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概要と使いどころ
Generate and maintain a multi-channel product feed across Google Merchant Center, Meta Catalog (Instagram + Facebook Shops), TikTok Shop, Pinterest Catalogs, Bing Shopping, and Snapchat Catalogs from a single product source of truth (Shopify, BigCommerce, WooCommerce, custom DB)..
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-pass editor that removes AI-writing tells from drafted content — eliminates filler phrases, balances sentence length, restores opinion and voice, and strips em-dash overuse so posts sound human and opinionated rather than ChatGPT-generic..
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 bookkeeping automation systems for transaction categorization, bank reconciliation, AP/AR efficiency, chart of accounts optimization, and month-end close using GAAP and double-entry accounting patterns..
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 long-form thought leadership articles, opinion pieces, industry POV essays, and CEO/founder bylines using the Made to Stick SUCCESs framework (Chip and Dan Heath). Use when the user asks for a long-form article, executive byline, opinion piece, industry POV, manifesto, "explain our point of view on X", or wants to publish an authority-building piece (1200-2500 words). Reads brand voice and positioning from knowledge/. For a short-form post, see linkedin-post. For the newsletter, see newsletter-writer. For improving an existing draft, see copy-review.
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。
Surface and visualize hidden dependencies blocking delivery. Use when the user says "map our dependencies", "what's blocking what", "dependency audit", "why are teams blocked", "we have a bottleneck", "draw out the dependencies", or asks to identify cross-team blockers - even if they don't explicitly say "dependency mapping". Based on "Making Work Visible" by Dominica DeGrandis (time theft, invisible work, flow blockers).
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 image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo", "infographic", "seo image", "create visual", "image-gen", "favicon", "schema image", "pinterest pin", "generate visual", "banner", or "thumbnail".
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。
Audit Google Ads measurement, Search, Shopping, Performance Max, Demand Gen, YouTube-linked inventory, keywords and search terms, negative-keyword generation or review, creative assets, bidding, budgets, settings, and policy. Use for Google Ads, AdWords, Search campaigns, search terms reports, broad negatives, Shopping, Performance Max, PMax, Demand Gen, GAQL, Google conversion tracking, or Google campaign optimization.
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。
Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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 to configure a Lightning Service Console app in Salesforce — Console Navigation (split view), workspace tabs and subtabs, the utility bar with Omni-Channel, Macros and History, Quick Text, keyboard shortcuts, and navigation rules per object. Trigger keywords: Service Console, console app, workspace tabs, subtabs, utility bar macros, Omni-Channel utility, split view, Quick Text, console navigation rules, keyboard shortcuts service console, navType Console, workspaceConfig mappings, WorkspaceMapping fieldName, UtilityBar FlexiPage, tabLimitConfig, listPlacement, MacroInstruction, QuickText Channel multipicklist, isNavTabPersistenceDisabled. NOT for opening or refreshing console tabs from code — use lwc/lwc-console-workspace-api. NOT for Omni-Channel routing setup — use admin/omni-channel-routing-setup.
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 picklist data quality has degraded: unrestricted picklists accepting garbage API values, dependent picklist relationships bypassed by integrations, record type picklist value mappings drifting out of sync, or orphaned values appearing in reports. NOT for the value-deactivation runbook or the API-name-vs-label trap — use admin/picklist-data-integrity. NOT for initial picklist creation or Global Value Set design — use admin/picklist-and-value-sets. NOT for record type configuration itself — use admin/record-types-and-page-layouts.
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 Salesforce-anchored personas and journey maps where every persona ties to a Permission Set Group, primary record types, list views, dashboards, automation, and a measured mobile/desktop posture, and journeys walk each task end-to-end with friction tags that drive UX decisions. NOT for stakeholder authority / RACI (use admin/stakeholder-raci-for-sf-projects), NOT for system-side process flows (use admin/process-flow-as-is-to-be), NOT for Lightning page design itself (use admin/lightning-app-builder-advanced or the lightning-record-page-auditor agent), NOT for pure design / UX research disconnected from org 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。
Use this skill when designing lead nurture journeys in MCAE (Account Engagement / Pardot) Engagement Studio — mapping content to funnel stages (Awareness, Consideration, Decision), behavioral trigger rules, branching program paths, and MQL handoff criteria to Sales. NOT for building a journey in Marketing Cloud Journey Builder — use admin/journey-builder-administration. NOT for the scoring and grading model behind MQL — use admin/mcae-lead-scoring-and-grading.
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 deploying a trained Einstein Discovery model to production records declaratively — activating a prediction definition, mapping output fields to page layouts, adding the Einstein Discovery Action to a Flow, running bulk predict jobs, and monitoring model health via Model Manager UI. Trigger keywords: prediction definition activation, bulk predict job, Einstein Discovery Flow action, Model Manager, prediction field mapping, model refresh activation, scoring job, Einstein Discovery recommendations on record. NOT for authoring the story in CRM Analytics Studio — use admin/einstein-discovery-setup. NOT for programmatic scoring through the API — use agentforce/einstein-discovery-development.
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 configuring or troubleshooting FSC Referral Management: setting up referral types via ReferralRecordTypeMapping custom metadata, routing referrals through Lead Assignment Rules keyed on the Expressed Interest picklist, tracking Referrer Score, and partner referral visibility in Experience Cloud. Trigger keywords: referral routing, FSC referral types, ReferralRecordTypeMapping, Expressed Interest picklist, partner referral Contact, Referrer Score Experience Cloud. NOT for clinical referrals in Health Cloud — use admin/referral-management-health. NOT for standard Lead capture and conversion outside FSC — use admin/lead-management-and-conversion.
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, filter, refresh, and activate audience segments in Salesforce Data Cloud: segment types (Standard, Real-Time, Waterfall, Dynamic, Data Kit), segment refresh schedules, activation field mapping, audience publishing. NOT for the SQL metrics a segment filters on - use admin/data-cloud-calculated-insights. NOT for ingestion, DLO to DMO mapping and identity resolution - use data/data-cloud-data-streams.
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。
Design, mock up, build and review terminal UIs — full-screen TUIs, interactive CLIs and pickers, and plugin panels or popups inside a host (herdr, tmux, Neovim, k9s, lazygit). Use when designing, reviewing (from code, a live capture or a screenshot) or redesigning a TUI's layout, keybindings, states or colors, including requests that name a known TUI (lazygit, k9s, btop, yazi, helix, fzf); writing terminal mockups; building or fixing one in Ink, Textual, Bubble Tea, Ratatui or gum; mapping a color scheme (Catppuccin, Dracula, Nord, Gruvbox, Tokyo Night, Rosé Pine…) onto a TUI's theme; fixing misaligned glyphs, flicker, NO_COLOR, exit codes, signals, pipes or a broken terminal after exit; suspend or $EDITOR handoff; or profiling a slow TUI. Not for web or native GUIs, terminal-emulator, editor or shell-prompt themes.
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。
Firmware development for the Waveshare ESP32-S3-RLCD-4.2 (SKU 33298 / 33507, and the -EN variant) — an ESP32-S3-WROOM-1-N16R8 AIoT board built around a 4.2" fully reflective 300x400 monochrome LCD on a Sitronix ST7305/ST7306, with no backlight, plus an ES8311 speaker codec, an ES7210 dual-microphone ADC, an SHTC3 temperature/humidity sensor, a PCF85063A RTC, a microSD/TF slot on SDMMC, an 18650 holder with battery sensing, BOOT/KEY/PWR buttons and a 2x8 2.54 mm expansion header. Use when working on this board: project setup, platformio.ini, the qio_opi PSRAM memory type, the pin map and which header pins are traps, U8g2 and the ST7305 constructor, a blank or shifted panel, ST7305 low-power mode HPM/LPM, the shared I2C bus and its four slaves, I2S audio directions and the speaker amplifier enable, mounting the TF card, battery voltage, USB CDC console with no UART bridge, flashing over Type-C, deep sleep, or debugging why something on the board does not work.
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。
Firmware development for the <VENDOR> <BOARD NAME> (<MCU PART NUMBER>) — its <peripheral>, <peripheral>, <peripheral>, and the <SDK/HAL> + <build system> setup around them. Use when working on this board or any <compatible siblings>: project setup, <config file>, clock configuration, pin mapping, peripheral bring-up, <the board's headline concern>, flashing, or debugging why something on the board does not work.
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。
Firmware development for the Raspberry Pi Pico (original, RP2040 — dual Cortex-M0+ @ 133 MHz, 264 KB SRAM, 2 MB QSPI flash) — its 26 exposed GPIO, 4-channel 12-bit ADC, 16-channel PWM, 2× UART/I2C/SPI, PIO state machines, USB 1.1 CDC, VSYS/VBUS/SMPS power wiring, and the PlatformIO + arduino-pico (earlephilhower) setup around them. Use when working on this board, any Pico H or Pico clone, or a bare RP2040: project setup, platformio.ini, the earlephilhower-vs-Mbed core choice, pin mapping, USB CDC serial, analogRead/analogWrite behaviour, Wire/SPI defaults, battery power, EEPROM emulation, BOOTSEL/UF2 flashing, or debugging why something on the board does not work.
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。
Firmware development for the WeAct Studio MiniSTM32H7xx core board (STM32H750VBT6) — its 0.96" ST7735 TFT, DVP camera, QSPI/SPI flash, MicroSD, USB, and the STM32Cube HAL + PlatformIO setup around them. Use when working on this board or any STM32H750/H743 WeAct core board: project setup, platformio.ini, clock/PLL configuration, pin mapping, peripheral bring-up, LCD performance, D-cache/DMA problems, DFU flashing, or debugging why something on the board does not work.
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 "build a feature", "fix a bug", "implement something", "start a dev cycle", types "/dev", or describes a software task that requires design, implementation, testing, and shipping. Orchestrates the full software development lifecycle from interrogation through shipping, with self-learning that improves over time.
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。
Run the same scrape or task across many accounts at once - each in its own browser profile with its own fingerprint, cookies and exit IP - and read data from sites that need a session or that answer a plain HTTP scraper with a captcha while answering a real browser. One command per site returns JSON, so there are no selectors to write or repair: Amazon and Walmart search, Google and DuckDuckGo results, Reddit posts and comments, X timeline, Medium, Yelp, Indeed job listings, Hacker News, GitHub, PyPI, npm, plus exit-IP and fingerprint checks. Use for multi-account operations you are authorized to run, price and listing monitoring per region, SERP collection, logged-in data, and scrapers that keep breaking. Also for 'scrape amazon', 'google search results', 'reddit data', 'scrape logged in site', 'run task on many accounts', 'site blocks my scraper', 'scraping without selectors'. Node or Python.
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。
Land a ready branch - push, PR, pinned CI watch, squash-merge, issue verification, cleanup. Use for every PR landing; encodes the run-ID pinning and cleanup discipline.
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。
Apply these opinionated JavaScript conventions whenever writing or reviewing JS or Node: ESM-first packaging, choosing between Promise combinators, error handling that doesn't swallow failures, AbortController for cancellation, keeping the event loop unblocked, and reaching for platform APIs before dependencies.
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。