Act as a Principal Business Analyst (8+ years exp) bridging the gap between Strategy and Execution. Specializes in translating vague vision into rigorous technical specifications using Gherkin (BDD), BPMN 2.0, and strict Requirement Engineering standards.
Use when doing any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when you have a spec or requirements for a multi-step task, before touching code
Analyze collected requirements from interviews, detect ambiguities, generate structured specifications, and suggest implementation approaches
Fetch and display comments from a GitHub pull request
Use when the user wants AI to turn a requirement text, requirement document, and existing reviewed plan files into dependency-ordered implementation plans, a consolidated `checklist.md`, and, only after an explicit execution command, implement those plans with subagents in parallel where safe and in sequence where required.
Use this skill when implementing or modifying AWS CDK constructs/examples in this repository, especially for spec-driven changes requiring requirements, design, tasks, test updates, and safe handoff.
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.
Create a PRD from scratch. Use when the user says "lets create a product requirements document" or "I want to create a new PRD
Clarify requirements before implementing. Use when serious doubts arise.
Explore requirements and approaches through collaborative dialogue before writing a right-sized requirements document and handing off implementation planning to bt:plan. Use for feature ideas, problem framing, vague or ambitious requests, "what should we build" conversations, or when a user wants to think through options before deciding what to build.
Expert MBSE and requirements engineer. Use when (1) exploring models and finding requirements, (2) adding features with proper MBSE traceability, (3) refactoring cluttered models and extracting specifications, (4) generating implementation tasks from requirement changes. Orchestrates reqvire commands and provides systems engineering guidance.
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:
