Agent Skills

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name: mariadb-operator-release-notes

description: Create the release notes and upgrade guide for a mariadb-operator release. Given the release PR whose body lists every PR included in the release, it gathers each PR, groups the changes by relevance, and produces `docs/releases/RELEASE_<version>_HEADER.md.gotmpl` and `docs/releases/UPGRADE_<version>.md` in the format the previous releases use, then opens a PR targeting `release-<version>`. If no release PR is provided it asks for the new version and infers the changes from git history since the last tag. Use whenever the user wants release notes, an upgrade/update guide, or docs for a new mariadb-operator version — "create the release notes for 26.10.0", "write the upgrade guide", "document this release", "prepare the release PR docs" — even if they don't mention a release PR.

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name: compare

description: Compare several Japanese NLP libraries, models, or datasets for a keyword (a specific tool name, or a function/task like '形態素解析') across a handful of criteria chosen for that comparison, rendered as a ○/△/✕ table. Use when the user wants a side-by-side comparison of multiple Japanese NLP tools/libraries/datasets, not just the single best one. Trigger phrases include 'X と Y と Z を比較して', '形態素解析ライブラリを比較', 'MeCab と Sudachi どっちがいい', 'どのツールを使うべき', 'compare japanese tokenizers', 'mecab vs sudachi vs janome', 'which embedding model should I use', '日本語NERライブラリの比較表', 'pros and cons of japanese OCR tools'. For a single ranked list use search; for alternatives to one specific tool (or contribution candidates) without a multi-axis table, use discover.

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name: discover

description: Given a Japanese NLP GitHub repo/model/dataset (URL / owner/repo / tool name) OR a topic, find what's already in awesome-japanese-nlp-resources and discover related resources NOT yet listed (contribution candidates). Mines the bundled dataset, then expands via web research across GitHub and Hugging Face. Use when the user names a SPECIFIC repository, model, or tool and wants alternatives/equivalents, OR wants to discover Japanese NLP resources for a topic that are NOT yet in the list, OR wants to prepare a contribution. Trigger phrases include 'mecabに似たツール', 'fugashiの代替', 'alternatives to fugashi', 'repos like manga-ocr', 'what else is like sudachi', 'リストに無い新しい日本語NLP', 'awesome-japanese-nlpに追加できそうな', '最近公開された日本語NLPツール', 'find unlisted Japanese NLP repos', 'new Japanese models on Hugging Face', 'contribute a new resource'. For a simple lookup of what already exists, use the search skill instead.

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name: research

description: Analyze current trends and challenges in Japanese NLP for a topic. Surveys the existing awesome-japanese-nlp-resources dataset and augments it with up-to-the-minute web research to produce a combined trend + issue report. Use only when the user explicitly wants a trend/landscape report, a challenges/limitations report, or a general research overview of a Japanese NLP topic (this combines the bundled dataset with live web research). Trigger phrases include '日本語LLMの最新トレンド', '〜の動向をまとめて', '最近の日本語NLPの流れ', '日本語LLMの課題', '〜の問題点・限界', '未解決の論点', 'trend report on Japanese embeddings', 'latest Japanese speech models', 'challenges in Japanese NER', 'limitations of Japanese embeddings'. For a simple lookup use the search skill; this one runs web research.

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name: search

description: Search all Japanese NLP resources (libraries, models, datasets, tutorials, dictionaries, Hugging Face). Accepts keywords or natural language questions in any language. Use whenever the user asks which Japanese NLP resource to use, or wants to find one: tokenizers / morphological analyzers, BERT or LLM models, embeddings, NER, text classification, datasets / corpora, dictionaries, tutorials, or Hugging Face models. Trigger phrases include '日本語の形態素解析ライブラリ', 'おすすめの日本語tokenizer', '日本語BERTモデル', '日本語の感情分析データセット', '日本語LLM 一覧', 'which Japanese embedding model', 'Japanese NER library'.

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name: skills-manager-cli

description: Drive the Skills Manager CLI (`skm`) to initialize the hub, adopt unmanaged skills, list/enable/disable skills per AI tool, and doctor/fix symlink sync. Use whenever the user or an agent needs to manage skills from a terminal, SSH session, CI job, or headless machine; when a skill is missing in Claude Code, Codex, Cursor, Gemini, OpenCode, or any other supported tool; when asked to run skm / Skills Manager CLI; or when setting up Skills Manager without the GUI. Do not use for `npx skills` / skills.sh search (different CLI), for writing SKILL.md content (skill-creator), or for marketplace browse/install (not in skm).

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name: mvp-plan

description: Plan the MVP build from a PRD and an MVP scope, as a full development plan or an ultra-lean build spec, with the AI Product Development Toolkit's planning prompts.

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name: nextjs-supabase-vercel

description: Set up the current empty folder with the AI App Starter, so the agent builds a Next.js, Supabase and Vercel app with the owner step by step, from idea to launch.

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name: prd

description: Interview the owner about a product idea, then draft a Product Requirements Document (PRD) with the AI Product Development Toolkit's PRD prompt.

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name: remotion-video

description: Make a short video about a product or brand (promo, launch, explainer, demo or social clip) entirely in code with Remotion, from idea to a rendered MP4 with sound. The owner approves the idea and a storyboard before anything is built.

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name: test-plan

description: Draft a test plan outline (scope, test types, environments, and entry and exit criteria) through a guided interview, with the AI Product Development Toolkit's test plan prompt.

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name: user-research

description: Plan a user research questionnaire, or turn collected responses into evidence-linked input for a PRD, with the AI Product Development Toolkit's research prompts.

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name: ux

description: Turn a PRD into UX specifications (screens, user flows and interaction patterns) through a guided interview, with the AI Product Development Toolkit's UX prompt.

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name: high-stakes-analytics-decision-lab

description: Build or review source-backed descriptive, diagnostic, predictive, and prescriptive analysis for consequential decisions. Use when an agent must profile and safely prepare uploaded data, turn a real dataset or research question into a reproducible study, investigate drivers without overstating causality, validate a model, compare feasible actions under dependent uncertainty and tail risk, trace every parameter to evidence and approval, or produce an answer-first analytical report across health, business, finance, policy, engineering, operations, behavioral science, AI, or planning.

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name: mindmemos-cli

description: Give an AI agent persistent, cross-session long-term memory through MindMemOS. Covers installing and authenticating the mindmemos CLI, the full command interface (add / search / get / update / delete / feedback / dreaming) with parameters and examples, guidance on which capability to use when, plus a Python SDK example. To wire memory into a specific agent host (OpenClaw, DeepSeek Harness, Codex, Claude, etc.), see references/.

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name: xlsx

description: Use this skill whenever the user wants to do anything with Excel spreadsheet files (.xlsx, .xls, .csv). This includes reading data, writing formulas, manipulating cells, formatting, filtering, creating charts, pivot tables, and any spreadsheet automation tasks.

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name: learn-from-materials

description: Turn books, PDFs, slides, documents, web pages and text into a source-grounded knowledge base, interactive learning HTML and Markdown in English or Chinese. Use for learning, summaries, explanations, review, quizzes, relationship maps, saving reusable methodology files, retrieving or comparing accumulated methods, and applying them to a real problem. 将材料转为可追溯知识库与交互学习页，支持中英文、关系图、方法论保存/检索/比较及应用；区分材料依据、推断与外部核验。

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name: add-azuredevops

description: Adds Azure DevOps connector to a Power Apps code app. Use when querying work items, creating bugs, managing pipelines, or making ADO API calls.

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name: add-connector

description: Use when adding a Power Platform connector to an Expo/React Native Power Apps mobile app and no dedicated mobile connector skill exists.

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name: add-connector

description: Adds any Power Platform connector to a Power Apps code app. Generic fallback for connectors not covered by a specific skill.

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name: add-data-source

description: Guide the user to add a data source, connection, or API connector to a Canvas App via Power Apps Studio, then verify and continue. USE WHEN the user asks to add a data source, add a connection, add an API, add a connector, connect to SharePoint / Dataverse / SQL / Excel / OneDrive / Teams / Office 365, or any similar request to make new data available to the app. DO NOT USE WHEN the user is asking to list or describe existing data sources — call list_data_sources or list_apis directly instead.

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name: add-datasource

description: Use when adding an unspecified data source to an Expo/React Native Power Apps mobile app; routes to Dataverse, SharePoint, or another connector.

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name: add-datasource

description: Adds a data source or connector to a Power Apps code app. Asks what the user wants to accomplish and routes to the appropriate specialized skill.

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name: add-dataverse

description: Use when the user wants to add Dataverse tables (existing or new) to a Power Apps mobile app, extend an existing Dataverse table with new columns, or apply an approved data model plan.