Review Markdown documents using the MRSF (Sidemark) sidecar format. Use when asked to review, comment on, or provide feedback on Markdown files. Adds structured, anchored review comments via the MRSF MCP server.
Guide for creating custom Claude Code subagents. Use when user wants to create a new agent (or update an existing agent) that handles specific types of tasks with custom prompts, tool restrictions, and permissions. Triggers on requests to create agents, subagents, custom agents, or when user wants specialized AI assistants for specific workflows.
Azure上にデプロイされたリソースのセキュリティ構成を評価し、Azure Security Benchmark v3およびCIS Benchmarksに準拠しているかを検証する。 IAM、ネットワークセキュリティ、データ暗号化、Defender for Cloud、ログ監視、Azure Policyを確認する。 「Azureのセキュリティ監査」「クラウドセキュリティ監査」「Azure監査」「IAM監査」「NSG監査」等のキーワードで使用する。 --- # Azureクラウド セキュリティレビュー ## 目的 Azure上にデプロイされたリソースのセキュリティ構成を評価し、Azure Security Benchmark v3およびCIS Benchmarksに準拠しているかを検証する。 ## 前提条件 - Azure CLIがインストールされ、対象サブスクリプションにログイン済みであること - 対象リソースグループへの読み取り権限（Reader以上）を持っていること ## 作業指示 1. **Azure環境の全体把握を行う** - 以下のコマンドでリソースの全体像を確認する： ```bash # サブスクリプション一覧 az account list --output table # リソースグループ一覧 az group list --output table # リソース一覧 az resource list --resource-group <rg-name> --output table ``` 2. **IAM（Identity and Access Management）を検証する** - 以下を確認する： ```bash # ロール割り当ての確認 az role assignment list --all --output table # カスタムロールの確認 az role definition list --custom-role-only true --output table ``` - 検証項目： - マネージドID（Managed Identity）が使用されているか - サービスプリンシパルにパスワード認証ではなく証明書認証が使用されているか - 最小権限の原則が適用されているか（Owner権限の付与が最小限か） - ゲストユーザのアクセスが適切に制限されているか - Privileged Identity Management（PIM）が有効化されているか 3. **ネットワークセキュリティを検証する** - 以下を確認する： ```bash # NSGルールの確認 az network nsg list --output table az network nsg rule list --nsg-name <nsg-name> --resource-group <rg-name> --output table # パブリックIPの確認 az network public-ip list --output table # VNet構成の確認 az network vnet list --output table ``` - 検証項目： - 不要なインバウンドルール（0.0.0.0/0からのSSH/RDP）がないか - プライベートエンドポイントが使用されているか - WAF（Web Application Firewall）が適用されているか - DDoS Protection が有効化されているか 4. **データ保護・暗号化を検証する** - 以下を確認する： ```bash # Key Vaultの確認 az keyvault list --output table az keyvault show --name <vault-name> # ストレージアカウントの確認 az storage account list --output table az storage account show --name <account-name> --query "{httpsOnly:enableHttpsTrafficOnly,minimumTlsVersion:minimumTlsVersion,publicAccess:allowBlobPublicAccess}" ``` - 検証項目： - ストレージアカウントのパブリックアクセスが無効化されているか - HTTPSのみの通信が強制されているか - TLS 1.2以上が最小バージョンとして設定されているか - Key Vaultでシークレットが管理されているか - Key Vaultのソフト削除と消去保護が有効化されているか 5. **Mi
Provides structured code review process and checklist
> **网络ID**: football_league
Classify and score business risks so agents produce consistent, comparable assessments.
Project-specific build process for the Builder workflow. Builds frontend assets for claudecode_webui.
Accessibility (A11y) reviewer for WCAG 2.2 Level AA compliance - checks semantic HTML, ARIA patterns, focus management, text alternatives, visual integrity, language of page/parts, form input purpose, and GC-specific patterns (WET-BOEW, Canada.ca) in code changes following CAN/ASC - EN 301 549:2024
HealthClaw Guardrails (healthclaw.io) — FHIR agent guardrails for secure clinical data access via MCP. Supports FHIR R4 US Core v9 (stable) and R6 ballot3 (experimental). Use when: (1) Reading patient data through MCP with automatic PHI redaction, (2) Writing clinical resources with two-phase propose/commit and step-up auth, (3) Proxying requests to real FHIR servers (HAPI, SMART Health IT, Epic), (4) Auditing AI agent access to healthcare data, (5) Evaluating R6 Permission resources for access control decisions. 12 MCP tools with guardrail enforcement.
Find functions with high cyclomatic complexity, excessive length, or too many parameters. Use when the user asks to find complex code, complexity hotspots, refactoring candidates, or wants to improve code maintainability.
Use when user wants to audit long-term memory for stale, incorrect, outdated, or duplicate entries, or correct memory entries based on new information
Public main skill for the incubating analyzer framework. Use when the user wants to analyze captures, reconstruct pass/resource relationships, infer engine or material structure, or build reusable render knowledge instead of directly debugging a defect. This skill is the future entry for analyzer requests and currently provides the minimum intake contract only.
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
