Develop, review, or refactor Go services built with Anclax, including OpenAPI specs, handlers, service/business logic, database/sqlc changes, async tasks, and Wire dependency injection.
Routes Snowflake-related operations to Cortex Code CLI for specialized Snowflake expertise. Use when user asks about Snowflake databases, data warehouses, SQL queries on Snowflake, Cortex AI features, Snowpark, dynamic tables, data governance in Snowflake, Snowflake security, or mentions "Cortex" explicitly. Do NOT use for general programming, local file operations, non-Snowflake databases, web development, or infrastructure tasks unrelated to Snowflake.
Back up all agent data to GitHub — SQLite databases, Claude Code memory, identity, skills, brain notes. Use when the user says backup, back up, save everything, push to github, or snapshot. Also used by heartbeat for automated backups.
Generate a drt sync YAML configuration file. Use this skill whenever a user wants to create a new drt sync, connect a data warehouse table to an external service, or set up a Reverse ETL pipeline with drt. --- Create a drt sync YAML configuration file for the user. ## Steps 1. Ask the user for the following (or infer from context if already provided): - **Source table or SQL**: what data to sync (e.g. `ref('new_users')` or a SQL query) - **Destination**: where to send it (Slack, Discord, REST API, HubSpot, GitHub Actions, Google Sheets, PostgreSQL, MySQL, or other) - **Sync mode**: full (every run) or incremental (watermark-based, needs a cursor column) - **Frequency intent**: helps set `batch_size` and `rate_limit` 2. Generate a valid sync YAML using the exact field names from `docs/llm/API_REFERENCE.md`. 3. Output the YAML in a code block and suggest where to save it: `syncs/<name>.yml` 4. Show the command to validate and run it: ```bash drt validate drt run --select <name> --dry-run drt run --select <name> ``` ## Rules - Use `type: bearer` + `token_env` (never hardcode tokens) - Default `on_error: skip` for Slack/webhooks, `on_error: fail` for critical syncs - For incremental mode, always include `cursor_field` - Use `ref('table_name')` when the source is a single DWH table; raw SQL when filtering or joining - Jinja2 templates use `{{ row.<column_name> }}` — column names must come from the user ## Reference See `docs/llm/API_REFERENCE.md` for all fields, types, and defaults.
Extract project knowledge into structured Markdown documents. Analyzes source code to generate architecture docs, API docs, database design, and flow diagrams.
Add a new property to the AI agents database. Use when the user wants to add, create, or introduce a new column, property, field, or feature to track across all agents in the comparison matrix. Handles all four required steps - database updates, groups.json, table display, and GitHub issue templates.
Execute SQL, SPARQL, SPASQL, SPARQL-FED, and GraphQL queries against live data spaces and knowledge graphs via OpenLink's OpenAPI-compliant web services. Use this skill whenever the user wants to query a database, RDF store, or SPARQL endpoint; explore a knowledge graph or data space; asks "How to ...", "Define the term ...", or poses a question against a known article or graph context; or mentions linkeddata.uriburner.com, Virtuoso, OPAL, or OpenLink services. Full query templates are in references/query-templates.md — load that file before constructing any predefined query.
Tensorlake SDK for agent sandboxes and sandbox-native orchestration. Use when the user mentions tensorlake, or asks about Tensorlake APIs/docs/capabilities. Also use when the user is building AI agents or agentic applications that need sandboxed execution environments for agents and isolated tool calls, or durable workflow orchestration for agents (parallel map/reduce DAGs). Works with any LLM provider (OpenAI, Anthropic), agent framework (LangChain, CrewAI, LlamaIndex), database, or API as the infrastructure layer.
Design robust, scalable database schemas for SQL and NoSQL databases. Provides normalization guidelines, indexing strategies, migration patterns, constraint design, and performance optimization. Ensures data integrity, query performance, and maintainable data models.
Comprehensive website and web app audit covering security, UX, performance, accessibility, SEO, compliance, and revenue protection. Use this skill whenever the user asks to audit, review, check, or score a website or web application. Also use when the user says 'full-stack audit', 'UX audit', 'security audit', 'launch checklist', 'is my site ready to launch', 'check my site', 'review my code for issues', 'what did I miss', or any variation of wanting a comprehensive quality review before or after launch. This skill catches the issues that AI-built and vibe-coded sites consistently get wrong: client-side paywalls, exposed database tables, missing security headers, broken mobile layouts, and trust gaps that kill conversion. Triggers even if the user only asks about one area (e.g., 'check my security') because problems compound across categories.
Use when analyzing bash-approve hook decisions, finding commands that needed user approval, identifying candidates for auto-approval, or querying the telemetry database
基于东方财富专业数据库，支持自然语言查询金融数据，覆盖A股、ETF、债券、港美股、基金等全品类资产，含实时行情、公司信息、估值、财务报表等，数据实时、权威、全面，可用于投资研究、交易复盘、行业分析、信用研究、财报审计、资产配置、报告撰写等场景，一站式满足机构与个人投资分析、市场监控、数据检索等需求。返回结果包含数据说明及 xlsx 文件。
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:
