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概要と使いどころ
Phase 4 of the SRS workflow. Reads spec.md and writes one detailed plan file per SRS section (§1–§3 + Appendices). Each file is a complete blueprint for the corresponding SRS section. No word limit.
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Utility skill. Lists all projects under the projects/ directory and shows which Virtual Team pipeline phases have been completed for each project.
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 setting up Service Cloud Voice with Amazon Connect — provisioning the contact center, configuring phone numbers, enabling real-time transcription, and configuring After Conversation Work Time. Covers the deployable metadata behind it: CallCenter, ConversationVendorInfo (vendorType), CallCenterRoutingMap, the Voice ServiceChannel that carries ACW, ServicePresenceStatus, PresenceUserConfig, ServiceCloudVoice.settings, and the VoiceCall / VoiceCallRecording objects. Trigger keywords: Service Cloud Voice, Amazon Connect, contact center, softphone, call transcription, After Conversation Work, ACW, wrap-up time, VoiceCall, CallCenter metadata, vendorType, telephony provider. NOT for Omni-Channel routing setup — use admin/omni-channel-routing-setup. NOT for Open CTI softphone adapters — use apex/cti-adapter-development. NOT for Sales Dialer (Voice.settings) — that is a different product.
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 writing, debugging, or optimizing SAQL queries in CRM Analytics — covering pipeline syntax, aggregation, windowing functions (rank, dense_rank, moving_average), cogroup joins, rollup subtotals, piggyback queries, and REST API execution. NOT for SOQL GROUP BY aggregates in Apex — use apex/apex-aggregate-queries. NOT for dashboard JSON steps and bindings — use admin/analytics-dashboard-json.
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 gather, document, and validate OmniScript flow design requirements before development begins — covering screen layout requirements, branching logic, data source requirements, and user journey mapping. Trigger keywords: OmniScript requirements, OmniScript BA, OmniScript screen design, OmniScript user journey, OmniScript branching requirements. NOT for building the OmniScript or moving logic into an Integration Procedure — use omnistudio/omniscript-design-patterns. NOT for FlexCard requirements — use admin/flexcard-requirements.
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 an admin needs to create an Einstein Discovery story in CRM Analytics Studio, configure prediction definitions, deploy writeback fields, set up what-if analysis, or manage model refresh and activation. Trigger keywords: Einstein Discovery story, prediction definition, writeback field, CRM Analytics Studio, model refresh, what-if analysis, bulk scoring, prediction field, 1OR prefix. NOT for the Einstein Discovery Flow action or model-health monitoring in Model Manager — use admin/einstein-discovery-deployment. NOT for Einstein Prediction Builder, a separate product needing no CRM Analytics license — use agentforce/einstein-prediction-builder. NOT for programmatic scoring through the Connect REST 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 when creating a new Experience Cloud site: selecting LWR vs Aura template, configuring branding and navigation, setting up a custom domain, and using Experience Builder. Trigger keywords: create new Experience Cloud site, LWR vs Aura template, set up community portal domain, Experience Builder page builder, branding sets, navigation menu configuration, Microsite LWR, Build Your Own LWR. NOT for coding LWR themes or custom components — use lwc/lwr-site-development. NOT for deploying a finished site to another org — use devops/experience-cloud-deployment-admin. Also covers the deployable metadata: Network, CustomSite, NavigationMenu, ExperienceBundle, DigitalExperienceBundle, urlPathPrefix, networkMemberGroups, emailSenderAddress, site status Live vs UnderConstruction.
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 building, debugging, or optimizing CRM Analytics dataflows — defining node types (sfdcDigest, Append, Augment, computeExpression, computeRelative, Flatten, dim2mea, sfdcRegister), scheduling runs, handling run failures, and tuning performance. NOT for doing the same transformation in a Data Prep recipe — use admin/analytics-recipe-design. NOT for dataset field types, refresh schedules, or row limits — use admin/analytics-dataset-management.
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 Data Manager in CRM Analytics: enabling objects for sync, scheduling data sync runs, setting up remote connections to external databases, monitoring sync status and error logs, or troubleshooting connected object issues. Trigger keywords: data sync, connected objects, Data Manager, sync schedule, remote connection, Snowflake connector, sync error, incremental sync, CRM Analytics data pipeline. NOT for pushing external data in programmatically via the External Data API — use data/analytics-external-data. NOT for authoring dataflow nodes — use admin/analytics-dataflow-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 editing CRM Analytics dashboard JSON directly to implement advanced bindings, custom SAQL/SOQL step queries, layout changes, step parameters, or cross-widget interactions. Trigger keywords: dashboard JSON, SAQL step, binding syntax, mustache binding, dashboard REST API, widget layout, step limit, datasetId, datasetVersionId. NOT for building the dashboard in the builder UI or picking chart types — use admin/analytics-dashboard-design. NOT for writing or tuning the SAQL itself — use admin/saql-query-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 designing or building CRM Analytics Data Prep recipes — including node selection, join patterns, bucket field configuration, formula expressions, and scheduling. Triggers: 'build a recipe', 'join datasets in analytics', 'bucket a measure field', 'schedule a recipe', 'data prep transformation'. NOT for dataflow JSON and its node types — use admin/analytics-dataflow-development. NOT for tuning a slow or oversized dataset — use data/analytics-dataset-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。
Behavior-first feature development — use when building new capabilities, continuing feature work, or when work introduces new state or multiple user flows. Discovers desired behavior through examples and scenarios before implementation. Do NOT use for bug fixes, typos, or small isolated changes.
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ESLint is the standard linting tool for JavaScript and TypeScript projects. It statically analyzes your code to find problems, enforce coding conventions, and catch bugs before they reach production. ESLint 9 introduced the flat config format, replacing the legacy `.eslintrc` system with a simpler, more composable `eslint.config.js` file. With a rich plugin ecosystem covering React, TypeScript, accessibility, and import ordering, ESLint is the backbone of code quality in modern web development.
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AI เชฟครัวร้านอาหาร — menu development, kitchen brigade, mise en place, food cost, seasonal menu, HACCP, Thai culinary context
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Executive & Business Coach — 1-on-1 coaching session, GROW model, accountability, leadership development สำหรับผู้บริหารและเจ้าของธุรกิจ
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นักอรรถบำบัด (Speech-Language Pathologist) — articulation, stuttering, language development, swallowing, session plan, parent coaching
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Embedded/IoT Engineer — Arduino/ESP32/Raspberry Pi, sensor integration, MQTT/BLE/LoRa, firmware development, battery optimization
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Deep learning framework development with tinygrad - a minimal tensor library with autograd, JIT compilation, and multi-device support. Use when writing neural networks, training models, implementing tensor operations, working with UOps/PatternMatcher for graph transformations, or contributing to tinygrad internals. Triggers on tinygrad imports, Tensor operations, nn modules, optimizer usage, schedule/codegen work, or device backends.
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Firmware development for the Beetle — the CJMCU / DFRobot "Mini Arduino Leonardo" USB board (ATmega32U4 @ 16 MHz, 5 V, 21×28 mm, castellated pads) — its native USB (CDC serial + HID keyboard/mouse/joystick), Caterina bootloader and 1200 bps touch upload, ten exposed I/O pads, four PWM pins across Timer0/Timer1, five ADC channels, I2C on D2/D3, SPI on the back-side ICSP pads, 28 KB usable flash and 2.5 KB SRAM, and the PlatformIO + Arduino AVR core (`board = leonardo`) setup around them. Use when working on this board or any ATmega32U4 Leonardo/Micro/Pro-Micro-class clone: project setup, platformio.ini, why the board shows up as two different serial ports, uploads that fail or hang, recovering a bricked or HID-spamming board by shorting the ICSP reset pads, pin mapping and which pads are missing, PWM/timer conflicts, Servo and tone, USB HID keyboard projects, the SRAM budget, powering from the + pad, 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 Guition JC4880P443C_I_W (JC4880P443, JC4880P443C, often mistyped JC4880P433) — a 4.3" 480x800 IPS touch display board on the JC-ESP32P4-M3 module (ESP32-P4NRW32, 32 MB PSRAM, 16 MB flash, ESP32-C6 Wi-Fi co-processor on SDIO) — its ST7701S MIPI-DSI panel, GT911 touch, backlight, ES8311 codec with speaker amp and mic, microSD, RS485, battery charger, 2x13 header, and the PlatformIO + ESP-IDF (pioarduino) setup around them. Use when working on this board: project setup, platformio.ini and sdkconfig.defaults, the P4 silicon revision and an "Illegal instruction" boot, a black DSI screen, ST7701 init sequence and timings, GT911 init errors, backlight PWM, choosing a free GPIO, Wi-Fi through esp_hosted and esp_wifi_remote, SD card, audio, flashing over USB-C, 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 Arduino Nano (A000005, ATmega328P @ 16 MHz, 5 V) — its 30 KB usable flash, 2 KB SRAM, 1 KB EEPROM, 8-channel 10-bit ADC, six 8-bit PWM pins across three timers, UART shared with the USB-serial chip, I2C on A4/A5, SPI on D10–D13, sleep modes, and the Arduino AVR core + PlatformIO setup around them. Use when working on this board or any ATmega328P Nano clone (FTDI or CH340 USB): project setup, platformio.ini, old-vs-new bootloader uploads, pin mapping, A6/A7 restrictions, timer/Servo/tone conflicts, the 2 KB SRAM budget, analog references, powering from VIN, ICSP recovery, 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 30-pin NodeMCU ESP8266 devkit — NodeMCU DevKit V1.0 / Amica (CP2102) and LoLin NodeMCU V3 (CH340G), built on the Ai-Thinker ESP-12E or ESP-12F module (ESP8266EX, 4 MB flash), with PlatformIO and the Arduino ESP8266 core (`board = nodemcuv2`). Use when working on a NodeMCU, ESP-12E, ESP-12F or ESP8266 devkit: project setup, platformio.ini, the D0-D10 vs GPIO numbering, which pins are safe and which break the boot, GPIO15/GPIO0/GPIO2 strapping, the A0 divider and 1 V ADC, software I2C and software PWM, analogWrite range, LittleFS and flash layouts, OTA, deep sleep and the missing GPIO16-to-RST link, Wi-Fi, heap exhaustion, watchdog and Soft WDT resets, exception decoding, flashing over CP2102/CH340, or debugging why the board does not boot, prints garbage, or reboots by itself.
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 RP2350A Core Board (RP2350A — dual Cortex-M33 @ 150 MHz, 520 KB SRAM, 4 MB or 16 MB QSPI flash) in both of its revisions, RP2350A_V10 and RP2350A_V20 — the 40-pin Pico-2-shaped header, 3-or-4-channel 12-bit ADC, PWM, PIO, USB-C CDC, the V1.0 LDO vs V2.0 buck-boost power wiring, and the PlatformIO + arduino-pico (earlephilhower) setup around them. Use when working on this board, a WeAct RP2350 core board of unknown revision, or any Raspberry Pi Pico 2 / RP2350A clone: project setup, platformio.ini, board = rpipico2 vs weact_rp2350b, telling V1.0 and V2.0 apart, pin mapping, LED and KEY pins, powering it from a battery, 4 MB vs 16 MB flash, erratum RP2350-E9 pull-down trouble, BOOT/RESET 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。