Define database schemas in JSON and generate migration plans. Use this skill when creating or modifying database models, defining tables with columns, constraints, and ENUM types for Vespertide-based projects.
Query TickFlow Assist LanceDB tables, schemas, and stored records through the query_database tool.
Interact with Notion using the unofficial private API - pages, databases, blocks, search, users, comments
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, Microsoft Teams, REST API, HubSpot, GitHub Actions, Google Sheets, PostgreSQL, MySQL, ClickHouse, Parquet, CSV/JSON/JSONL, Jira, Linear, SendGrid, Staged Upload (async bulk APIs), or other) - **Sync mode**: full (every run), incremental (watermark-based, needs cursor column), upsert (dedup by key), or replace (TRUNCATE + INSERT for full table refresh) - **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.
Ash Framework database access rules: domain code interfaces, migrations, actor authorization, atomic changes
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.
1C metadata management — create, edit, validate, and remove configuration objects (catalogs, documents, registers, enums), managed forms, data composition schemas (SKD), spreadsheet layouts (MXL), roles, external processors (EPF/ERF), extensions (CFE), configurations (CF), databases, subsystems, command interfaces, templates. Use when working with 1C metadata structure — NOT for general BSL code writing.
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.
Administer an Omni Analytics instance — manage connections, users, groups, user attributes, permissions, schedules, and schema refreshes via the Omni CLI. Use this skill whenever someone wants to manage users or groups, set up permissions on a dashboard or folder, configure user attributes, create or modify schedules, manage database connections, refresh a schema, set up access controls, provision users, or any variant of "add a user", "give access to", "set up permissions", "who has access", "configure connection", "refresh the schema", or "schedule a delivery".
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.
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:
