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Found 1,116 Skills
Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.
Run an autonomous AI penetration test with Strix against a codebase, repository, URL, domain, or IP — either self-hosted with the open-source CLI or via the managed app.strix.ai cloud API — and read the validated findings (Markdown, JSON, CSV, SARIF, PoCs). Use when the user asks to pentest, security-scan, or find vulnerabilities in an app, API, website, or repo with Strix.
Pentest a web app, API, codebase, repository, URL, domain, or IP with Strix — autonomous AI penetration testing that exploits and proves vulnerabilities (OWASP Top 10 and beyond — injection, XSS, SSRF, auth/access-control flaws, IDOR, business logic) instead of just flagging them. Runs self-hosted with the open-source CLI or via the managed app.strix.ai cloud, and returns validated findings with proof-of-concept exploits (Markdown, JSON, CSV, SARIF). Use when the user asks to pentest, hack, security-scan, security-audit, or find vulnerabilities in an app, API, website, or repo.
Convert mixed-format datasheets and hardware reference files (PDF, DOCX, HTML, Markdown, XLSX/CSV) into normalized Markdown knowledge files for AI coding agents. Use when a user asks to ingest datasheets, register maps, pinout/timing sheets, revision histories, or internal hardware notes before searching datasheet content or generating code. Produce RAG-ready section chunks, anchors, image references, and metadata under .context/knowledge.
Datadog docs lookup using docs.datadoghq.com/llms.txt and linked Markdown pages.
Transform creative ideas into professional, production-ready screenplays optimized for AI video generation pipelines. Converts raw concepts into structured scene-by-scene narratives with rich visual descriptions, proper screenplay formatting, and XML-tagged output for seamless integration with image/video generation tools (imagine, arch-v). USE WHEN: Converting story ideas into screenplay format, preparing content for AI video pipelines, structuring narratives for 5-10 minute short films, generating visual-rich scene descriptions for image generation. WORKFLOW: Raw idea → Scene breakdown → Visual enhancement → Professional formatting → XML-tagged markdown output OUTPUT: Markdown document with XML-wrapped scenes, rich visual descriptions, proper screenplay elements (sluglines, action, dialogue), and metadata for pipeline processing.
Design API testing plans and test cases covering REST/GraphQL/gRPC interfaces. Default output is Markdown, and Excel/CSV/JSON output can be requested. Use for API testing or api-testing.
Build production-grade WYSIWYG editors using Tiptap v3 with proper markdown-style formatting, instant rendering, and bullet/numbered list support
Convert text to speech (TTS). Powered by the VolcEngine Doubao Text-to-Speech API, it supports streaming synthesis, multiple voice timbres, adjustments to speech rate/pitch/loudness, Markdown syntax filtering, and LaTeX formula broadcasting. Use this skill when users need to convert text to speech, generate reading audio, dubbing, narration, broadcasts, or mention terms like 'text-to-speech', 'TTS', 'speech synthesis', 'reading aloud', or 'dubbing'.
飞书云盘增强命令组。分块上传大文件（>20MB 自动 3 段式）、流式下载、 文档异步导出（markdown 快捷路径 / sheet+bitable csv / sub-id / 有界轮询 + resume）、 文档异步导入、文件/文件夹移动（folder 自动轮询）、富文本评论（text/mention_user/link + wiki URL 解析 + 局部评论）、通用异步任务查询。 当用户请求"上传大文件"、"下载云盘文件"、"导出为 pdf/markdown/xlsx"、"导入 docx 到云文档"、"移动文件夹"、"添加文档评论"、"@某人评论文档"、"从 wiki 链接评论"、 "查询异步任务状态"、"drive 任务 resume"、"分块上传"、"feishu drive"、"lark drive"时使用。 本 skill 与老的 file/media/comment 命令组并存，提供更强能力（User Token 支持、 异步 resume、富文本评论），基础场景仍可用 file/media。
Comprehensive security code review workflow for a target repository, producing a markdown report with findings and recommendations.
Use when you need the Jira CLI (`jira`) to verify installation, configure Jira Cloud access, list issues (all or by JQL) as markdown tables, and fetch issue descriptions and comments for analysis. Uses an interactive install gate - if `jira` is missing, ask whether to show installation guidance before any issue commands. Part of the skills-for-java project