Best Data & AI Skills for VS Code

steipete/taskflow-inbox-triage

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data-ai

Example TaskFlow authoring pattern for inbox triage. Use when messages need different treatment based on intent, with some routes notifying immediately, some waiting on outside answers, and others rolling into a later summary.

steipete/prose

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data-ai

OpenProse VM skill pack. Activate on any `prose` command, .prose files, or OpenProse mentions; orchestrates multi-agent workflows.

openclaw/prose

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data-ai

OpenProse VM skill pack. Activate on any `prose` command, .prose files, or OpenProse mentions; orchestrates multi-agent workflows.

obra/verification-before-completion

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data-ai

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

affaan-m/email-ops

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data-ai

Evidence-first mailbox triage, drafting, send verification, and sent-mail-safe follow-up workflow for ECC. Use when the user wants to organize email, draft or send through the real mail surface, or prove what landed in Sent.

affaan-m/agentic-engineering

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data-ai

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

affaan-m/team-agent-orchestration

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data-ai

Run team-based orchestration for agent squads using work items, ownership, agent Kanban, merge gates, and control pane handoffs. Use when coordinating an agent squad with work items, ownership, Kanban, and merge gates.

affaan-m/swift-actor-persistence

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data-ai

Thread-safe data persistence in Swift using actors — in-memory cache with file-backed storage, eliminating data races by design. Use when persisting data in Swift and a data race or thread-safety problem needs designing out.

affaan-m/redis-patterns

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data-ai

Redis data structure patterns, caching strategies, distributed locks, rate limiting, pub/sub, and connection management for production applications. Use when adding caching, a distributed lock, rate limiting, or pub/sub with Redis, or when key design needs review.

affaan-m/android-clean-architecture

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data-ai

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

affaan-m/iterative-retrieval

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data-ai

Pattern for progressively refining context retrieval to solve the subagent context problem. Use when a subagent lacks the context it needs and retrieval must be refined across passes.

affaan-m/openclaw-persona-forge

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data-ai

为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡， 输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。 如当前环境提供已审核的生图 skill，可自动生成统一风格头像图片。 当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。 不适用于：微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。 触发词：龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、 龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。 Use when creating, designing, or customizing an OpenClaw lobster persona — identity, SOUL.md, name, or avatar prompt.

affaan-m/santa-method

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data-ai

Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships. Use when output must clear two independent adversarial reviewers before it ships.

affaan-m/kotlin-exposed-patterns

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data-ai

JetBrains Exposed ORM patterns including DSL queries, DAO pattern, transactions, HikariCP connection pooling, Flyway migrations, and repository pattern. Use when working with the Exposed ORM — DSL or DAO queries, transactions, pooling, or migrations.

affaan-m/ito-data-atlas-agent

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data-ai

Design source-grounded Data Atlas style agents for Itô basket research, market discovery, parameter drafting, and human-in-the-loop editing. Use for architecture and read-only workflow planning, not live order execution.

affaan-m/token-budget-advisor

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data-ai

在回答前，为用户提供关于消耗多少响应深度的知情选择。当用户明确希望控制响应长度、深度或令牌预算时使用此技能。触发条件："token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar cuánto usas"，或用户明确要求控制答案大小或深度的清晰变体。不触发条件：用户已在当前会话中指定了级别（保持该级别），请求明显是单字答案，或"token"指代认证/会话/支付令牌而非响应大小。

affaan-m/data-throughput-accelerator

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data-ai

Use when large data ingestion, backfill, export, ETL, warehouse loading, manifest catch-up, or table synchronization needs to become much faster while preserving data correctness.

affaan-m/token-budget-advisor

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data-ai

回答する前に、どれだけの回答深度を消費するかについてユーザーに情報に基づいた選択を提供する。ユーザーが回答の長さ、深さ、またはトークンバジェットを明示的に制御したい場合にこのスキルを使用する。トリガー条件："token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar cuánto usas"、またはユーザーが回答のサイズや深さの制御を明示的に求めるその他の明確なバリエーション。トリガーしない条件：ユーザーが現在のセッションでレベルを指定済み（そのレベルを維持）、リクエストが明らかに一言の回答、または「token」が認証/セッション/支払いトークンを指している。

mattpocock/claude-handoff

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data-ai

Hand the current conversation off to a fresh background agent that picks up the work immediately.