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Found 2,511 Skills
bkend.ai database expert skill. Covers table creation, CRUD operations, 7 column types, constraints, filtering (AND/OR, 8 operators), sorting, pagination, relations, joins, indexing, and schema management via MCP and REST API. Triggers: table, column, CRUD, schema, index, filter, query, data model, 테이블, 컬럼, 스키마, 인덱스, 필터, 쿼리, 데이터 모델, テーブル, カラム, スキーマ, インデックス, フィルター, 数据表, 列, 模式, 索引, 过滤, 查询, tabla, columna, esquema, indice, filtro, consulta, tableau, colonne, schema, index, filtre, requete, Tabelle, Spalte, Schema, Index, Filter, Abfrage, tabella, colonna, schema, indice, filtro, query Do NOT use for: authentication (use bkend-auth), file storage (use bkend-storage), platform management (use bkend-quickstart).
Jotai状態管理ライブラリのエキスパートスキル。Reactアプリケーションでのatomベースの状態管理を実装する際に使用。以下の場合にこのスキルを使用: (1) Jotaiのatom設計・実装 (2) 派生atom、非同期atom、atomFamilyの実装 (3) Jotaiのベストプラクティスに基づくリファクタリング (4) パフォーマンス最適化（selectAtom、splitAtom等） (5) 永続化（localStorage/sessionStorage連携） (6) TypeScript型定義 (7) テスト実装 ユーザーが「Jotai」「atom」「状態管理」に関する質問や実装依頼をした場合に発動。
Create and modify Google Docs documents. Read document content and structure, manage formatting, paragraphs, and styles. Use when working with Google Docs document management.
Search, read, and extract attachments from Apple Mail's local storage. Query emails by sender, recipient, subject, body, date, mailbox, and flags. Read raw RFC822 messages and extract file attachments.
Propose concrete, high-leverage product/UX improvements to increase a software project's appeal and retention. Use when asked to generate product improvement proposals, UX ideas, onboarding/doc improvements, packaging/pricing positioning suggestions grounded in repo evidence, and prioritized MVP plans (ideation only; no implementation).
Use this when the Discover (reverse engineering) of legacy projects tends to get out of control in coverage. You need to first conduct module classification (P0/P1/P2) and constrain the depth of reverse engineering, ensuring that high-ROI modules are made traceable first instead of "writing everything but making it unmaintainable."
HOWL v2 — Hunt, Optimize, Win, Learn. Nightly self-improvement loop for the WOLF autonomous trading strategy. Runs once per day (via cron) to review all trades from the last 24 hours, compute win rates, analyze signal quality correlation, evaluate DSL tier performance, identify missed opportunities, and produce concrete improvement suggestions for the wolf-strategy skill. v2 adds fee drag ratio (FDR) analysis, holding period bucketing, LONG vs SHORT regime detection, rotation cost tracking, cumulative drift detection, and gross vs net profit factor separation. Use when setting up daily trade review automation, analyzing trading performance, or improving an autonomous trading strategy through data-driven feedback loops. Requires Senpi MCP connection, mcporter CLI, and OpenClaw cron system.
Skill for creating custom lint rules by leveraging the existing linter ecosystems of various programming languages. This is a linter designed for AI Agents rather than humans, and its error messages function as correction instruction prompts for AI. Create custom rules in the `lints/` directory using standard methods for each language, including Rust (dylint), TypeScript/JavaScript (ESLint), Python (pylint), Go (golangci-lint), etc. Use this skill in the following scenarios: (1) When you want AI to enforce project-specific coding rules; (2) When you want to create lint rules that output AI-readable correction instructions when violations occur; (3) When you want to enforce naming conventions, structural patterns, and consistency rules through AI-driven linting. Triggers: "Create a linter rule", "Add a lint rule", "Enforce this pattern", "AI linter", "Custom lint", "Code rules", "Naming rules", "Structural rules", "create a linter rule", "add a lint rule", "enforce this pattern", "AI linter".
Review PRs, MRs, and Gerrit changes with focus on security, maintainability, and architectural fit. Leverages github, gitlab, or gerrit skills based on repository context. Use when asked to review my code, check this PR, review a pull request, look at a merge request, review a patchset, or provide code review feedback.
Use when rapidly growing Xiaohongshu following, implementing viral strategies, leveraging platform mechanics, or accelerating follower acquisition
Use this when you need to design viral content or referral programs that leverage social sharing and word-of-mouth to achieve exponential growth
Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test. Produces a complete positioning document, positioning statement, competitive alternatives map, and market category analysis. Use when the user wants to define or refine their market positioning, find their unique position, differentiate from competitors, craft a positioning statement, choose a market category, or figure out "how should we position this product." Triggers for "positioning", "how to position", "market position", "differentiation strategy", "positioning statement", "competitive positioning", "category strategy", "where do we fit in the market", "how are we different", "unique value proposition", or any request to define, sharpen, or rethink positioning. Works standalone — no prior startup-design or startup-competitors session needed, but leverages their output if available.