Use this skill when a user wants to add a new tool or integration (e.g., GitHub, Brave Search, Notion, etc.) that isn't currently available but can be imported from the MCP registry or via a direct URL.
Comprehensive kanban board and task management via ktui CLI. Use for project tracking, todo lists, task dependencies, workflow automation, and board management. Activates when user mentions boards, tasks, kanban, or project management. If the `ktui` command is not available, but `uv` is available utilize `uvx kanban-tui` instead.
Search for CLI commands and tools installed on your system. Use when you need to find specific functionality, discover available commands, or explore what CLI tools are available.
Persistent memory for coding agents. Query past decisions and learnings before starting work. Lerim watches your sessions, extracts what matters, and makes it available across every future session.
Show MEGA-Code help — available commands, output locations, skill and strategy structure, and usage tips.
Guide for querying and operating on data through the Agentic Data Protocol (ADP) MCP tools. This skill teaches how to use adp_discover, adp_describe, adp_validate, and adp_execute tools effectively. Use this skill whenever the user wants to explore available data resources, query data, look up records, insert new data, or update existing data through ADP — even if they don't mention "ADP" explicitly. Triggers include "find data", "query records", "look up customer", "insert rows", "update entries", "what data is available", "search for similar items", "show me the schema", or any data exploration and manipulation task where ADP MCP tools are connected. --- # ADP Skill — Data Access via Agentic Data Protocol This skill helps you interact with data through four ADP MCP tools that connect to an ADP Hypervisor. The Hypervisor is a policy-enforcing gateway that abstracts away backend differences (SQL databases, MongoDB, vector stores, file systems) behind a single intent-based interface. ## Core Workflow Always follow this sequence — each step builds on the previous one: ``` discover → describe → validate (optional) → execute ``` 1. **Discover** — Find what data resources are available 2. **Describe** — Read the usage contract for a specific resource (field schema, allowed operators, required predicates) 3. **Validate** — Dry-run your intent to catch errors before execution (recommended but optional) 4. **Execute** — Run the intent and get results Skipping `describe` leads to malformed intents because you won't know which fields exist, which predicates are required, or which operators are allowed. Always describe before building an intent. ## The Four MCP Tools ### 1. `adp_discover` — Browse Available Resources Find what data is available. Use filters to narrow results. **Parameters:** - `domain_prefix` (optional): Filter by domain, e.g. `"com.acme"` - `intent_class` (optional): `"LOOKUP"`, `"QUERY"`, `"INGEST"`, or `"REVISE"` - `keyword` (optional): Free-text search acr
Check if `mcp-app-builder` is available in the skills folder. If not, install it:
Discover available prompts in .prompts/
Skill index and overview — lists all available NeuroSkill skills, tools, and explains how skill loading works.
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:
