Query AutoRAG-Research pipeline results using natural language. Converts questions to SQL, executes safely (SELECT-only), returns formatted results. Auto-detects DB connection from configs/db.yaml or env vars. Use for pipeline comparison, metrics analysis, token usage.
Provides 10 endpoints under /api/ for querying data (execute_query), exploring metadata
跨学科专家研究方法。描述如何从网上的信息去采集、分析最靠谱、最真实的数据并进行分析研究的方法论框架。
Use when accessing Alchemy APIs for RPC calls, token balances, NFT metadata, asset transfers, transaction simulation, or Alchemy-specific features. Also use when the user mentions "SIWE", "SIWS", "x402", "MPP", "mppx", or "agentic gateway" — this skill covers wallet-based auth flows for Alchemy's x402 and MPP protocols on EVM (Ethereum, Base, Polygon) and SVM (Solana).
Use the local Notion CLI (notion-cli-agent) to query, create, update, and manage Notion pages and databases via shell. Use when interacting with Notion workspaces, querying databases, creating or updating pages, managing tasks, reading content blocks, or running bulk/batch operations on Notion data. Prefer over Notion MCP or API calls.
Run Cadence Spectre simulations remotely via virtuoso-bridge: upload netlists, execute, parse PSF results. TRIGGER when the user wants to run a SPICE/Spectre simulation from a netlist file, do transient/AC/PSS/pnoise analysis outside Virtuoso GUI, parse PSF waveform data, run multiple simulations in parallel across one or more servers, check simulation job status, or mentions Spectre APS/AXS modes. Also triggers for sim-jobs, sim-cancel, or parallel/concurrent simulation requests. Use this for standalone netlist-driven simulation — for GUI-based ADE Maestro simulation, use the virtuoso skill instead.
Complete CoinGecko Solana API integration for token prices, DEX pool data, OHLCV charts, trades, and market analytics. Use for building trading bots, portfolio trackers, price feeds, and on-chain data applications.
Set up build environment and test fixtures for COBOL-to-Java migrations. Creates compilation infrastructure for both languages and generates golden test data.
Structures AI and ML product decisions including model selection, data requirements, evaluation frameworks, and responsible AI considerations. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Triggers on "AI product", "LLM feature", "AI canvas", "build with AI", "AI integration", "AI-powered", "machine learning feature".
Build, validate, and manage semantic models using Sidemantic. Use when asked to create a semantic layer, define metrics/dimensions, model a database schema, generate models from SQL queries, import from Cube/dbt/LookML, or set up analytics definitions. Prioritizes CLI-first workflows, with YAML and optional Python API usage for advanced automation.
This skill should be used when the user wants to add one or more skills from GitHub repositories to the kilo-marketplace. It handles parsing GitHub URLs, cloning skill directories, and updating SKILL.md frontmatter with source metadata.
Automated design system construction from repository analysis to production-ready implementation. Analyzes codebases, extracts design patterns, builds token hierarchies with OKLCH color management, implements accessible components with tests, and verifies through multi-reviewer panels.
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:
