4,982 件 ・ 関連度順
概要と使いどころ
Verify a factual claim — "check this claim", "verify this", "is this true", "how solid is this". Finds primary sources and rates the evidence as supported, mixed, unsupported or unverifiable, with citations.
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。
Identify and fix typos and grammar mistakes in a file, limited to syntax errors only. Use when user asks to find or fix typos, grammar mistakes, spelling, or syntax errors in a file. Does not suggest editorial or style changes.
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。
Azure DevOps pull requests, for repos whose git remote is on dev.azure.com or *.visualstudio.com. Covers comment threads, which `az repos pr` cannot read or post. Use to create a PR for the current branch, check out, list or complete PRs, post code comments on a PR, reply to threads, and assess whether review feedback was addressed. Trigger on "create PR", "checkout PR 123", "list PRs", "complete PR", "comment on the PR", "post these review findings", "check PR feedback", "/dev-azdo:pr".
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。
Discovers and integrates third-party APIs using the context-matic MCP server. Uses `fetch_api` to find available API SDKs, `ask` for integration guidance, `model_search` and `endpoint_search` for SDK details. Use when the user asks to integrate a third-party API, add an API client, implement features with an external API, or work with any third-party API or SDK.
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。
Find and own a defensible market position. Use when messaging sounds like competitors, conversion is weak despite awareness, repositioning a product, or testing positioning claims. Includes Crawl-Walk-Run rollout methodology and the word change that improved enterprise deal progression.
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。
Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP as the default, with Context7 and Aspire MCP for content that lives outside learn.microsoft.com.
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。
Analyze V8 heap snapshots to investigate memory leaks and retention issues. Use when given .heapsnapshot files, asked to compare before/after snapshots, asked to find what retains objects, or investigating why objects survive GC. Provides snapshot parsing, comparison, retainer-path helpers, and scratchpad 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。
Enable code intelligence (go-to-definition, find-references, hover, type info) for any programming language by installing and configuring an LSP server for Copilot CLI. Detects the OS, installs the right server, and generates the JSON configuration (user-level or repo-level). Use when you need deeper code understanding and no LSP server is configured, or when the user asks to set up, install, or configure an LSP server.
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。
Launch new products from idea to first customers. Use when launching products, finding early adopters, building launch week playbooks, diagnosing why adoption stalls, or learning that press coverage does not equal growth. Includes the three-layer diagnosis, the 2-week experiment cycle, and the launch that got 50K impressions and 12 signups.
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。
Investigate and fix CI failures on a pull request. Use when CI checks fail on a PR branch — covers finding the PR, identifying failed checks, downloading logs and artifacts, extracting the failure cause, and iterating on a fix. Requires the `gh` CLI.
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。
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-*.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating user timing marks.
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。
Prepare for tomorrow's meetings and tasks. Pulls calendar from Outlook via WorkIQ, cross-references open tasks and workspace context, classifies meetings, detects conflicts and day-fit issues, finds learning and deep-work slots, and generates a structured HTML prep file with productivity recommendations.
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。
Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review.
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。
Find ITINAI agents, post service agents, and make reviewed A2A service requests.
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。
Trust scoring, agent discovery, profiling, wallet/identity lookup, contact, dispatch, and metadata reads/writes via 8K4 Protocol (ERC-8004). Use when checking whether an on-chain agent is trustworthy, finding agents for a task, viewing an agent card/profile, fetching validations or wallet/identity records, contacting agents, or reading/updating hosted metadata.
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 skill marketplace integration for A2A Market. Enables agents to buy skills, sell skills, and earn money autonomously. Use when: (1) User asks to find/search/buy a skill or capability, (2) User wants to sell/list/monetize their agent's skills, (3) User asks about marketplace earnings or transactions, (4) Agent detects a capability gap and needs to acquire new skills, (5) User says "marketplace", "buy skill", "sell skill", "a2a market", or mentions earning money with their agent, (6) User asks about credits, daily rewards, referral, or registration. Supports x402 USDC payments on Base L2 and Credits payment system.
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。
Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring. Prefer JSON output and non-interactive flows.
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。
Roleplay the most difficult, tech-resistant user for your product. Browse the app as that persona, find every UX pain point, then filter complaints through a pragmatism layer to separate real problems from noise. Creates actionable tickets from genuine issues 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。
Design or improve search experiences, result presentation, and filtering interfaces. Use when the user asks to add search, redesign search results, improve findability, build autocomplete, add filters, or fix zero-results dead ends.
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。
Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants measurable accessibility, performance, responsive, theming, or anti-pattern findings—not when they mainly want an overall UX critique or final visual/detail polish.
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。
Surface architectural friction and propose deepening opportunities that improve testability and AI-navigability. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase easier for agents to navigate.
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。
Run the full Forge pipeline unattended: each phase is reviewed by a fresh evaluator subagent, the findings feed back, and the run advances itself. Use when the user runs /forgemaster-auto or wants a feature built end to end without approval gates.
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。
Identifies outdated elements in provided content and suggests updates to maintain freshness. Finds statistics, dates, and examples that need updating. Use PROACTIVELY for older content.
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。
This skill provides symbol-level code understanding and navigation using Language Server Protocol (LSP). Enables IDE-like capabilities for finding symbols, tracking references, and making precise code edits at the symbol level.
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。