「rsa」の検索結果

Use when the user wants to develop, run, preview, save, deploy, or roll back a CloudBase Web app in this conversation as a Lovable/Codex-Sites-like vibe- coding session — i.e. any request that maps to "spin up a React+Vite project, see it live in the browser, iterate, save versions, deploy". Activate ONLY for browser-rendered Web projects based on the CloudBase official React (or Vue) + Vite template. Do NOT activate for: WeChat/Alipay mini-program, React Native / Flutter / Electron, pure cloud functions / CloudRun backends, or Next.js / Nuxt / Astro / Remix / SvelteKit (those frameworks are explicitly out of scope).

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 new reusable skills from conversation context

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。

Restore a prior business-state snapshot saved by /money-save, so you can continue from exactly where the last session left off. Loads the most recent snapshot for the current project (auto-detected from the working directory), or a specific one by index. Use when starting a new Claude Code conversation and the user wants to continue prior work. Triggered by: 'continue from last time', 'where did we leave off', 'pick up from before', 'resume', '接着上次', '续上', '之前的结论', '上次诊断到哪了'.

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。

Codify a successful workflow from the current conversation into a permanent project-local skill. After you discover (e.g.) a cold-email sequence that converts, an ad-creative format that beats baseline, or a content-pipeline cadence that compounds — /money-skillify writes it as a SKILL.md under the project's local skills directory so future sessions can re-invoke it without re-discovery. Use when the user says: 'this worked, save it', 'codify this', 'turn this into a skill', '把这个固化下来', '存成 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。

Search a Claude Code session transcript for a string or regex pattern and show every matching message with surrounding context. Reads /api/sessions/:id/transcript and resolves sessions via /api/sessions?limit= from the Agent Monitor dashboard. Use when hunting for a specific message, prompt, tool call, or error inside a session's conversation.

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。

Versatile JavaScript animation engine for DOM, CSS, SVG, and JavaScript objects. Use when creating timeline-based animations, stagger effects, SVG morphing, keyframe sequences, or complex choreographed animations. Triggers on tasks involving Anime.js, timeline animations, staggered sequences, SVG path animations, morphing, or multi-step animation choreography. Alternative to GSAP for SVG-heavy animations and React-independent projects.

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 set up, optimize, or manage LinkedIn Ads. Also use when the user mentions "LinkedIn Ads," "LinkedIn Campaign Manager," "Sponsored Content," "Lead Gen Forms," "Sponsored Messaging," "Message Ads," "Conversation Ads," "Accelerate," "Classic ad set," "Audience Network," "objective-based pricing," "Insight Tag," "job title targeting," "company targeting," "Matched Audiences," or "B2B paid ads." For organic posts, use linkedin-posts.

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 set up, optimize, or manage Google Ads campaigns. Also use when the user mentions "Google Ads," "Google Search Ads," "PPC," "SEM," "PMF testing with ads," "test product-market fit," "Responsive Search Ads," "RSA," "Performance Max," "Quality Score," "keyword bidding," or "Google Display/YouTube ads." For paid mix, use paid-ads-strategy.

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 an Unreal Engine 5.8 project misses its frame rate or stutters: "optimize to 60 fps", "we run at 38 fps", CPU or GPU bound, game or render thread too long, hitches, traversal or shader stutter (PSO), GC spikes, camera-cut spikes, Lumen, Nanite, VSM, ray tracing, foliage, crowds or Niagara too expensive, async compute, stat unit, ProfileGPU, Unreal Insights, TraceQuery, snapshothitches, scalability and device profiles, dynamic resolution and TSR, streaming budgets, or proving a fix with before and after captures.

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 has finished building a mobile app, started Metro with `npm run dev`, and wants the running app monitored for runtime errors AND silent failures (empty lists, blank screens, swallowed network errors) and fixed autonomously. Accepts a free-text symptom (e.g., `/debug-app "todos not appearing on home screen"`) to drive persisted-log diagnostics — injects temporary console.log statements at data-path boundaries, reads the sanitized `.powernative/metro-logs/` log, and cleans up logs after the root cause is fixed. Supports port/platform filtering, configurable clean-cycle and timeout limits, and watch-only `--no-fix` mode. Otherwise polls with a durable byte cursor, fixes inline or routes appropriately, verifies each fix from new output, and exits after the configured clean checks (default 3). Foreground loop — blocks the conversation while running. Run only after the app is loaded.

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。

The Jobs-to-be-Done framework as applied product methodology. Job statements, struggling moments, hire and fire criteria, the difference between feature-thinking and job-thinking. Honest about where JTBD adds clarity (discovery, prioritization, positioning) and where it becomes performative ritual (job-statement workshops that do not drive decisions, persona-theater disguised as JTBD). Triggers on jobs-to-be-done, JTBD, job statements, struggling moments, hire criteria, fire criteria, switch triggers, functional emotional social jobs, outcome-driven innovation. Also triggers when a team is over-relying on feature-request lists or persona archetypes that do not drive product decisions, when a positioning conversation needs the framing JTBD provides, or when discovery is producing outputs that do not connect to product strategy.

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。

Enter talk mode — conversation and research, no repo changes. ONLY invoke when the user explicitly types `/talk` or `$talk`; never auto-select from a natural-language question or design discussion.

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 meeting notes or a transcript into sourced decisions, changes and next actions. Use after a customer conversation; review consequential record updates before saving.

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。

Multi-AI second opinion via OpenAI Codex CLI. Three modes: Review (pass/fail gate), Challenge (adversarial edge-case finder), Consult (freeform with session continuity). Read-only with streaming output and thinking traces. Cross-model analysis when review has already run.

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。

Pre-landing PR review with two-pass checklist. Pass 1 critical: SQL safety, race conditions, LLM trust boundaries, enum completeness. Pass 2 informational: side effects, magic numbers, dead code, test gaps. Adversarial review auto-scaled by diff size. Scope drift detection.

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。

Fully automated ship workflow: pre-flight, merge base, run tests, coverage audit, pre-landing review, design review, adversarial review, version bump, CHANGELOG generation, TODOS.md update, bisectable commits, push and PR creation, auto-sync docs via document-release.

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。

Capture and catalog new ideas from conversations and research

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。

Adversarial verification for AI-generated legal content. Use when fact-checking legal documents, validating citations, detecting hallucinations, scoring document quality, or assessing distribution readiness.

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 "scan AI systems for security threats", "check for prompt injection vulnerabilities", "assess model security posture", "detect data poisoning risks", or "audit AI/ML pipeline security".

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。

Adversarial thinking partner that stress-tests plans, prepares board meetings, and surfaces blind spots. Use when you need plan validation, board prep, hard-decision frameworks, or pre/post-mortem failure 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。

Use when the user needs to design evaluation datasets, create test cases, stratify samples, generate adversarial examples, extract eval dimensions from traces/specs, or build a labeled evaluation set. Also use when the user mentions test data design, eval coverage, difficulty stratification, synthetic data generation for eval, or "how to create good evaluation data." Outputs datasets in OpenJudge-compatible format.

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 wants to test their LLM/agent application for safety and security vulnerabilities — jailbreaks, prompt injection, PII extraction, harmful content generation, or evaluator gaming. Also use when the user mentions security testing, adversarial testing, red teaming, safety evaluation, ASR (Attack Success Rate), or "is my app safe to deploy." Outputs ASR paired with over-refusal rate and an audit document.

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 design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.

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 one sentence of intent into tasteful, produced motion. Given a natural-language request like "make a good-looking animated landing page", "add a delightful like animation", or "make a silky release video", this skill classifies the intent, picks the most suitable recipes from the motion-anything library while honoring MOTION-SPEC.md (timing, easing, and the restraint budget), and produces the output. The universal entry point to motion-anything. Works on web pages, slides, app-showcase pages, and video.

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。