「loads」の検索結果

Diagnose and mitigate Salesforce data skew — ownership skew (single user owns >10,000 records) and parent-child skew (>10,000 children under one parent) — that cause sharing recalculation slowness, group membership lock errors, and record-level locking failures. Covers lookup skew and UNABLE_TO_LOCK_ROW, Defer Sharing Calculation (deferGroupMembership / deferSharingRules in Sharing.settings), ownership bucket groups, Controlled by Parent OWD, Bulk API serial vs parallel concurrency for skewed loads, and the documented load ordering for roles, groups and sharing rules. NOT for planning and batching a recalculation job — use data/sharing-recalculation-performance. NOT for designing the sharing model itself — use admin/sharing-and-visibility.

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。

Router for the 101 SfSkills `data` skill packages. Data model, data movement and data quality: migrations, bulk loads, query optimisation, deduplicating at volume, archival. Ordinary-volume duplicate cleanup and prevention use salesforce-admin; come here for hundreds-of-thousands+ dedup or third-party tools. LDV architecture uses salesforce-architect. Use when the request mentions data model, data migration, data load, Data Loader, Bulk API, external id, deduplication at volume, archival, SOSL, cross-object search, sandbox seed data, SandboxPostCopy, native Data Seeding. Finds and opens the exact skill package to read; it does not contain the guidance 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 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 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。

Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence.

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。

Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence.

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。

Work with Runpod GPU infrastructure and documentation. Use when Codex needs to create, deploy, manage, debug, or review Runpod Pods, Serverless workers/endpoints, templates, network volumes, Public Endpoints, Flash apps, runpodctl commands, Runpod Python SDK usage, REST/GraphQL API usage, Runpod MCP setup, Docker images for Runpod, endpoint request payloads, logs, billing/cost checks, or Runpod deployment troubleshooting.

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。

Fetch any URL and convert to markdown using Chrome CDP, with automatic image downloading. Supports auto-capture and wait-for-user modes. Downloads article images to local directory and rewrites image references to relative paths. Use when user wants to save a webpage as markdown with images. Keywords: url to markdown, save webpage, download article, 网页转markdown

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。

Loads org- and repo-level coding rules from Qodo before code tasks begin, ensuring all generation and modification follows team standards. Use before any code generation or modification task when rules are not already loaded. Invoke when user asks to write, edit, refactor, or review code, or when starting implementation planning.

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 estimating one-rep max (1RM), converting between weight and rep ranges, or calculating training loads from a validated percentage-of-max table.

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。

Operate long-lived agent workloads with observability, security boundaries, and lifecycle 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。

Persistent per-project memory for Claude Code. Auto-loads project context on session start, tracks sessions with git activity, and writes to native memory. Commands run deterministic Node.js scripts — behavior is consistent across model versions.

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。

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

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 any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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 sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify environmental impact requirements, and provide actionable recommendations to build, deploy, and manage the workload sustainably in Google Cloud.

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 security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.

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 operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident 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。

This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads.

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 cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.

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 reliability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use this skill to evaluate a workload, identify reliability requirements, and provide actionable recommendations for build, deploy, and manage the workload reliably in Google Cloud.

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 performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.

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 and operate ChatDOC Studio knowledge bases through pd_router using a Bearer API key and JavaScript helpers. Use when Codex needs to upload one or more PDF/DOC/DOCX files, skip failed files without aborting the whole job, create a knowledge base from successful uploads, or call the ChatDOC Studio knowledge-base skill endpoints through `https://platform.paodingai.com/openapi/chatdoc-studio/...`.

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。

4claw — a moderated imageboard for AI agents. Boards, threads, replies, media uploads, bumping (bump=false to not bump), greentext, and automatic capacity purges. Post spicy hot takes (what you’re REALLY thinking) — but no illegal content, doxxing, harassment, or minors.

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。

Download YouTube videos with customizable quality and format options. Use this skill when the user asks to download, save, or grab YouTube videos. Supports various quality settings (best, 1080p, 720p, 480p, 360p), multiple formats (mp4, webm, mkv), and audio-only downloads as MP3.

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。