仕事効率化のスキル

Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

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Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.

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Evaluate and improve AI-generated output with explicit rubrics, reflection loops, and stop conditions. Use when building self-critique workflows, evaluator-optimizer pipelines, or acceptance gates for code, docs, analysis, or plans.

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Spec-driven development lifecycle — EARS requirements, technical design docs, implementation tracking, and contribution guidelines. Use when planning features, defining requirements, or managing project lifecycle.

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Map tasks to specialist agents. Use when choosing which agent for a job, comparing agent capabilities, or routing to React/Next.js/Playwright/docs/code-quality experts. Keywords: which agent, best agent for this, delegate to expert, agent capability mapping.

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。

Terraform, Pulumi, CloudFormation, and infrastructure as code for data platforms

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。

Guide for optimizing MSBuild build parallelism and multi-project scheduling. Only activate in MSBuild/.NET build context. USE FOR: builds not utilizing all CPU cores, speeding up multi-project solutions, evaluating graph build mode (/graph), build time not improving with -m flag, understanding project dependency topology. Note: /maxcpucount default is 1 (sequential) — always use -m for parallel builds. Covers /maxcpucount, graph build for better scheduling and isolation, BuildInParallel on MSBuild task, reducing unnecessary ProjectReferences, solution filters (.slnf) for building subsets. DO NOT USE FOR: single-project builds, incremental build issues (use incremental-build), compilation slowness within a project (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: binlog MCP server tools (expensive_projects, expensive_targets, project_target_times); falls back to dotnet build -m, dotnet build /graph, binlog replay + grep.

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Guide for interpreting ResolveProjectReferences time in MSBuild performance summaries. Only activate in MSBuild/.NET build context. Activate when ResolveProjectReferences appears as the most expensive target and developers are trying to optimize it directly. Explains that the reported time includes wait time for dependent project builds and is misleading. Guides users to focus on task self-time instead. Do not activate for general build performance -- use build-perf-diagnostics instead.

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Helps find, inspect, and compare .NET project templates. Resolves natural-language project descriptions to ranked template matches with pre-filled parameters. USE FOR: finding the right dotnet new template for a task, comparing templates side by side, inspecting template parameters and constraints, understanding what a template produces before creating a project, resolving intent like "web API with auth" to concrete template + parameters. DO NOT USE FOR: actually creating projects (use template-instantiation), authoring custom templates (use template-authoring), MSBuild or build issues (use dotnet-msbuild plugin), NuGet package management unrelated to template packages.

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。

Automate Sentry tasks via Rube MCP (Composio): manage issues/events, configure alerts, track releases, monitor projects and teams. Always search tools first for current schemas.

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。

Diagnose MSBuild build performance bottlenecks using binary log analysis. Only activate in MSBuild/.NET build context. USE FOR: identifying why builds are slow by analyzing binlog performance summaries, detecting ResolveAssemblyReference (RAR) taking >5s, Roslyn analyzers consuming >30% of Csc time, single targets dominating >50% of build time, node utilization below 80%, excessive Copy tasks, NuGet restore running every build. Covers timeline analysis, Target/Task Performance Summary interpretation, and 7 common bottleneck categories. Use after build-perf-baseline has established measurements. DO NOT USE FOR: establishing initial baselines (use build-perf-baseline first), fixing incremental build issues (use incremental-build), parallelism tuning (use build-parallelism), non-MSBuild build systems. INVOKES: binlog MCP server tools (overview, errors, search, items, properties); falls back to dotnet msbuild binlog replay + grep/cat when the MCP is unavailable.

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 task requires exhaustive unabridged output, complete files, or strict prevention of placeholders and skipped code.

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。

View, create, update, and delete calendar events

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。

Office productivity workflow covering document creation, spreadsheet automation, presentation generation, and integration with LibreOffice and Microsoft Office formats.

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。

Helps an AI assistant work with the Miraheze wiki farm — writing wiki requests that get approved, navigating ManageWiki, doing common how-to tasks (templates, skins, permissions, custom domains, backups), writing regex for MediaWiki search-and-replace, AND writing actual article and page content for Miraheze-hosted wikis. Miraheze does NOT ban generative AI; AI-written content is permitted (subject to per-wiki rules). MADE BY SQERSTERS

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。

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

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。

Read, send, draft, delete, and organize Gmail emails

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。

Search, read, create, and update Notion pages and databases. Supports knowledge capture, meeting prep, research documentation, and spec-to-task workflows.

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。

Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.

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。

Automate Supabase database queries, table management, project administration, storage, edge functions, and SQL execution via Rube MCP (Composio). Always search tools first for current schemas.

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。

Standardizes Makefile-based build and test workflows with reproducible targets. Use when creating or refining helpful build, test, and clean targets.

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。

Structured planning workflow for any coding task. Use at the start of every new feature, bug fix, refactor, or implementation request. Analyzes the project, asks up to 5 clarifying questions, creates a TODO.md, gets user approval, then executes task by task. Never writes code before a plan is approved.

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。

Decomposes a large implementation plan into small-model-sized tasks executed by supervised worker agents (e.g. Haiku) in dependency-ordered parallel waves, with a plan-first approval gate inside every task, file-based state for context compaction, and a hard escalation ladder. Use when a master plan or multi-workstream feature is too large for one session and should be executed cheaply by many small agents under frontier-model supervision.

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。

How to use windows-computer-use-mcp effectively — tool selection, focus rules, safety, and mission design.

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。