- 📁 references/
- 📄 SKILL.md
versioning-with-jj
jjでバージョン管理操作を実行する。jjが有効化されている環境でgitコマンドの代わりに使用。bookmark移動忘れによる変更漏れ・履歴分断を防ぐワークフローを提供。
jjでバージョン管理操作を実行する。jjが有効化されている環境でgitコマンドの代わりに使用。bookmark移動忘れによる変更漏れ・履歴分断を防ぐワークフローを提供。
Processes Firefox bookmark exports (JSON) to organize links by category, generate summaries, and produce a visual HTML feed. Activate when the user mentions "bookmarks", "bookmark curator", "organizar bookmarks", "exportei os bookmarks", or "bookmark feed". --- # Bookmark Curator Process Firefox bookmark JSON exports into organized, categorized outputs: a structured markdown file for the training-mentor Skill and a visual HTML feed for browsing. ## Input Firefox bookmark JSON export. Default location: `~/Downloads/bookmarks-YYYY-MM-DD.json` (or ask the user for the filename). If the file is not found, ask the user to export: > Firefox > Bookmarks > Manage Bookmarks > Import and Backup > Backup > Save as JSON ## Processing Pipeline ### Step 0: Check Progress Read `references/progress.md` (in this Skill's folder). This file tracks which URLs have already been processed. If it doesn't exist, create it. Compare all bookmark URLs from the JSON against the processed list. Only process new URLs not yet in the list.
Karakeep bookmark search, browsing, and management
Manage X/Twitter bookmarks locally with Field Theory CLI. Actions: sync, search, list, classify, stats, viz, l2-label, review queue. Keywords: x bookmarks, twitter bookmarks, fieldtheory, ft.
Interact with X/Twitter via the xcom-rs CLI (Rust). Use for posting tweets, replies, threads, searching, reading timelines/mentions, liking, retweeting, bookmarks, media upload, and user lookups. Use this skill whenever the user wants to do anything on X/Twitter — posting, reading, searching, monitoring mentions, managing bookmarks, or looking up users and their tweets.
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: