「defaults」の検索結果

Use when admins are reducing Chatter signal-to-noise across an org — covers org-level Chatter Email Settings, per-user Email Settings preferences, group-level email digest frequency (Daily / Weekly / Every post / Never), bell-icon Custom Notifications vs Chatter feed-post tradeoffs, automated-feed suppression on record types via Feed Tracking config, and the Chatter Settings org defaults that control whether new users start with everything-on. Triggers: 'chatter feed full of automated posts nobody reads', 'users complain about chatter email volume', 'turn off chatter notifications for a specific group', 'change default chatter digest frequency', 'stop process builder posts from filling the feed', 'NotificationFrequency invalid value', 'ChatterEmailsMD.settings will not deploy', 'custom notification recipient limit'. NOT for Custom Notifications API design (use apex/apex-custom-notifications-from-apex), NOT for Connect API / Chatter REST API integration patterns (use apex/apex-connect-api-chatter), NOT for Chatter group lifecycle, archiving, ownership and unlisted-group governance (use admin/chatter-group-governance).

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Use when designing deployable Salesforce configuration with Custom Metadata Types, especially when choosing between CMTs, Custom Settings, and Custom Objects, protecting packaged defaults, or exposing config to Apex, Flow, and formulas. Triggers: 'custom metadata vs custom settings', 'deployable config', 'protected custom metadata', 'feature flags in Salesforce'. NOT for hierarchical Custom Settings resolution, getInstance/getValues, or their SOQL cost — use admin/custom-metadata-types-and-settings. NOT for high-churn transactional or user-managed business records — use admin/object-creation-and-design. NOT for secrets — use integration/named-credentials-setup. More trigger keywords: __mdt, CustomMetadata .md file, customMetadata folder, getInstance, getAll, xsi:type, visibility PackageProtected, MetadataRelationship, EntityDefinition field, $CustomMetadata.

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Router for the 63 SfSkills `flow` skill packages. Flow Builder: record-triggered, screen, scheduled and orchestration flows, bulkification, fault handling, limits, testing. "My flow" belongs here even when salesforce-apex also names the limit. Nightly scheduling without naming code defaults here; apex takes it when code/class/Apex is named. Flow-vs-Apex choice before anything is built: admin/process-automation-selection. Use when the request mentions Flow, Flow Builder, record-triggered flow, screen flow, scheduled flow, subflow, fault path, flow element, orchestration, Process Builder migration, Workflow Rule migration, flow limit, flow hitting SOQL limit, too many SOQL queries in a flow, flow bulkification, Get Records performance. Finds and opens the exact skill package to read; it does not contain the guidance itself.

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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.

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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 Guition JC-ESP32P4-M3-DEV board (JC-ESP32P4-M3 module — ESP32-P4NRW32 with 32 MB in-package PSRAM, 16 MB flash, and an ESP32-C6 radio co-processor on SDIO) — its MIPI-DSI panel and MIPI-CSI camera connectors, IP101 Ethernet, ES8311 codec with speaker amplifier and microphone, microSD on SDMMC, RS485, three USB-C sockets, the 26-pin JP1 header, and the PlatformIO + ESP-IDF (pioarduino) setup around them. Use when working on this board or any ESP32-P4 devkit: project setup, platformio.ini and sdkconfig.defaults, the silicon revision split between rev v1.3 and rev v3.x, why the bootloader dies with "Illegal instruction", the pin map and which header pins are traps, Wi-Fi through esp_hosted and esp_wifi_remote, mounting the TF card and its on-chip LDO, bringing up a DSI panel, the shared I2C bus, audio direction and the amplifier enable, Ethernet RMII pins, choosing a free GPIO, flashing over any of the three USB-C ports, or debugging why something on the board does not work.

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Run a self-retrospective on a SKMTC-related session — generator authoring, CLI configuration, debugging, or any sustained interaction involving `@skmtc/core`, `@skmtc/cli`, or `@skmtc/gen-*` packages. Captures three distinct outputs: (1) friction entries (mistakes, surprises, overridden defaults, multi-cycle struggles), (2) a "knowledge acquired" block recording facts the agent learned during the session that weren't in its training — the primary signal for doc gaps — and (3) a closing priority list ranking the top 2-3 findings for docs/skills triage. Wins are logged only when they identify a pattern worth codifying that isn't already in a skill. Use this skill when the user asks to "retro", "skmtc retro", "log friction", "reflect on this session", "what did we learn", "run a retrospective", or after substantive SKMTC work (generator authoring, multi-step debugging, non-trivial CLI configuration) where capturing observations would help improve skills, docs, or SKMTC itself. Distinct from the `skmtc-cli` and `skmtc-generator` skills — those guide *doing* the work; this skill captures observations *about* the work. Do not invoke this skill during ordinary work; it is end-of- session (or mid-session-checkpoint) only.

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Create an implementation plan for a feature — a dependency-ordered, actionable task list for the project. Has four modes: fast (a quick single-pass plan), full (a richer plan that can also create a git branch), ultra (a multi-file bundle — a manifest plus one deeply specified file per phase — for execution by a smaller model), and add (extend an existing plan with more tasks). Pick the mode from the user's wording: "full plan" runs full; "quick plan" or "fast plan" runs fast; "ultra plan", "ultraplan" or "ultra-plan" runs ultra; a plain "create a plan" with no qualifier defaults to fast; "add to the plan" or "extend the plan" runs add. Use whenever the user wants to plan a feature or task, e.g. "create a plan", "create a full plan", "create a quick plan", "run an ultra plan for the inventory system", "plan this feature", "add this to the plan", "extend the plan", "add a phase to the plan". Ultra runs only when the user names it — never because the feature looks large.

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。

Teaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or generic.

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Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.

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。

Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.

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 Next.js conventions whenever writing or reviewing App Router code (14+): Server Components by default, where the 'use client' boundary belongs, the caching defaults that changed in Next 15, tag-based revalidation, treating Server Actions as public endpoints, the Metadata API, and next/image and next/font.

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View, create, cancel, bid, and claim Aavegotchi GBM auctions on Base mainnet (8453). Subgraph-first discovery (Goldsky), with onchain verification + execution via Foundry cast. Safety-first: DRY_RUN defaults to 1 (simulate with cast call; only broadcast with cast send when DRY_RUN=0 and explicitly instructed).

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。

View, add, and execute Aavegotchi Baazaar listings on Base mainnet (8453). Buy with GHST directly or buy with USDC using swapAndBuy*. Safety-first: dryRun defaults true (simulate with cast call; only broadcast with cast send when dryRun=false / DRY_RUN=0).

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。

Generates a minimal .editorconfig with sensible defaults for a repository. Use when starting work in a new repository, when a project has no .editorconfig, or when the user asks to add or standardise editor and formatting settings.

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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

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Delimits putative species boundaries from molecular data within the de Queiroz 2007 unified-lineage framework using ASAP (Puillandre 2021 successor to ABGD), mPTP C++ (Kapli 2017 successor to bPTP; bPTP is Python NOT R), GMYC single/multi-threshold (Pons 2006; Fujisawa 2013), multilocus BPP v4 with prior calibration from data (NOT defaults; Yang 2015), SNAPP + BFD* for SNP delimitation, DELINEATE (Sukumaran 2021) speciation-process modeling to address Sukumaran & Knowles 2017 PNAS critique that MSC delimits structure not species, integrative-taxonomy congruence (Padial 2010; Carstens 2013), Dsuite for introgression testing before sister claims (Malinsky 2021), and Meyer & Paulay 2005 barcoding-gap-absence caveat. Use when delineating species from DNA barcoding data, resolving cryptic complexes, choosing among ASAP/mPTP/BPP/DELINEATE, calibrating BPP priors, distinguishing introgression from ILS, or applying the Sukumaran-Knowles oversplitting correction.

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。

Draft a pull request description from the current branch diff plus rolling-wave project context. Use when the user wants PR body text, changes, potential risks, or reviewer notes for a branch, especially after completing a rolling-wave slice. Defaults to the Git Town parent branch when no base branch is named.

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。

Scan the codebase for common security issues: hardcoded secrets, SQL injection vectors, XSS, unvalidated inputs, and insecure defaults. Use before deploying, as part of code quality review, or when asked to check for security issues.

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 GenAI and agentic apps with genai-tk (tclatos/genai-tk), a YAML-driven IoC toolkit over LangChain, DeepAgents, DeerFlow, and Prefect. Use this skill whenever the user mentions genai-tk, genai_tk, `cli init`, `cli agents run`, `LangchainAgent`, `create_harness`, `get_llm`, `global_config()`, `model_id@provider`, `agents:`/`agent_defaults:` profiles, `RetrieverFactory`, `cli workflow`, or BAML extraction. Also trigger for app_conf.yaml, GENAITK_PROFILE, CodeAct, OpenSandbox, decision models, or "the toolkit".

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Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow.

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Use when adding or reviewing keyboard shortcuts in a macOS app — in-app vs global, RegisterEventHotKey vs the KeyboardShortcuts package vs NSEvent monitors, user-configurable recording, conflict handling, and which defaults won't collide with the system.

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Verified lookup pack for crouton's schema→CRUD generation domain — the fieldsFile JSON format, the complete field-type catalog with aliases, the naming contract, the exact artifact list one generate run produces, the seed/default-layout pipeline, dialect defaults, and rollback semantics. Use when writing or reviewing a collection schema, when asking "what field types exist / what does `crouton config` actually generate / where did this file name come from / why did I get a pg schema", when a generated file's name or path doesn't match the docs, or when removing/regenerating a collection. Trigger phrases — "what field types are supported", "schema JSON format", "what files does crouton generate", "naming convention for collections", "rollback a collection", "dialect default". The generation WORKFLOW (steps + sign-off gates) lives in the `crouton` skill — this is the reference it doesn't carry.

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。

Teaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or 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。