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Calculate and model paid-media CPA, CPL, CPC, CPM, ROAS, MER, break-even targets, contribution margin, LTV:CAC, impression-share opportunity, budgets, forecasts, and experiment economics. Use for PPC math, ad calculator, break-even analysis, ROAS calculator, CPA calculator, budget forecast, LTV CAC, or MER.

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Fix a bug using Scout → Diagnose → Fix → Review → Finalize. Use when the user pastes an error message, stack trace, or test failure, or says "fix this bug", "something's broken", "tests are failing", "I'm getting an error". Also accepts `--from-quality <report>` or `--from-test <report>` to fix exactly the findings/failures a report lists. Modes (pick one): --fast (trivial errors — lint, type, build — skip scout and review), --hard (mandatory review, no auto-approve).

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。

Fix a bug using Scout → Diagnose → Fix → Review → Finalize. Use when the user pastes an error message, stack trace, or test failure, or says "fix this bug", "something's broken", "tests are failing", "I'm getting an error". Also accepts `--from-quality <report>` or `--from-test <report>` to fix exactly the findings/failures a report lists. Modes (pick one): --fast (trivial errors — lint, type, build — skip scout and review), --hard (mandatory review, no auto-approve).

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 Agentforce run costs are climbing, you need to forecast scale, or you want to reduce tokens per conversation without hurting quality. Covers topic (now subagent) design impact on cost, prompt/template reuse, grounding size discipline, caching, and model-tier selection. Triggers: 'agentforce cost', 'tokens per conversation too high', 'reduce agentforce runs spend', 'forecast agentforce scale cost', 'einstein trust layer tokens'. NOT for capping spend per user with a budget gate and fallback — use agentforce/agent-rate-limit-strategy. NOT for org-wide model-tier and BYOLLM platform strategy — use architect/ai-platform-architecture.

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Use when designing or auditing Salesforce access control — deciding between Profiles, Permission Sets, and Permission Set Groups. Triggers: 'user can't see field', 'too many profiles', 'permission model', 'least privilege', 'profile migration', 'what stays on the profile', 'profile only settings', 'login hours permission set', 'layout assignment permission set', 'IsOwnedByProfile', 'profile retrieve empty'. NOT for sharing rules or record-level access — use admin/sharing-and-visibility for that.

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 designing or refactoring Salesforce access architecture around minimal profiles, permission sets, permission set groups, muting, and assignment governance. Triggers: 'profile sprawl', 'permission set strategy', 'PSG architecture', 'access bundle design', 'least privilege', 'how to slice permission sets', 'permission set naming convention', 'permission set license restriction', 'PSG status Outdated', 'permissionset-meta.xml'. NOT for PSG muting mechanics and recalculation order — use admin/permission-set-group-composition. NOT for record-sharing model design — use admin/sharing-and-visibility. NOT for time-boxing an assignment — use admin/permission-set-expiration.

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Designing Lookup vs Master-Detail vs Hierarchical vs External relationships: cascade delete, roll-up summaries, ownership, sharing implications, polymorphic lookups, junction objects, relationship depth limits. NOT for restricting which records a lookup can pick — use admin/lookup-filter-cross-object-patterns. NOT for a roll-up across a plain lookup — use data/roll-up-summary-alternatives.

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Dispatch an explicit, user-dictated set of edits that spans TWO OR MORE zones of the GDD — the master spec, systems, content types, and flows — in one ordered pass. Writes nothing itself: it resolves each delta to its (target, zone), orders them so a system change lands before the content or flow that depends on it, delegates each to the owning skill (/unikit-gd-spec, /unikit-gd-system, /unikit-gd-content, /unikit-gd-flow), and closes with one /unikit-gd-verify pass. Use when you already know the changes and they touch more than one part of the design, e.g. "apply these GDD changes", "update the combat system and its loot and the boss flow". It also takes a /unikit-gd-review report file (applies its apply-ready bucket), and a bare /unikit-gd-apply reads the last /unikit-gd-verify output in the session. For a single-zone change call its owner directly; to research an open question use /unikit-gd-explore first.

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Create and own the master game design document (GAME.md — the authored one-pager plus the generated [gen] system/flow maps) and the GD-IDS.yaml facts registry — the top-level, big-picture layer of the GDD and the machine interface the code side reads. Use it to write the master spec from a concept or dialogue, import an existing GDD (a file path or URL), edit GAME.md content ("change a pillar", "rework the monetization stance", "tweak the loop stack"), pitch the game ("pitch" → PITCH.md), re-decompose the systems ("remap"), and — importantly — to add a new system to the design map ("let's add a new system", "add a crafting system to the game design", "add this to the GDD"). This is the structural, map-level layer plus GAME.md content edits. To write or fill in the detailed parameters of one existing system, use /unikit-gd-system; to apply one edit spanning several zones at once use /unikit-gd-apply; to invent a brand-new game concept use /unikit-gd-brainstorm.

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。

สร้างสคริปต์ podcast ที่ฟังแล้วไม่เบื่อ พร้อม show notes, timestamps, teaser social

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Understand what SKMTC is, how its engine works, and the architectural invariants — for agents building or extending infrastructure *around* SKMTC rather than authoring generators or running the CLI. Covers the three-phase pipeline, the host/Worker boundary, cross-generator coordination, the manifest, the attribution / gen-maps (provenance) subsystem, the package graph, the dependency substrate, and the design decisions that make SKMTC behave unlike a typical codegen tool. Use this skill when the user asks "what is SKMTC", "how does the SKMTC engine work", "explain the SKMTC architecture", or is building platform infrastructure around SKMTC — a hosted generate API, a schema or generator registry, tracing or provenance tooling, a web app or SaaS that wraps the engine, or platform-level CI integration. This skill is the system mental model. It does NOT cover authoring generators (→ skmtc-generator), running CLI commands (→ skmtc-cli), or diagnosing broken runs (→ skmtc-debug).

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。

Integrate PocketBase as a Go library using the github.com/castle-x/goutils/pocketbase (gopb) package to build single-binary full-stack applications. Use when building Go applications that need user authentication, embedding PocketBase into Go binary, registering custom API routes, managing default users, serving embedded SPA frontend, or deploying single-binary applications. NOT for using PocketBase as a standalone separate process.

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超级情场高手：基于语用学（Grice）、依恋理论（Bowlby/Gottman）和信号博弈论（Spence）的情感洞察与指导系统。 以上帝视角洞察两性关系的全貌，一针见血指出问题本质，给出清晰的方向。 用户粘贴聊天记录或描述情感场景，输出对方真实意图、关系动态诊断、信号质量评估和行动指引。 触发词：「情场高手」「帮我看看」「分析一下」「这段感情怎么办」「ta什么意思」「dating decoder」 调研时间：2026年4月。

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。

.NET timezone handling guidance for C# applications. Use when working with TimeZoneInfo, DateTimeOffset, NodaTime, UTC conversion, daylight saving time, scheduling across timezones, cross-platform Windows/IANA timezone IDs, or when a .NET user needs the timezone for a city, address, region, or country and copy-paste-ready C# code.

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Expert .NET 10 Full-Stack Developer skill. Use this when implementing new features, vertical slices, or modifying existing logic in the JJGNET Broadcasting application. It covers Domain, Data (EF Core), Managers, Api, and Web.

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。

Step-by-step release checklist for Squad — prevents v0.8.22-style disasters

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Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.

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Master the `agentbrain` CLI (npm package `agentbrain-cli`). Use this skill whenever the user runs, installs, configures, or asks about `agentbrain` commands; when they interact with the AgentBrain enterprise data hub — organizations, connectors, knowledge bases, workflows, media/documents, knowledge graph, permissions, LLM/prompt config, cost & usage, governance, audit logs; when uploading documents/files to AgentBrain (`agentbrain media upload`); when authenticating (login/logout/token/apiKey); when retrieving MCP context (`agentbrain retrieve-context`); when running SQL against a connector; when the user pastes any `agentbrain …` command; when they edit `~/.agentbrain/config.json`; or when they mention AgentBrain, agent-brain, agentbrain-cli, or the `.agentbrain` folder.

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.

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FastAPI patterns for async APIs, dependency injection, Pydantic request and response models, OpenAPI docs, tests, security, and production 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。

Research what people actually say about any topic in the last 30 days. Pulls posts and engagement from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the web.

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Clean editorial-style interfaces. Warm monochrome palette, typographic contrast, flat bento grids, muted pastels. No gradients, no heavy shadows.

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Elite frontend design taste for building, reviewing, and polishing web interfaces. Use whenever the user wants to design, redesign, shape, critique, audit, polish, or improve any UI (landing pages, portfolios, dashboards, product UI, components, forms, onboarding, empty states) or asks to make something look better / premium / modern, fix the styling, add or fix animations, or make a design feel less generic ("AI slop"). Covers typography, color, spacing, layout, visual hierarchy, motion, micro-interactions, component states, accessibility, responsive behavior, UX copy, and anti-pattern 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。

Creates test infrastructure with Vitest, xUnit, and pytest

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。