- 📄 SKILL.md
dataverse-sdk-dev
Development guidance for contributing to the PowerPlatform Dataverse Client Python SDK repository. Use when working on SDK development tasks like adding features, fixing bugs, or writing tests.
Development guidance for contributing to the PowerPlatform Dataverse Client Python SDK repository. Use when working on SDK development tasks like adding features, fixing bugs, or writing tests.
Guide for using Kimi API utilities (session management, prompts, colorful printing, threading)
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
This skill should be used when the user asks to "콘텐츠 만들어줘", "카드뉴스 만들어줘", "카드뉴스 영상 만들어줘", "리서치부터 영상까지", "콘텐츠 파이프라인", "content pipeline", "주제로 콘텐츠 만들어줘". 주제 하나로 리서치→카드뉴스→영상까지 풀 파이프라인을 자동 실행합니다. Make sure to use this skill whenever the user mentions content creation that involves research, card news, or video generation from a topic.
Analyze a CLAUDE.md file and generate PreToolUse hook scripts that enforce its rules at the tool-call level. Use when users want their CLAUDE.md directives enforced as code rather than relying on prompt compliance. Reads the CLAUDE.md, identifies enforceable rules, generates standalone bash hook scripts, and wires them into .claude/settings.json.
Guide for adding a new feature to OhMyCode. Use when user wants to add functionality that goes beyond existing extension points (tools/providers). Always start by reading docs/DEVELOPMENT_GUIDE.md.
Guide to Control Tower's AI control concepts. Use when the user asks about control protocols, blue team and red team roles, usefulness, safety, audit budgets, trusted monitoring, or the conceptual model behind Control Tower.
A skill to create a pull request on a GitHub repository. Use this skill when the user wants to create a pull request for the changes you have made.
Build durable, fault-tolerant workflows using Azure Durable Functions with .NET isolated worker and Durable Task Scheduler backend. Use when creating serverless orchestrations, activities, entities, or implementing patterns like function chaining, fan-out/fan-in, async HTTP APIs, human interaction, monitoring, or stateful aggregators. Applies to Azure Functions apps requiring durable execution, state persistence, or distributed coordination with built-in HTTP management APIs and Azure integration.
Create, produce, and publish UGC-style short-form video reels at scale. Full pipeline: source UGC reaction hooks from DanSUGC, analyze app demos with Gemini AI, assemble reels with ffmpeg, publish via DanSUGC Posting (TikTok + Instagram), track performance and research viral formats/hooks via DanSUGC's built-in analytics proxy.
System architecture and design thinking — requirements analysis, component design, data modeling, scaling strategy, and trade-off analysis. Use when: "design this system", "what's the architecture for", "trade-offs for X", "how should we architect", "system design for", "API design", "data model for", "service boundaries", "architecture doc", "create an ADR". When the design thinking is done, this skill hands off to /ship:write-docs to write the design document. Note: this is NOT for visual design (use /ship:visual-design) or implementation planning (use /ship:design). --- # Architectural Design Think through system design decisions rigorously before writing them down. This skill is about the **thinking** — requirements, components, trade-offs, boundaries. When the design is ready, you MUST invoke `Skill("write-docs")` to write the design document — do not write the doc inline. ## Scale to Complexity Not every decision needs all 5 phases. Match the depth to the decision: - **Small** (single component, clear constraints) — Phase 1 briefly, Phase 2, Phase 5. Skip deep dive and scaling. - **Medium** (multi-component, some unknowns) — All 5 phases, but keep each concise. - **Large** (new system, significant unknowns, cross-team) — All 5 phases in full depth, with diagrams and explicit load estimates. ## Red Flag **Never:** - Skip requirements gathering and jump straight to a solution - Design without understanding existing constraints (tech stack, team, timeline) - Omit trade-off analysis — every decision has alternatives that were rejected for a reason - Skip the Boundaries section — it's the core anti-drift mechanism - Propose a design without verifying assumptions against the actual codebase - Conflate "what we want" with "what exists" — be explicit about the gap ## Phase 1: Requirements Gathering Before designing anything, understand what you're solving. ### Functional Requirements - What must the system do? List concrete capabilities. - What are the input/output co
Manages Architecture Decision Records (ADR) for tracking important architectural decisions
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: