Use these skills when you need to provision new Cloud SQL instances, create databases and users, clone existing environments, and monitor the progress of long-running operations.
Access Elyan Labs GPU compute marketplace — V100, RTX 5070, POWER8 inference endpoints via x402 USDC micropayments
Build, critique, and iterate high-converting marketing or product landing pages using React + Vite + TypeScript + Tailwind and shadcn/ui components, with all icons sourced from Iconify. Use when the user asks for a landing page, sales page, signup page, CRO improvements, above-the-fold vs below-the-fold structure, hero + CTA copy, section order, or wants production-ready shadcn + Vite code.
Benchmark and optimize SDK, CLI, MCP, and prompt documentation so every LLM model can reliably call the right actions with correct arguments. Use when setting up skill-optimizer for a project, running benchmarks, interpreting results, optimizing SKILL.md files, or diagnosing configuration issues. Also use when working inside the skill-optimizer repository itself — for running against mock repos, testing changes, or understanding the codebase. --- # skill-optimizer Benchmark your SDK / CLI / MCP / prompt docs against multiple LLMs, measure whether they call the right actions with the right arguments, and iteratively rewrite your guidance until a quality floor is met across every model. ## Context Detection Before doing anything, figure out where you are: 1. **Look for `skill-optimizer.json`** (in CWD or parent directories). If found, you are in a **configured target project**. Use that file path as `<config-path>` in all commands below. 2. **Look for `src/cli.ts` and a `package.json` with `"name": "skill-optimizer"`**. If found, you are in the **optimizer repo itself**. You can use dev commands directly (`npm run build`, `npm test`, `npx tsx src/cli.ts`). To benchmark a target, either use the mock repos in `mock-repos/` or point `--config` at an external project's config. 3. **Neither found** — you are in an **unconfigured target project**. Read `references/setup.md` to scaffold a config before proceeding. ## Quick Reference | Task | Command | |------|---------| | Init config | `npx skill-optimizer init cli\|sdk\|mcp\|prompt` | | Init (non-interactive) | `npx skill-optimizer init cli --yes` | | Import CLI commands | `npx skill-optimizer import-commands --from ./src/cli.ts` | | Import (binary scrape) | `npx skill-optimizer import-commands --from my-cli --scrape` | | Diagnose config | `npx skill-optimizer doctor --config <config-path>` | | Auto-fix config | `npx skill-optimizer doctor --fix --config <config-path>` | | Dry run (no LLM calls) | `npx skill-optimizer run -
Git Context Controller (GCC) v2 — Lean agent memory backed by real git. Stores hash + intent + optional decision notes instead of verbose markdown. Auto-bridges to aiyoucli vector memory when available. Dual mode: git-backed (lean index.yaml) or standalone (markdown fallback). Triggers on /gcc commands or natural language like 'commit this progress', 'branch to try an alternative', 'merge results', 'recover context'.
Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to set up AGENTS.md, add intent layer, make agents understand the codebase, or scaffolding AI-friendly project documentation. --- # Intent Layer Hierarchical AGENTS.md infrastructure so agents navigate codebases like senior engineers. ## Core Principle **Only ONE root context file.** CLAUDE.md and AGENTS.md should NOT coexist at project root. Child AGENTS.md in subdirectories are encouraged for complex subsystems. ## Workflow ``` 1. Detect state scripts/detect_state.sh /path/to/project → Returns: none | partial | complete 2. Route none/partial → Initial setup (steps 3-5) complete → Maintenance (step 6) 3. Measure [gate - show table first] scripts/analyze_structure.sh /path/to/project scripts/estimate_tokens.sh /path/to/each/source/dir 4. Decide No root file → Ask: CLAUDE.md or AGENTS.md? Has root file → Add Intent Layer section + child nodes if needed 5. Execute Use references/templates.md for structure Use references/node-examples.md for real-world patterns
API security best practices and common vulnerability prevention. Enforces security checks for authentication, input validation, SQL injection, XSS, and OWASP Top 10 vulnerabilities. Use when building or modifying APIs.
Interact with GitHub using the `gh` CLI
ECS-first, agent-native game engine in Rust
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
钉钉 AI 表格（多维表格）操作。当用户提到"钉钉AI表格"、"AI表格"、"多维表格"、"工作表"、"字段"、"记录"、"新增记录"、"查询记录"、"更新记录"、"删除记录"、"新建字段"、"删除字段"、"dingtalk AI table"、"dingtalk notable"、"able文件"时使用此技能。支持工作表管理、字段管理、记录的增删改查等全部操作。
Performance comparison for trading strategies. Compare backtest vs actual results, strategy vs strategy metrics, or period vs period performance. Use when exploring differences between theoretical and live execution, understanding how two strategies relate, or analyzing performance across time periods.
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:
