- 📁 bad-examples/
- 📁 context/
- 📁 good-examples/
- 📄 SKILL.md
prd-generator
소크라틱 질문 기반 PRD 생성 — PM의 가정을 도전하고, 복수 옵션을 제시하며, 견고한 PRD를 만드는 AI PM 스킬
12 days ago · Uploaded
Detail →
Daily Featured Skills Count
04/06
04/07
04/08
04/09
04/10
04/11
04/12
♾️ Free & Open Source 🛡️ Secure & Worry-Free
Import Skills
- 📄 SKILL.md
prd-methodology
PRP (Product Requirement Prompt) methodology for writing PRDs. Reference for best practices in structuring requirements documents for coding agents. --- # PRP Methodology — Quick Reference The PRP (Product Requirement Prompt) framework is a structured process for creating PRDs that coding agents can execute in a single pass. ## Core Principle A PRD must contain ALL context needed for implementation. If a fresh Claude session with only the PRD can't build the feature correctly, the PRD is incomplete. ## The 3-Step Process 1. **Write initial description** — Brain dump what you want: feature, tech stack, constraints, integrations, examples, documentation references 2. **Generate the PRD** — Research the codebase + web, interview the user, produce a structured document following the base template 3. **Execute the PRD** — Clear context, start fresh, implement from the PRD alone ## What Makes a Good PRD **DO:** - Reference specific files and code patterns from the codebase - Write testable validation criteria ("returns 401 on invalid token") - Include explicit non-goals to prevent scope creep - List anti-patterns specific to the project - Order implementation steps by dependency (what must exist before what) - Include migration strategy for existing data/behavior **DON'T:** - Use vague validation criteria ("works well", "is performant") - Leave technical design abstract ("use appropriate data structures") - Assume the implementing agent knows project conventions — spell them out - Skip the non-goals section — agents will over-build without boundaries - Write steps that can't be verified independently ## Interview Technique The most valuable part of PRD generation is the interview. Goal: reduce assumptions to near zero. - Ask at least 8-10 questions before writing - Batch questions in groups of 3-4 - Provide recommended answers based on codebase research - Cover: scope, users, technical constraints, data model, compatibility, edge cases, testing, anti-patterns - Final ques
7 days ago · Uploaded
Detail →
- 📄 SKILL.md
prd
Generate a Product Requirements Document (PRD) for a new feature. Use when planning a feature, starting a new project, or when asked to create a PRD. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out.
7 days ago · Uploaded
Detail →
- 📁 references/
- 📄 SKILL.md
architect
技术架构设计 Skill。根据产品需求文档（PRD）设计完整的技术架构方案，输出结构化的架构设计文档。覆盖技术栈选型、系统架构、数据模型、API 设计、部署方案、非功能需求、安全设计等。触发条件：(1) 设计技术架构，(2) 从 PRD 推导技术方案，(3) 系统设计/技术选型，(4) 数据库设计，(5) API 设计，(6) 部署架构设计。
9 days ago · Uploaded
Detail →
- 📁 data/
- 📁 steps-c/
- 📁 templates/
- 📄 bmad-skill-manifest.yaml
- 📄 SKILL.md
- 📄 workflow.md
bmad-create-prd
Create a PRD from scratch. Use when the user says "lets create a product requirements document" or "I want to create a new PRD
10 days ago · Uploaded
Detail →
- 📄 SKILL.md
prd-generator
Generates a structured PRD from a feature description or brief. Use when asked to write, draft, or create a PRD.
5 days ago · Uploaded
Detail →
- 📁 commands/
- 📁 config/
- 📁 scripts/
- 📄 SKILL.md
prd-init
创建标准PRD文档包结构。新项目启动或初始化PRD工作空间时调用。
11 days ago · Uploaded
Detail →
‹
1
›
Skill File Structure Sample (Reference)
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
SKILL.md Requirements
├─ ⭐ 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
Why SkillWink?
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.
FAQ
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
1. What are Agent Skills?
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.
2. How do Skills work?
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.
3. How can I quickly find the right skill?
Use these three together:
- Semantic search: describe your goal in natural language.
- Multi-filtering: category/tag/author/language/license.
- Sort by downloads/likes/comments/updated to find higher-quality skills.
4. Which import methods are supported?
- Upload archive: .zip / .skill (recommended)
- Upload skills folder
- Import from GitHub repository
Note: file size for all methods should be within 10MB.
5. How to use in Claude / Codex?
Typical paths (may vary by local setup):
- Claude Code：~/.claude/skills/
- Codex CLI：~/.codex/skills/
One SKILL.md can usually be reused across tools.
6. Can one skill be shared 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.
7. Are these skills safe to use?
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
8. Why does it not work after import?
Most common reasons:
- Wrong folder path or nested one level too deep
- Invalid/incomplete SKILL.md fields or format
- Dependencies missing (Python/Node/CLI)
- Tool has not reloaded skills yet
9. Does SkillWink include duplicates/low-quality skills?
We try to avoid that. Use ranking + comments to surface better skills:
- Duplicate skills: compare differences (speed/stability/focus)
- Low quality skills: regularly cleaned up