5-layer persistent memory and coherence architecture for OpenClaw agents. Solves AI amnesia and within-session drift. Built and validated over 353 sessions on a live business. No CS degree required.
Code understanding tool selection. Use when exploring architecture,
Ultimate Claude Code skill creator and architect. Designs, scaffolds, builds, reviews, evolves, and publishes production-grade Claude Code skills following the Agent Skills open standard and 3-layer architecture (directive, orchestration, execution). Handles single-file skills, multi-skill orchestrators with sub-skills and subagents, MCP-enhanced workflows, and full skill ecosystems. Industry detection for skill domain. Triggers on: "create skill", "build skill", "new skill", "skill creator", "skill builder", "skill-forge", "design skill", "scaffold skill", "review skill", "improve skill", "publish skill", "skill architecture", "convert skill", "port skill", "multi-platform", "cross-platform", "eval skill", "test skill", "benchmark skill", "skill evals", "measure skill", "skill performance", "skill A/B test".
This skill should be used when the user asks to design system architecture, make architectural decisions, or translate PRD into technical design
Review ESP32 firmware architecture for RTOS safety, memory management, error handling, and embedded best practices.
Architecture Decision Records with evaluate and design modes. Document significant technical decisions with context, alternatives, and consequences.
This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design".
Reference for project architecture. Use when you need to understand the codebase structure, module organization, request/response flow, or key types.
Transform a requirements document into a technical architecture design. Use after /blueprint:requirements has produced a requirements doc.
Designs Act and Cast architectures through dynamic questioning, outputting validated CLAUDE.md with mermaid diagrams. Use when starting new Act project, adding cast, planning architecture, extracting sub-cast (10+ nodes), redesigning existing cast, or ask "design architecture", "plan cast", "redesign cast", "create CLAUDE.md".
This skill should be used when conducting architecture review with area/performance/power tradeoff analysis. Saves review reports to reviews/ directory.
Extracts reusable knowledge (debugging discoveries, architectural decisions, conventions) from work sessions and saves them as structured memory files in .claude/memories/. Also use when the user asks to "run a retrospective", "extract learnings", or "save what we learned" from the current session.
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:
