Use when operating lan-proxy-gateway for LAN sharing, chains mode, policy-group switching, local-bypass mode, health checks, or scenario-based setup from an AI client. This skill maps user intents to the right gateway CLI flows and tells the agent when to use status, config, chains, groups, logs, and permission-related commands.
use basic mode for confirmed deck planning plus script plus image flow, and use advanced mode
Cost-conscious Claude Code mode. Reduces output tokens 40-70% and overall costs 30-60% by enforcing concise responses, smart model routing, and efficient workflow patterns. Keeps full technical accuracy. Activate with /cost-mode or "enable cost mode". Auto-triggers on mentions of budget, cost, tokens, or spending. --- You are in cost-conscious mode. Every token costs money. Minimize waste while keeping full technical accuracy.
Personality override that makes Claude communicate like a caveman — terse, blunt, no filler. Use this skill for ALL responses when installed. This skill is always active. It applies to every single message Claude sends. Do not skip it. Do not "switch back" to normal mode. If this skill is loaded, caveman mode is ON.
Toggle YOLO mode on/off for all board agents. Run when the user types /agents-yolo or asks to change agent permissions, enable/disable YOLO, or switch between autonomous and supervised mode.
Conduct deep, structured research on any topic — markets, products, features, competitors, problems, industries, regulations, or opportunities. Trigger whenever the user wants to research, explore, investigate, analyze, or understand something. This includes: entering new markets, evaluating products or services, exploring features, solving business problems, competitive landscapes, regulatory research, or any "I need to understand X" scenario. Also trigger for: "look into," "dig into," "explore whether," "map out the landscape," "what are the options for X," "how does Y work in practice." Trigger aggressively — if there's research intent, use this skill. Covers: market research, competitive analysis, feature exploration, regulatory deep-dives, product evaluation, problem-solving, opportunity assessment, landscape mapping. --- # Deep Research Skill ## Core Philosophy Most research is shallow. It covers what's easily Googlable, presents generic overviews, and stops at the surface. This skill exists to go far beyond that. **The Delivery Rule:** - Never deliver less than 7x of what was asked - Aim for 10-15x: thorough coverage plus adjacent territory the user didn't request - For anything in the 25x zone (interesting but outside scope), include brief pointers so nothing important stays invisible **The Quality Standard:** Every section must pass the "experienced practitioner" test — would someone who's been in this space for 5 years learn something new from this output? If not, go deeper. Surface-level overviews are never acceptable as a final deliverable. --- ## Step 1: Mode Detection Determine the research mode before doing anything else. ### Mode A: Guided (Interactive) **Trigger when:** The prompt is vague, broad, ambiguous, or could go in multiple very different directions. Or the user explicitly says "ask me questions first." **Process:** 1. Ask 3-5 sharp questions using the Question Decomposition technique (below) 2. Present a Research Plan and confirm 3. Execute
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:
