Free to get · One-click to use
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
Build CLI applications with TimeWarp.Nuru - a .NET route-based CLI framework with web-style routing, source generators, and AOT support. Use when creating CLI tools, defining commands/queries, adding parameters or options, testing CLI output, or working with TimeWarp.Nuru.
Expert guidance for working with Dagster and the dg CLI. ALWAYS use before doing any task that requires knowledge specific to Dagster, or that references assets, materialization, components, data tools or data pipelines. Common tasks may include creating a new project, adding new definitions, understanding the current project structure, answering general questions about the codebase (finding asset, schedule, sensor, component or job definitions), debugging issues, or providing deep information about a specific Dagster concept. --- ## dg CLI The `dg` CLI is the recommended way to programmatically interact with Dagster (adding definitions, launching runs, exploring project structure, etc.). It is installed as part of the `dagster-dg-cli` package. If a relevant CLI command for a given task exists, always attempt to use it. ONLY explore the existing project structure if it is strictly necessary to accomplish the user's goal. In many cases, existing CLI tools will have sufficient understanding of the project structure, meaning listing and reading existing files is wasteful and unnecessary. Almost all `dg` commands that return information have a `--json` flag that can be used to get the information in a machine-readable format. This should be preferred over the default table output unless you are directly showing the information to the user. ## UV Compatibility Projects typically use `uv` for dependency management, and it is recommended to use it for `dg` commands if possible: ```bash uv run dg list defs uv run dg launch --assets my_asset ``` ## Core Dagster Concepts Brief definitions only (see reference files for detailed examples): - **Asset**: Persistent object (table, file, model) produced by your pipeline - **Component**: Reusable building block that generates definitions (assets, schedules, sensors, jobs, etc.) relevant to a particular domain. ## CRITICAL: Always Read Reference Files Before Answering NEVER answer from memory or guess at CLI commands, APIs, or syntax
Interact with GitHub via gh CLI
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
This skill should be used to review and audit the bt CLI for adherence to CLI best practices from clig.dev AND internal codebase patterns. It checks source code for help text, flags, error handling, output formatting, subcommand structure, pattern consistency, and more. Triggers on "review my code", "audit the CLI", "check CLI best practices", or /bt-review. --- # CLI Best Practices Review Audit the `bt` CLI codebase against two reference documents: 1. **clig.dev guidelines** — industry CLI best practices 2. **bt codebase patterns** — established internal conventions for consistency ## When to Use - When a user asks to review, audit, or check the CLI - When triggered via `/bt-review` - After implementing new commands or subcommands - Before releases to ensure CLI quality ## Review Process ### 1. Scope the Review
This skill should be used when the user asks to "log in", "check auth", "create API key", "revoke API key", "check health", "submit feedback", "view audit log", "feature flags", "shell completions", "account details", "accept terms", "validate token", "elnora setup", or any task involving Elnora Platform authentication, administration, or diagnostics. --- # Elnora Admin & Diagnostics Authentication, API key management, account settings, health checks, feature flags, audit logs, feedback, and shell completions. ## Invocation ``` CLI="uv run --project ${CLAUDE_PLUGIN_ROOT} elnora" ``` ## Authentication ### Login ```bash $CLI auth login $CLI --compact auth login --api-key <KEY> ``` Interactive login prompts for the API key and saves to `~/.elnora/config.toml`. The `--api-key` flag is insecure (visible in process listings) -- prefer interactive prompt or env var. Keys must start with `elnora_live_` and be 20+ characters. ### Check Auth Status ```bash $CLI --compact auth status # -> {"authenticated":true,"totalProjects":N} ``` Quick way to verify the CLI is properly configured. ### Logout ```bash $CLI --compact auth logout # -> {"loggedOut":true,"removed":"~/.elnora/config.toml"} ``` Removes saved credentials from disk. ### Validate Token ```bash $CLI --compact auth validate $CLI --compact auth validate --token <TOKEN> ``` Validates the current API key (or a specific token). Useful for debugging auth issues. ## API Key Management ### Create API Key ```bash $CLI --compact api-keys create --name "CI Pipeline" $CLI --compact api-keys create --name "Agent Key" --scopes "read,write" ``` | Flag | Required | Notes | |------|----------|-------| | `--name` | Yes | Key name for identification | | `--scopes` | No | Comma-separated scope list | **IMPORTANT:** The key value is only shown once in the response. Store it securely. ### List API Keys ```bash $CLI --compact api-keys list ``` ### Revoke API Key ```bash $CLI --compact api-keys revoke <KEY_ID> # -> {"revoked":true,"keyId":"..
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, or reading/injecting/running secrets via op.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
AI驱动的电商评论深度分析工具,支持CLI本地模式和Gemini增强模式。提供22维度智能标签、黑金奢华可视化看板、四位一体VOC系统(6套3D头像)。 触发词使用场景: - 用户需要分析电商产品评论(Amazon/eBay/AliExpress等) - 用户想要生成产品洞察报告和机会点分析 - 用户需要从评论中提取用户画像和VOC - 用户需要创建专业的可视化分析看板 - 用户提到"电商评论分析"、"评论分析"、"竞品分析"、"用户洞察"、"VOC分析"等关键词 核心能力: - 双模洞察系统: CLI本地模式(使用内置模型) + Gemini增强模式(API付费) - 22维度智能标签系统: 人群/场景/功能/质量/服务/体验/市场/情感 - 黑金奢华可视化看板: 董事会高管汇报级别HTML报告 - 四位一体VOC系统: 6套3D头像,立体化用户画像 - 三位一体输出: CSV标签数据 + Markdown洞察报告 + HTML可视化看板 强制交互约束(绝对级): ❗ 无论任何情况,当用户触发评论分析时,AI Agent 必须先通过 AskUserQuestion 工具依次向用户收集以下三个参数,再执行分析命令: 1. 分析数量(多少条评论) 2. AI引擎模式(CLI/混动/Gemini) 3. 报告署名 严禁自行填充默认值或猜测用户意图。这是本 Skill 的最高优先级规则。 如果用户明确表示"都用默认值"或"你决定",才可以使用默认值(100条/模式1/AI Assistant)。 渐进式披露逻辑: 1. 首次使用时,引导用户克隆主仓库并安装依赖 2. 提供清晰的快速开始命令和参数说明 3. 遇到问题时,引导用户查看主仓库文档 4. 强调双模洞察系统的成本差异和使用场景 技术要求: - Python 3.9+ - Claude Code CLI(CLI本地模式必需) - Gemini API Key(Gemini增强模式可选)
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 AI semantic + 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:
