[omh] Engineering leadership over roadmap and risk: roadmap, PM, technical tradeoffs, risk, delivery, release, and follow-up operating cadence. Use when the user says: cto-loop, cto loop, cto, cto pm, pm dev qa security ops, roadmap technical tradeoffs, technical tradeoff, delivery risk.
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。
rlaope/oh-my-hermes☆ 3,3262026年10月12日 更新
Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously, and synthesize a final verdict. Based on Karpathy's LLM Council methodology. MANDATORY TRIGGERS: 'council this', 'run the council', 'war room this', 'pressure-test this', 'stress-test this', 'debate this'. STRONG TRIGGERS (use when combined with a real decision or tradeoff): 'should I X or Y', 'which option', 'what would you do', 'is this the right move', 'validate this', 'get multiple perspectives', 'I can't decide', 'I'm torn between'. Do NOT trigger on simple yes/no questions, factual lookups, or casual 'should I' without a meaningful tradeoff (e.g. 'should I use markdown' is not a council question). DO trigger when the user presents a genuine decision with stakes, multiple options, and context that suggests they want it pressure-tested from multiple angles.
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。
aiwithremy/claude-skills-llm-council☆ 2,4602026年4月26日 更新
Makes agent reasoning visible, surfaces tradeoffs, and fades help so humans build judgment. Use when reviewing or learning from agent-written code.
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。
athola/claude-night-market☆ 3412026年10月10日 更新
Contract for the project decision journal (tradeoffs and lessons-learned logs). Use when recording a decision, tradeoff, or lesson, or building a consumer hook.
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。
athola/claude-night-market☆ 3412026年10月10日 更新
独立开发者与微型 SaaS — 单人或极小团队 (≤3 人) 构建可持续订阅收入的软件产品商业, 有别于自由职业/咨询、企业级 SaaS 和开源维护: (a) 产品发现与验证 (自己的痒 vs 市场优先 Nugent/Walling; 着陆页冒烟测试; 先接 Stripe 再写代码; JTBD 访谈适配独立开发者场景; Reddit/HN/X/社区痛点挖掘; Mom Test 验证框架; 公开构建作为验证机制); (b) 独立开发者技术架构 (无聊技术论 McKinley; 单体优先; serverless vs VPS 在 ≤$100/月预算下的取舍; Rails/Django/Laravel/Next.js 等框架的出货速度选型; 托管服务优先于自建; Supabase/PlanetScale/Neon 数据库即服务; Clerk/Auth0 认证即服务; Stripe/Paddle/LemonSqueezy 支付; Vercel/Fly.io/Railway 部署; AI 辅助编码 Cursor/Copilot 作为力量倍增器); (c) 无营销团队的分发与增长 (SEO 作为微型 SaaS 护城河; Product Hunt 发布; AppSumo 终身授权利弊; 冷邮件; Twitter/X 公开构建; IndieHackers 社区分发; 集成市场 Shopify/WordPress/Zapier/Slack 应用目录; 联盟计划; 一人内容营销); (d) 定价与变现 (SaaS 定价心理学; freemium vs 免费试用 vs 纯付费; 按席位 vs 按用量 vs 固定费率; 年付折扣; 老用户保价; 微型 SaaS 流失率控制; MRR/ARR/LTV/CAC 在微型规模的含义; $10K MRR 里程碑心理学); (e) 独立创始人心智模型与生活设计 (default alive vs default dead Graham; 拉面盈利 Levels; 生活方式生意 vs 增长生意的光谱; 独立开发者倦怠预防; 时间管理与上下文切换成本; 地理套利与远程优先; 一次构建反复销售的资产思维; 社区作为支持网络 IndieHackers/WIP/MicroConf); (f) 法务与运营基础 (公司注册地选择 LLC/Ltd/GmbH 税效; Stripe Atlas vs Firstbase vs 本地律师; 服务条款与隐私政策; GDPR/CCPA 低成本合规; 知识产权基础; 首次雇人的承包商 vs 员工选择; 独立开发者会计 SaaS — Xero/QuickBooks; 多辖区税务义务)。中国独立开发者生态: 出海作为主导策略 (从中国构建面向全球市场的产品以避开国内竞争/监管); 即刻/V2EX/少数派作为社区枢纽; 微信小程序作为替代分发; 小报童/爱发电作为中文市场变现; 人民币定价心理学; 支付宝/微信支付集成; ICP 备案要求; 中国区 App Store 审核差异; 独立开发者周刊。诚实处理: 生存偏差 (每一个 Pieter Levels 背后是数千个从未达到 $1K MRR 的人), AI 对微型 SaaS 生态位的颠覆 (wrapper 产品脆弱), 独自构建的孤独与心理健康成本, 公开构建的表演性质 vs 真正透明, AppSumo 终身授权上瘾毁坏单位经济, 样板代码销售的伦理边界。不含: 企业级 SaaS (不同 GTM/销售/融资模型), 不含: 自由职业/咨询 (用时间换钱非建资产), 不含: 开源维护 (不同可持续性模型), 不含: 风投支持的创业 (不同增长期望), 不含: 无代码/低代码平台构建 (相邻但不同受众), 不含: 内容创作作为主业。 (Independent Developer and Micro-SaaS — the craft of single-person or tiny-team (≤3 people) software product businesses that generate sustainable recurring revenue without venture capital, distinct from freelancing/consulting, enterprise SaaS, and open-source maintainership: (a) product discovery and validation (scratching your own itch vs market-first Nugent/Walling; landing page smoke tests; Stripe checkout before code; Jobs-to-Be-Done interview adapted to solo context; Reddit/HN/X/community pain-point mining; idea validation frameworks Fitzpatrick Mom Test; build-in-public as validation mechanism); (b) technical architecture for solo operators (boring technology thesis Mckinley; monolith-first; serverless vs VPS tradeoffs for ≤$100/mo infra; framework selection for shipping speed — Rails/Django/Laravel/Next.js/Remix/SvelteKit; managed services over self-hosted whenever possible; database-as-a-service Supabase/PlanetScale/Neon/Turso; auth-as-a-service Clerk/Auth0/Supabase Auth; payment integration Stripe/Paddle/LemonSqueezy; deployment Vercel/Fly.io/Railway/Render; monorepo vs polyrepo for solo; AI-assisted coding Cursor/Copilot as force multiplier); (c) distribution and growth without a marketing team (SEO as moat for micro-SaaS Ahrefs-style content marketing on 1-person budget; Product Hunt launches; AppSumo lifetime deals tradeoffs; cold email outreach; Twitter/X building in public; IndieHackers community distribution; integration marketplaces Shopify/WordPress/Zapier/Slack app directories as channels; affiliate programs; content marketing at scale-of-one); (d) pricing and monetization (SaaS pricing psychology Patel/Campbell; freemium vs free trial vs paid-only; per-seat vs usage-based vs flat-rate; annual discount strategies; grandfathering existing customers; churn reduction for micro-SaaS — Baremetrics/ProfitWell/ChartMogul analytics; MRR/ARR/LTV/CAC at micro scale; the $10K MRR milestone psychology); (e) solo founder mental model and lifestyle design (default alive vs default dead Graham; ramen profitability Levels; lifestyle business vs growth business spectrum; burnout prevention for solo operators — no team to delegate to; time management and context-switching costs; geographic arbitrage and remote-first; the 'build once sell twice' asset mindset; community as support network IndieHackers/WIP/MicroConf); (f) legal and operational basics (incorporation LLC/Ltd/Gm
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。
swaylq/master-skill☆ 1492026年9月6日 更新
Brainstorms and debates approaches, then drives toward an actionable decision. Use whenever someone needs a thinking partner for a decision they're facing: 'discuss', 'debate', 'brainstorm', 'weigh options', 'tradeoffs', 'should I do X or Y', 'help me decide', 'I'm torn between', 'sanity check my thinking', or 'what do you think about'. The user must be asking for help reasoning through a choice — not asking to build, fix, evaluate, plan, or modify something (even if the topic involves this skill itself). Picks the right decision lens, surfaces tradeoffs and blind spots, pushes back when reasoning is genuinely weak, and never implements.
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。
avibebuilder/claude-prime☆ 1202026年5月17日 更新
Use for tradeoff analysis, or when the user must pick between concrete options: "A or B?", "which library should we use?", "build vs buy", "compare these approaches". Scores options on weighted criteria, tests sensitivity and reversibility. Skip for open ideation or single-option reviews.
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。
ysskrishna/ai-agent-skills☆ 112026年10月8日 更新
Name what was prioritized, what was sacrificed, and whether the tradeoff was right. Every design decision trades something. Use when evaluating design decisions, defending choices, or helping teams understand what they're giving up.
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。
Dragoon0x/taste-skills☆ 62026年2月27日 更新
Next.js 16以降の開発で、起動や変更反映の遅さ、Turbopackとwebpackの使い分けを確認します。キャッシュやproxy.tsの命名も扱うスキルです。
- 開発サーバーの起動の遅さを調べたいとき
- コード変更の反映が遅いときの確認
- Turbopackとwebpackの選択
affaan-m/ECC☆ 27.8万2026年10月12日 更新
正解が一つに定まらない判断を、長期的な影響、前提への疑問、実行の現実性、失敗リスクの四つの視点で検討し、反対意見も見える形で推奨案をまとめるスキル。
- 今すぐ公開するか改善を待つか決めたいとき
- 段階的展開と一斉展開を比較したいとき
- 範囲の縮小と長期的な狙いを検討したいとき
affaan-m/ECC☆ 27.8万2026年10月12日 更新
OpenDesign's feature business case for the plugin marketplace: the user pain, options, tradeoffs, and the measure of success. Built as a decision-grade product management deck for PM, eng, design, leadership.
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。
nexu-io/open-design☆ 10.1万2026年10月12日 更新
Copilot left 14 review comments on your PR — half are nits. Hours of fix → reply → resolve → re-request, and each round lands MORE comments. This skill runs loop engineering: auto-triggers Copilot Code Review via GraphQL (no @copilot mention), triages every open thread (Copilot, humans, advanced-security) with a fix / decline / escalate rubric, dispatches parallel fix sub-agents that obey the repo build/test/lint conventions, commits per iteration, replies+resolves citing the pushed SHA, then re-triggers until HEAD is reviewed with zero threads awaiting the agent's reply (remaining open threads are explicit hand-offs to the human — escalated declines, design tradeoffs). You merge a clean PR; the bot runs it. Trigger phrases: "address copilot comments", "run a copilot review loop", "fix this PR", "iterate on copilot feedback". Repo-agnostic, gh CLI + PowerShell. Full autopilot needs repo Triage/Write; external PR authors get single-iteration mode plus manual re-trigger (UI 🔄 or substantive-commit push).
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。
github/awesome-copilot☆ 4万2026年10月9日 更新
Choose the right Zoom building surface for a use case and explain the tradeoffs clearly. Use when deciding between REST API, Webhooks, WebSockets, Meeting SDK, Video SDK, Zoom Apps SDK, Phone, Contact Center, or MCP for a specific product idea or integration goal.
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。
anthropics/knowledge-work-plugins☆ 2.9万2026年10月11日 更新
Apply the Fable-derived 10-stage OBSERVE, OBSERVE, LISTEN, THINK, CONNECT, CONNECT, FEEL, ACCEPT, CREATE, GROW loop to consequential or ambiguous reasoning and decisions. Use for think this through, deep think, architecture review, postmortem, tradeoff analysis, or challenges to assumptions. This is a reasoning review, not a deterministic vault health check or repair workflow.
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。
AgriciDaniel/claude-obsidian☆ 1.5万2026年9月11日 更新
Required before calling image_generate. Create and edit images from a prompt — generate an image, make a picture / logo / illustration / icon / banner / poster / thumbnail / hero image / mockup / product shot / social graphic, or edit / restyle / combine existing images from reference images. Uses OpenAI gpt-image-2 through the Hive image service, billed to the user's Hive credits like an LLM call (no API key needed). Teaches the exact call shape, the quality/cost tradeoff (quality="low" is the default and cheapest), reference-image editing, how to show the result to the user with attach_file, and the failure modes (out of credits, model unavailable, moderation).
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。
aden-hive/hive☆ 1.1万2026年10月12日 更新
Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.
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。
openai/codex-security☆ 1.1万2026年10月12日 更新
Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or investment tradeoffs.
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。
AgriciDaniel/claude-ads☆ 9,9102026年10月8日 更新
Decision needed + recommendation + evidence + tradeoffs, 把复杂材料压成可拍板的一页
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。
nexu-io/html-anything☆ 9,0942026年9月15日 更新
Analyze product or business data to support a decision or recommendation. Use when a decision depends on metric-backed evidence, such as choosing a direction, prioritizing an opportunity, evaluating a change, segmenting users, sizing tradeoffs, or deciding what to do next.
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。
openai/plugins☆ 7,4092026年10月8日 更新
Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.
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。
openai/plugins☆ 7,4092026年10月8日 更新
Structure a spoken PM product-sense answer with assumptions, segmentation, pain-point prioritization, and MVP tradeoffs. Use when practicing design, improve, or build-next interview questions.
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。
deanpeters/Product-Manager-Skills☆ 7,2752026年9月2日 更新
Use when a question, decision, plan, tradeoff, or claim needs a rigorous verdict and one perspective is not enough. Spawns a panel of 3 to 5 subagent jurors that form independent blind opinions, deliberate anonymously under an anti-anchoring and anti-sycophancy protocol, and return one committed verdict with confidence, preserved dissent, and a concrete next action. Domain-agnostic across engineering, architecture, data, product, hiring, strategy, vendor choice, build-vs-buy, and research design. Trigger phrases include "convene a jury", "have agents debate and decide", "get a panel to decide", "multi-agent decision", "stress-test this and decide", "monte um juri", "tribunal de agentes", "painel para decidir". Do NOT use to only critique without deciding (use the-fool for that), to build a plan or write the solution itself, or for simple factual lookups.
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。
tech-leads-club/agent-skills☆ 7,0512026年10月9日 更新
A structured workflow for co-authoring high-signal docs (PRD, RFC, design docs, proposals, decision records). Use when the user needs to turn messy context into a readable artifact with clear goals, tradeoffs, and next steps. Emphasizes context capture, outline-first drafting, and context-free reader testing to catch blind spots.
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。
shareAI-lab/Kode-CLI☆ 5,2352026年10月9日 更新
Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).
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。
NVIDIA/skills☆ 3,5682026年10月10日 更新