the precise boundary between verified, assumed, and unverified components. Use when assessing verification coverage, understanding trust boundaries, auditing formal proofs, or documenting verification scope. Reports explicitly list verified code, assumptions, axioms, trusted computing base, and unverified components. Conservative and explicit about verification status without attempting to repair or mask gaps.

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。

ArabelaTso/Skills-4-SE2532026年8月21日 更新

Detects security vulnerabilities by matching code against known vulnerability patterns, insecure coding idioms, and CVE-style patterns. Explains why patterns are risky and under what conditions they are exploitable. Use when analyzing code for security issues, reviewing for common vulnerabilities, or assessing exploitability of suspicious code 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。

ArabelaTso/Skills-4-SE2532026年8月21日 更新

Analyze vulnerable code to identify underlying root causes such as violated assumptions, incorrect invariants, missing validation checks, or unsafe component interactions. Use when investigating security vulnerabilities, CVEs, exploit code, or security audit findings. Infers why the vulnerability exists beyond surface symptoms, identifies systemic issues, and explains the chain of failures that enable exploitation.

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。

ArabelaTso/Skills-4-SE2532026年8月21日 更新

Converts pseudocode descriptions and algorithm specifications into complete, executable Java code. Use this skill when you need to implement algorithms from pseudocode, translate algorithm descriptions to Java, generate Java code from specifications, convert textbook algorithms to working code, or create executable implementations from high-level descriptions. Preserves logic and control flow while handling Java idioms, data structures, and includes test cases for verification.

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。

ArabelaTso/Skills-4-SE2532026年8月21日 更新

Lint and typecheck debt paydown: clear pre-existing repo-wide lint/type violations and suppressions (@ts-ignore, # type: ignore) one rule per wave, fixing causes not symptoms. Runs on green main. For diff-scoped quality use absolute-simplify. Triggers on "absolute debt", "fix our lint warnings", "clear the type errors", "get to strict mode", "burn down suppressions".

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。

maddhruv/absolute2192026年7月6日 更新

Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step sequence, wedges, double tops and bottoms, triangles, head and shoulders, climaxes, measured moves, support and resistance

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。

agentii-ai/agentii-investment-intelligence2072026年9月29日 更新

Think and work like an expert MEMS Engineer. Use when a task calls for MEMS Engineer judgment. Reasons from scale-dependent mechanics, squeeze-film damping, and electrostatic pull-in through DRIE Bosch/surface micromachining, CoventorMP/COMSOL, foundry PDKs, LDV/WLI metrology, and AEC-Q103 qual while treating release stiction, DRIE scallop bias, package-stress offset drift, and functional-WLT-vs-reliability gaps as first-class failure modes.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Mathematical Physicist. Use when a task calls for Mathematical Physicist judgment. Reasons from Hilbert-space domains, Wightman/OS and Haag–Kastler axioms, constructive QFT, Gibbs measures, and spectral/scattering theory; uses Reed–Simon, Glimm–Jaffe, MathSciNet/math-ph, while treating wrong self-adjoint extensions, invalid Wick rotation, limit-order swaps, and lattice-as-continuum claims as first-class failure modes.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Knowledge Representation Researcher. Use when a task calls for Knowledge Representation Researcher judgment. Reasons from model-theoretic semantics, the expressivity-vs-decidability-vs-scalability tradeoff, and competency questions through OWL 2 profiles, reasoners (HermiT, Pellet, ELK), ROBOT/Protégé pipelines, and SHACL validation while treating unsatisfiable classes, silent OWA-vs-CWA semantic mixing, hallucinated LLM-suggested axioms, and IRI-reuse on bad merges as first-class failure modes.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新