Adds visual descriptions to transcripts by extracting and analyzing video frames with ffmpeg. Creates visual transcript with periodic visual descriptions of the video clip. Use when all files have audio transcripts present (transcript) but don't yet have visual transcripts created (visual_transcript).
{extracted description}
Convert natural language segment descriptions into Apollo.io API search filters.
This skill should be used when the user asks to generate weekly reports from git history, process document links, update markdown files with URL descriptions, or mentions "生成周报", "处理文档链接", "更新 docs.md". Automates weekly report generation by extracting URLs from git commits or source files, generating concise Chinese descriptions, and organizing them into markdown tables.
Mobile accessibility patterns for Android and iOS - content descriptions, touch targets, screen reader support, WCAG compliance, dynamic type, and color contrast.
[1-2 sentence description of what this skill does]. Triggers on [specific phrases/contexts that should activate this skill]. Outputs [what the skill produces].
Write high-quality pull request descriptions based on Google's CL description best practices. Use when creating a pull request, writing a PR description, or when the user asks to describe changes for a PR or merge request.
Generate a 3D model from a text description using build123d and render it in the browser viewer. Use when asked to "render", "make a 3D model", "create a part", "design a", "model a", or any 3D modeling request.
Generate a draft story markdown by analyzing a Jira story or feature description, Figma designs, and the codebase.
Self-improving skills toolkit that watches real agent sessions, detects missed triggers, grades execution quality, and evolves skill descriptions to match how users actually talk. Use when grading sessions, generating evals, evolving skill descriptions or routing tables, checking skill health, viewing the dashboard, ingesting sessions from other platforms, or running autonomous improvement loops. Make sure to use this skill whenever the user mentions skill improvement, skill performance, skill triggers, skill evolution, skill health, undertriggering, overtriggering, session grading, or wants to know how their skills are doing — even if they don't say "selftune" explicitly.
[SPEC] Clear description of when this skill should be activated. Include keywords that Claude uses to decide whether to auto-invoke. The description is CRITICAL for auto-activation — be specific.
Generates a structured PRD from a feature description or brief. Use when asked to write, draft, or create a PRD.
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:
