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Use this skill when planning or executing the human side of an Agentforce or Einstein AI feature rollout — user trust-building, AI-specific training, structured feedback collection via the Feedback API, and adoption measurement via Agentforce Analytics. NOT for turning the Einstein for Sales features on — use agentforce/agentforce-sales-ai-setup. NOT for rollout training with no AI in scope — use admin/change-management-and-training.

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Use this skill when planning user adoption, structuring Salesforce training materials, drafting release communications, or running a change impact assessment for a Salesforce rollout or update. Triggers: user adoption plan, training materials, release announcement, change impact, go-live communication, communication plan, training plan by persona, adoption metrics, LoginHistory adoption report, PromptAction, training sandbox, go-live checklist, post-go-live feedback, super user program, pilot group. NOT for org deployment mechanics or sandbox promotion — use admin/change-management-and-deployment. NOT for adoption of an Agentforce or Einstein AI feature — use admin/ai-adoption-change-management. NOT for configuring the in-app prompts themselves — use admin/in-app-guidance-and-walkthroughs.

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 enabling, configuring, or monitoring Change Data Capture (CDC) entity selection, channel enrichment, and delivery usage limits from an admin perspective. Covers the PlatformEventChannel and PlatformEventChannelMember metadata, the standard ChangeEvents channel, custom __chn data channels, enrichedFields, filterExpression, destructive deselection, and PlatformEventUsageMetric / EventBusSubscriber monitoring. Trigger keywords: change data capture, CDC, entity selection, change event, platform event channel, channel member, enrichment, event delivery allocation. NOT for writing an Apex change-event trigger — use apex/change-data-capture-apex. NOT for subscribing an external system over Pub/Sub or CometD — use integration/change-data-capture-integration.

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 this skill when driving adoption of CRM Analytics (Einstein Analytics) across an org — the Analytics Adoption App for measuring who uses which dashboards, embedding analytics into Lightning pages, pinning dashboards to the Analytics home page, self-service personas, and analytics success metrics. Triggers: analytics adoption, dashboard usage tracking, embedded analytics strategy, self-service analytics enablement, CRM Analytics rollout. NOT for building the dashboards — use admin/analytics-dashboard-design. NOT for the app, datasets and lenses — use admin/crm-analytics-app-creation. NOT for non-analytics rollout training — use admin/change-management-and-training.

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。

Timeboxed ideation on a topic where lens-driven proposers generate structurally different ideas, blind critics cull them, and pairwise judges rank the survivors on a tournament ladder instead of 1-10 scores, evolving the leaders until the clock runs out. Use when the user wants to brainstorm, explore ideas, discover features, generate options, or think through possibilities for a specified duration. Triggers on requests like "brainstorm X for 30 minutes", "ideate on X", "spend an hour thinking about X", "what features should we build", "explore options for X". Not for executing a task over time (timeboxed-iterating) or optimizing a measurable metric (autoresearch).

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。

Improve an existing agent SKILL.md through one gated cycle: select the target (default this skill), snapshot the committed baseline, diagnose against skill-design-principles plus four rubric dimensions, apply exactly one focused change, and ship only if a different agent than the author PASSes with quoted evidence. Use when the user says "improve this skill", "improve-skill", "iterate on SKILL.md", or "apply skill-design-principles to a skill". Do not use for code slop over a duration (anneal), generic timeboxed work (timeboxed-iterating), graph orchestration (workgraph), metric hill-climb on a codebase (autoresearch), or stripping slop from existing prose (catalog-deslop).

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。

Expert in point-set topology, algebraic topology, differential geometry, and geometric intuition for abstract concepts

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。

Aggregate friction log files across a time period to identify recurring patterns, classify each cluster by intervention type, produce a prioritized action plan with success criteria, and calculate convergence metrics. Complements `skmtc-retro` (which captures per-session signal) by acting as the system's actuator: turning accumulated observations into decisions. The primary output is a review document that makes the "is it getting better?" question answerable. Use this skill when the user asks to "review retros", "review friction", "run a retro review", "what's the pattern across sessions", "what should we fix next", or on a periodic cadence (monthly, pre-release). Also run after a cluster of sessions on the same feature area to surface systemic issues before they compound. Distinct from `skmtc-retro` — that skill captures per-session observations; this skill synthesizes them into decisions. Do not run this skill as a substitute for a per-session retro.

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。

Write, restructure, or review documentation — tutorials, how-to guides, reference pages, concept/explanation docs, API references, READMEs, changelogs, release notes, and troubleshooting guides. Distills documentation craft from Mintlify's guides (compiled from technical writers at Stripe, GitHub, Amplitude, and Anaconda), the Diátaxis framework (including the compass and per-type voice), the Google and Microsoft style guides, Every Page Is Page One, Write the Docs, and Docs for Developers: audience analysis, content-type selection, style and word-level rules, procedure writing, structure for humans and AI agents, code-example standards, page templates (templates.md), mechanical enforcement and llms.txt (mechanics.md), maintenance, and success metrics. Use this skill when the user asks to "write docs", "document this feature", "improve this page", "review these docs", "write a tutorial / how-to / reference page", "structure the docs", "write API documentation", "write a README / changelog", or when authoring any file under a `docs/` tree. For SKMTC docs specifically, this skill governs the *craft* (what makes the page good); the content split between skills, `llms.md`, and the docs tree is governed by `docs/skills/README.md`. Distinct from `skmtc-retro` (captures observations about work) and the `skmtc-*` operational skills (guide doing the work) — this skill guides writing *about* the work for readers.

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。

Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas.

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。

Startup Founder Playbook — idea validation, MVP, fundraising (seed→Series A), team building, pitch deck, metrics, investor relations

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。

วิเคราะห์ crypto market — BTC/ETH/altcoin, on-chain metrics (MVRV, NUPL), DeFi yield, fear/greed (risk สูงมาก)

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。

AI Growth Hacker — north star metric, AARRR funnel, viral loop, experimentation framework, retention hook สำหรับ startup และ e-commerce ไทย

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。

Converts transparent or solid-background single-color PNG files and SVG files containing one embedded or local PNG into verified path-only SVG output. Removes pure-color backgrounds automatically. Uses Potrace threshold and parameter scans with alpha error metrics to preserve detailed logos, stamps, engravings, and line art. Use when the user asks to convert images to SVG, vectorize PNG, convert bitmap to true SVG, remove embedded raster data from SVG, 图片转矢量, PNG 转 SVG, 真矢量, or 位图描摹.

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 monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms. Use when turning metrics into a working dashboard instead of a vanity board.

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。

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics

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。

Semantic Design System Skill for Google Stitch. Generates agent-friendly DESIGN.md files that enforce premium, anti-generic UI standards — strict typography, calibrated color, asymmetric layouts, perpetual micro-motion, and hardware-accelerated performance.

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。

Runtime profiling with multi-metric measurement, instrumentation, and performance map generation

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。

Checks structured logging, health check endpoints, metrics collection, request tracing, log levels. Returns findings with severity, location, effort, recommendations.

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。

Builds dependency graph, detects cycles (DFS), validates boundary rules, calculates coupling metrics (Ca/Ce/I, CCD/NCCD). Adaptive architecture 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。

Coordinates code quality: ln-511 metrics, ln-512 cleanup, inline agent review (Codex + Gemini), ln-513 regression, ln-514 log analysis. Returns quality_verdict + aggregated results.

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。

Measurement-driven code refactoring — profile before changing, measure after, keep only if metrics improve. Covers complexity reduction, extraction patterns, and bulk refactoring for mechanical changes across many files.

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。

Complete community building, engagement, and monetization system. From zero to thriving community — launch strategy, member engagement loops, content programming, moderation frameworks, growth tactics, monetization models, and health metrics. Works for Discord, Slack, Telegram, Circle, forums, or any platform.

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。

Generate investor-ready board decks and reporting packages. Covers monthly board updates, quarterly deep dives, and annual reviews with the metrics that actually matter.

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。