「feed」の検索結果

Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse 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。

Good-faith adversarial scrutiny of an idea or plan. Spawns critical skeptics across relevant lenses, pairs them with an advocate defending the idea, and synthesizes the exchange into a report. Produces feedback only — no code, no tickets, no artifacts.

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。

Analysis of Competing Hypotheses. Operationalizes Richards Heuer's CIA-tradition technique for systematically narrowing among multiple hypotheses against evidence. Builds an explicit hypothesis-vs-evidence matrix and focuses on disconfirmation rather than confirmation — the central insight: hypotheses cannot be proven, only disconfirmed; the surviving hypothesis is the one with the least disconfirming evidence. Spawns parallel hypothesizers (in isolation, across hypothesis-generation angles) and parallel evidence-gatherers (across evidence classes), then synthesizes into a matrix, diagnosticity analysis, sensitivity analysis, and falsification milestones. Produces feedback only — no code, no tickets, no artifacts.

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。

Prospective failure imagination for a plan, decision, or running system. Operates in two modes — **plan mode** (a plan has not yet been committed to; imagine its catastrophic failure broadly) and **scenario mode** (a specific catastrophic scenario is posed against an existing system; investigate causes against the actual code and architecture). Spawns parallel pre-mortemers in isolation across three categories of lens: standard failure classes (technical, operational, estimation, scope, adoption, dependency, team, incentive, detection, reversibility, adversarial), 0-3 ad-hoc target-specific lenses the orchestrator names when warranted, and a first-principles lens that always runs to catch what the prescribed taxonomy misses. Synthesizes into a prioritized risk register with early-warning signals. Produces feedback only — no code, no tickets, no artifacts.

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。

Good-faith divergent brainstorming for achieving a goal. Validates assumptions, then spawns brainstormers running different techniques (first-principles, working-backwards, lateral, analogical, constraints-shift, etc.) in isolation, and synthesizes the pool into a report of standouts, reasonable ideas, and hybrid combinations. Produces feedback only — no code, no tickets, no artifacts.

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。

Abductive reasoning about causes. Takes a phenomenon, separates observations from interpretations, then spawns diagnosticians applying different reasoning lenses (technical, human-factors, process, incentive-structure, environmental, temporal, measurement-artifact, statistical) in isolation. Orchestrator evaluates candidate causes for fit-against-evidence, calibrates confidence honestly, and reports leading candidate(s) with distinguishing evidence needed. Produces feedback only — no code, no tickets, no artifacts.

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。

Problem redefinition before problem solving. Takes a stated problem, extracts its premises, then spawns reframers applying different lenses (problem-vs-symptom, scope-shift, stakeholder-shift, level-of-abstraction, time-horizon, inversion, category-shift, constraints-shift) in isolation, and synthesizes the alternatives into a report with an orchestrator recommendation. Produces feedback only — no code, no tickets, no artifacts.

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。

Retrospective learning from a completed experience. Takes a project, incident, decision that played out, or time period; gathers ground truth (observations) separately from recollections; spawns reflectors applying different lenses (what-worked-vs-got-lucky, what-didn't, what-surprised, system-rewards-vs-intent, decisions-that-aged, what-to-tell-past-self, patterns-that-recur) in isolation; synthesizes into updated mental models as first-class output. Produces feedback only — no code, no tickets, no artifacts.

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。

Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.

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。

When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.

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。

Try to break a piece of UI by feeding it worst-case data — long names, unbreakable emails, one-letter names, missing fields, huge counts, zero items, long labels, non-Latin text, emoji, extreme numbers — then render it behind a "Demo data / Worst case" toggle and report everything that broke, with the fix for each. Use when the user asks to stress-test, break, or find edge cases in a component or screen, or to "try the worst case". For visual design critique use emil-design-eng; for motion use review-animations.

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。

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

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。

Non-interactive content-production toolkit: mine quotable moments from podcast RSS feeds and meeting notes, discover clip-worthy moments in video transcripts, repurpose long-form source into platform-native drafts (X, LinkedIn, YouTube Shorts, newsletter), and batch-score/gate those drafts before publish. Use when asked to "mine quotes from this podcast", "find clips in this video", "repurpose this into a thread / LinkedIn post / Short", "turn this transcript into posts", "extract viral moments", or "gate this batch of drafts". Runs Python scripts end to end. For interactive expert-panel scoring of a single artifact see content-ops.

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 the user asks to measure command execution time or optimize a feedback loop. Records explicit measurements and recommends faster alternatives such as unit tests versus integration tests. It is opt-in; it does not run on every command.

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。

Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.

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。

Patterns and practices that dramatically accelerate development velocity. Covers parallel execution, automation, feedback loops, workflow optimization, and anti-pattern avoidance. Use when starting projects, planning sprints, optimizing workflows, or onboarding developers.

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。

Validate a business idea using the minimalist entrepreneur framework before building anything. Use to test if an idea is worth pursuing through manual validation and customer feedback.

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。

Analyze meeting transcripts to identify communication patterns, behavioral insights, and actionable feedback for improving communication and leadership effectiveness.

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。

Address GitHub PR review comments and issue feedback using the gh CLI. Fetch all comments, summarize review threads, and apply fixes with explicit user approval.

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。

Collaborative writing partner that assists with research, outlining, drafting, citations, and iterative feedback. Helps writers create high-quality content while maintaining their unique voice and style.

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。

Continuous learning framework — learn from work, organize knowledge, build feedback loops. Use when: recording lessons, organizing knowledge, or setting up learning systems that persist across sessions.

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。

Applies local lessons to every use of the Orca CLI (orca-ide, orca-dev). Use alongside the upstream orca-cli skill whenever the Orca CLI is needed, including before creating a branch worktree or asking the user for feedback on a change before committing while running inside Orca.

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。

Used by the Reviewer agent during Phase 9 (DesignVerify) and Phase 11 (Quality) to evaluate frontend code. Assesses visual hierarchy, spacing consistency, accessibility, and detects formulaic 'AI slop' design patterns, providing actionable feedback to the Developer.

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。

阿拉丁·AI短剧数字人肖像权合规工坊把「AI 演员/数字人/换脸/声音克隆做完却因肖像权没授权被投诉下架、数字人授权到期还在用、授权只买了一个平台却全网发、AI 形象神似明星惹官司、被举报时拿不出授权链举证」升级成一条纯本地零依赖的上架前置授权链自查工具链：多源导入(drama-cast 角色卡 _cast.json 双契约兼容/人物资产类型声明 assets.json/授权凭证登记 CSV 或 JSON/drama-publish 发行计划 _publish_plan.json 抽平台)→人物资产五分类(AI原创 ai_original/真人出演 real_actor/第三方数字人 digital_human/换脸 face_swap/声音克隆 voice_clone)逐类判定所需授权→10 条确定性授权链规则(A1缺授权凭证 A2要素缺失 A3已过期 A4即将到期 A5平台越界 A6用途越界 A7撞脸公众人物 A8声音克隆缺授权 A9转授瑕疵 A10平台报备缺失)→门禁评分(P0=25/P1=8/P2=3 扣分，100分制 A-D 档，READY可提审/REVIEW建议整改/BLOCK禁止上架)→自包含 HTML 授权链看板(门禁灯+逐条命中+整改建议)+Markdown 整改清单(可直接交制片执行)+feedback 回灌契约(缺证角色回灌 drama-cast 补授权、越界平台回灌 drama-publish 调发行、续签观察名单、报备提醒)。与 aladin-drama 系列闭环衔接(cast/publish 进，整改反馈回灌 cast 补授权、publish 调发行矩阵)。区别于内容合规工具只扫违禁词与画面红线：本款专管「人」的授权链(肖像权/声音权/数字人许可/换脸源授权)，确定性规则可复算、命中带人物名与整改方向、纯本地零依赖零API、授权信息不出本机(法务资产敏感)。触发词：短剧肖像权、数字人授权、换脸授权、声音克隆授权、AI演员合规、肖像授权到期、授权链自查、撞脸明星、数字人合规、AI形象报备、肖像权侵权、portrait rights、digital human license、face swap consent、voice clone authorization、AI短剧、阿拉丁短剧、短剧创作闭环。

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。