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概要と使いどころ
Create, inspect, analyze, and edit spreadsheets (`.xlsx`, `.xlsm`, `.csv`, `.tsv`) with local code execution. Use for formulas, formatting, charts, validation, financial models, and spreadsheet deliverables.
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。
Prepares indicators of compromise for safe sharing: defanging URLs, domains, IPs, and emails so they cannot be accidentally clicked or resolved, and formatting them into STIX/CSV/MISP-friendly output. Activates for requests to defang IOCs, sanitize indicators for a report, or export indicators for sharing.
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。
Validate SEO preservation during site migrations. Checks redirect chains (301 vs 302, hop count), canonical consistency, title/meta preservation, HTTP status codes, content similarity, and schema preservation. Accepts single URL pair or CSV file of URL pairs. Use when user says "migration check", "site migration", "redirect audit", "URL mapping", "domain change", "relaunch", "site move".
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 when the user wants to generate, normalize, verify, deduplicate, or export training datasets for Codex, Antigravity, or Claude Code from topics, URLs, reference material, web research, or existing JSONL/CSV files. Supports SFT and DPO workflows, custom export schemas, and deterministic local pipeline scripts.
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。
Pin-to-net mapping auditor -- verifies that every IC pin in the schematic is connected to the correct net, matched against a pin map source of truth (CSV, datasheet table, or Python dict). Critical for BGA/QFN devices where swap errors are invisible to DRC/ERC.
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, read, edit, fix, or clean spreadsheet files (.xlsx, .xlsm, .csv, .tsv). Use whenever a build task's artifact kind is spreadsheet, or the task names a spreadsheet file and wants something done to it or produced from it, including restructuring messy tabular data into a proper workbook. Covers openpyxl generation, formulas and recalculation, editing existing workbooks, and the validation gates. Not for tasks whose deliverable is a document, report, or web page that merely contains a 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。
Verify an artifact before delivering it - file deliverables (pdf, pptx, docx, xlsx, csv) and web artifacts alike. Use whenever a build is about to return a link, or a build task asks for validation, QA, or a visual check. Covers the per-kind gate scripts, render-and-look verification, and leftover-placeholder scanning.
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 importing SAM3 or YOLO tracking CSV files into getpixelvideo, including bbox-to-marker anchor 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。
Treino Ultralytics YOLO pose para keypoints do campo de futebol (32 kp), export ONNX, e inferência em vídeo com vaila.soccerfield_keypoints_ai (CSV getpixelvideo + overlay). Use quando o usuário fala em football pitch keypoints, YOLO26 pose, treino Roboflow/HF dataset martinjolif, field_keypoints_getpixelvideo, calibração FIFA, ou soccerfield_keypoints_ai.
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, .xltx, .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。
Use this skill to create, deactivate, freeze, or manage Salesforce users, assign user licenses and feature licenses, configure profiles and roles, set login hours and IP restrictions, and set up delegated administration. Triggers: 'add a new user in Salesforce', 'create a user and assign a licence', adding a new user, deactivating a departing employee, license assignment, freezing a user account, delegated admin setup. NOT for designing the permission set / PSG model — use admin/permission-set-architecture. NOT for who can see which records — use admin/sharing-and-visibility. Also covers: bulk user loads by CSV, Bulk API 2.0 upsert on Username, the UserLogin freeze object, licence and permission-set-licence reclamation, Role metadata deployment, and the offboarding checklist as SOQL.
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 a BA or admin needs to document the Salesforce data model: creating field inventories, object relationship maps, ER diagrams, or analyzing field usage across objects. Triggers: 'data dictionary', 'document our data model', 'object relationship map', 'field inventory', 'ER diagram for Salesforce'. NOT for designing the model or choosing lookup vs master-detail — use data/data-model-design-patterns. NOT for generating the Mermaid or PlantUML diagram — use architect/salesforce-erd-and-diagramming. More trigger keywords: field inventory CSV, describe API, getGlobalDescribe, DescribeFieldResult, sObject describe, schema snapshot, schema drift, blank field descriptions, undocumented fields, field ownership, data dictionary review cadence.
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 a production-grade OEE (Overall Equipment Effectiveness) measurement pipeline for a manufacturing line — data ingestion from MQTT/OPC-UA/Modbus/CSV, A×P×Q calculation engine, Six Big Losses categorizer, MTBF/MTTR/TEEP metrics, Grafana or Streamlit dashboard.
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。
Reference guide for using Xpoz effectively. Load this skill whenever working with Xpoz MCP tools, SDKs, or CLI — it ensures correct query syntax, optimal field selection, proper pagination, and best practices for every Xpoz interaction. Covers authentication, query syntax (boolean operators, date filtering), response modes (fast/paging/CSV), field selection, tracking setup, and all platform tool references (Twitter, Instagram, Reddit, TikTok). Use for ANY Xpoz-related work, not just explicit best-practices questions.
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。
美国加州消费者隐私法（CCPA/CPRA）合规检查、风险评估和文档生成工具。 为涉及加州消费者数据的业务提供全面的CCPA/CPRA合规解决方案。 Use when: 需要进行CCPA/CPRA合规自查、消费者权利保障检查、选择退出机制实现、 数据销售合规检查、服务提供商管理、隐私合规体系建设。 🎉 版本1.0.5重要更新： - 🔧 全新统一化CLI接口，与PIPL、GDPR工具体验一致 - 📊 支持JSON/Markdown/HTML/CSV多格式报告输出 - 🚀 跨法域检查：可与PIPL、GDPR配合使用 - 🔒 纯本地运行，零外部依赖 触发关键词：CCPA、CPRA、加州合规、消费者隐私、数据保护、美国合规、 California privacy、Do Not Sell、消费者权利、选择退出 适用范围：美国加州消费者隐私法（CCPA）/ 加州隐私权法案（CPRA） 运行模式：纯本地，无网络请求 ❎ 外部依赖：无（仅Python标准库）⭐
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。
阿拉丁·AI短剧数字人肖像权合规工坊把「AI 演员/数字人/换脸/声音克隆做完却因肖像权没授权被投诉下架、数字人授权到期还在用、授权只买了一个平台却全网发、AI 形象神似明星惹官司、被举报时拿不出授权链举证」升级成一条纯本地零依赖的上架前置授权链自查工具链：多源导入(drama-cast 角色卡 _cast.json 双契约兼容/人物资产类型声明 assets.json/授权凭证登记 CSV 或 JSON/drama-publish 发行计划 _publish_plan.json 抽平台)→人物资产五分类(AI原创 ai_original/真人出演 real_actor/第三方数字人 digital_human/换脸 face_swap/声音克隆 voice_clone)逐类判定所需授权→10 条确定性授权链规则(A1缺授权凭证 A2要素缺失 A3已过期 A4即将到期 A5平台越界 A6用途越界 A7撞脸公众人物 A8声音克隆缺授权 A9转授瑕疵 A10平台报备缺失)→门禁评分(P0=25/P1=8/P2=3 扣分，100分制 A-D 档，READY可提审/REVIEW建议整改/BLOCK禁止上架)→自包含 HTML 授权链看板(门禁灯+逐条命中+整改建议)+Markdown 整改清单(可直接交制片执行)+feedback 回灌契约(缺证角色回灌 drama-cast 补授权、越界平台回灌 drama-publish 调发行、续签观察名单、报备提醒)。与 aladin-drama 系列闭环衔接(cast/publish 进，整改反馈回灌 cast 补授权、publish 调发行矩阵)。区别于内容合规工具只扫违禁词与画面红线：本款专管「人」的授权链(肖像权/声音权/数字人许可/换脸源授权)，确定性规则可复算、命中带人物名与整改方向、纯本地零依赖零API、授权信息不出本机(法务资产敏感)。触发词：短剧肖像权、数字人授权、换脸授权、声音克隆授权、AI演员合规、肖像授权到期、授权链自查、撞脸明星、数字人合规、AI形象报备、肖像权侵权、portrait rights、digital human license、face swap consent、voice clone authorization、AI短剧、阿拉丁短剧、短剧创作闭环。
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。
Domain-aware complexity routing: scans the task for domain keywords, matches domain-complexity.csv, and returns complexity level, workflow intensity, and execution tier. Extends Phase 0 orchestration.
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。
Local-only regression / benchmark skill for ui-clone-skills maintainers. Drives the standard ui-reverse-engineering pipeline against the canonical reference site (https://realfood.gov) and records AE/SSIM, iteration count, gate fail counts, and outcome to benchmark/history.csv so prompt / sub-doc / model-version drift surfaces as a trend. Trigger phrases: "run benchmark" / "regression benchmark" / "benchmark clone". The Makefile no longer has a `benchmark` target — setup is inline bash in this skill (Step 1 below). Internal: NOT registered in `.claude-plugin/plugin.json` `skills`. Not part of the public 3-skill marketplace surface. Maintainer tooling only.
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。
Safely localize unknown Unity games, especially Japanese-to-Chinese projects. Use to discover Unity version/layout/backend, migrate translations across game versions, extract occurrence-mapped text from serialized assets, embedded CSV, bytecode, UI, Localization StringTables, Utage, or middleware, bridge rows through AiNiee-style translation, validate and transactionally write approved candidates, audit residual and runtime-only text or AutoTranslator diffs, diagnose TMP fonts and Addressables/IL2CPP failures, locate saves, or acceptance-test SHA-verified patches.
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。
Translate books, documents, AiNiee projects, Unity localization caches, or flat MTool JSON dictionaries end to end on the coding agent itself without the AiNiee app. Use for requests such as "用 agent 翻译这本书", "把 epub 翻译了", "翻译 Unity CSV/cache", "把这个 MTool JSON 翻译了", or "AiNiee-style translation" that need a locked glossary, resumable batches or bounded subagent groups, terminology consistency, source-aware QA, validated cache writeback, and export. For MTool, preserve the left JSON key as immutable source text and write only the right value as translation.
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。
Annotate speech/TTS datasets with per-clip quality metrics (MOS, SNR, STOI, pitch, bandwidth, speaking rate, WER/CER, gender/emotion), multi-ASR consensus transcription and speaker labeling using the audiogear pipeline; then filter clips by quality and build listenable HTML QA reports. Use when asked to compute audio dataset metrics, build extended_metadata.csv, transcribe unlabeled audio, select clean TTS training data, or QA a speech dataset.
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。
Given an article DOI or PubMed ID, discover and download the genomics data files deposited by the authors (VCF, FASTA, H5AD, CSV, JSON, BAM, etc.) from public repositories such as GEO, ENA, Zenodo, Figshare, Dryad, and OSF.
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。