K8s 清单生成器
io.github.wshobson/agents/k8s-manifest-generator
遵循最佳实践与安全标准,为 Deployment、Service、ConfigMap 与 Secret 生成生产就绪的 Kubernetes manifest。在生成 Kubernetes YAML 清单、创建 K8s 资源或实施生产级 Kubernetes 配置时使用。
“E Commerce Operations” 共 9,817 个结果
io.github.wshobson/agents/k8s-manifest-generator
遵循最佳实践与安全标准,为 Deployment、Service、ConfigMap 与 Secret 生成生产就绪的 Kubernetes manifest。在生成 Kubernetes YAML 清单、创建 K8s 资源或实施生产级 Kubernetes 配置时使用。
io.github.heygen-com/hyperframes/embedded-captions
Add captions or subtitles to an existing single-subject talking-head video without editing the footage. Use for plain verbatim captions, cinematic captions embedded behind the subject, VFX captions, “炸/特效/酷炫字幕,” or a named identity from the 35-style catalog. Route by visual identity, not by backend engine. The quiet `anchor` rail is the default; embed every word only when the user explicitly wants a fully cinematic treatment. The workflow runs locally end to end, including transcription and subject matting; split multi-shot footage before applying it.
io.github.heygen-com/hyperframes/hyperframes-keyframes
当 HyperFrames 合成需要推近、拉出、缩放、改构图、Ken Burns 效果、运镜、视觉匹配/甩镜交接,或其他 seek-safe 的 2D/3D 关键帧时使用;也用于 GSAP、CSS keyframes、Anime.js、WAAPI、FLIP、路径、遮罩、SVG morph/draw、文字拖尾、3D 纵深,或 `hyperframes keyframes` 诊断。不要用于宽泛的场景策略、品牌设计、素材获取、字幕或一般视频规划。
io.github.QwikDev/qwik/qwik-core-development
用于修改或审阅 packages/qwik 下的 Qwik 核心包代码,尤其是响应式原语、信号、VNode、cursor 行为、QRL,以及面向 optimizer 的运行时行为,或 Qwik 核心测试。
io.github.affaan-m/ECC/mcp-dependency-review
Statically review MCP configuration for mutable package references before approval or CI, without executing discovered MCP servers.
io.github.affaan-m/ECC/mcp-dependency-review
Statically review MCP configuration for mutable package references before approval or CI, without executing discovered MCP servers. Use when reviewing .mcp.json, Cursor, VS Code, Claude, Windsurf, or other repo-scoped MCP config.
io.github.affaan-m/ECC/mcp-dependency-review
Statically review MCP configuration for mutable package references before approval or CI, without executing discovered MCP servers. Use when reviewing .mcp.json, Cursor, VS Code, Claude, Windsurf, or other repo-scoped MCP config.
io.github.NousResearch/hermes-agent/unreal-mcp
自动化 Unreal Engine 编辑器的场景、Actor 与渲染操作。
io.github.asgeirtj/system_prompts_leaks/durable-test-collateral
Load the body before the first implementation edit for a bug fix or behavior change, or when the user or governing specification makes reusable tests a deliverable. It keeps the smallest focused test with the delivered project and updates coverage when behavior changes. Do not load for greenfield work unless reusable tests are explicitly required, behavior-preserving refactors, verification-only work, plan/review/explanation/documentation/formatting/generated-output-only work, explicit no-change or no-tool work, or when the user declines tests.
io.github.asgeirtj/system_prompts_leaks/requirements-clarification
Clarify a material user-owned product decision before substantive implementation commitments. Use only when request and named/governing evidence still leave a choice that would materially change scope, platform support, user-facing surface, data/API contract, domain values, project placement, or cross-system architecture; also use when a truncated request omits such a choice. On the initial turn, inspect only named or governing requirements evidence, then ask directly without loading: prefer structured input; ask one blocking outcome question or at most three coupled questions; wait. After the answer, load the body before write or delegation. Do not use for implement/build/fix/debug/refactor work when expected behavior is settled, plan/design deliverables owned by Plan, complexity/greenfield/integration alone, agent-owned technical choices, locally discoverable facts, reversible defaults, permission to begin, or stop/no-tool turns. Never re-ask supplied facts or turn clarification into refusal.
io.github.asgeirtj/system_prompts_leaks/taste
Mandatory preflight for web frontend visual design. If available, call read_skill for bundled:taste before the first frontend create or edit tool call whenever creating or visually styling a human-viewed web page, component, app, dashboard, or interactive report. Do not load it for non-visual frontend logic or machine-only HTML. If unavailable, continue without warning. Negative constraints only; user requests and other explicit styles still win.
io.github.asgeirtj/system_prompts_leaks/python-env
Setting up or installing into a Python environment. One rule applies whether or not you read the body - the environment belongs with the project, so create it inside the project directory (.venv) or let uv manage it, and never in a scratch directory like /tmp and never by forcing an install into the system interpreter. Load the body before creating a virtualenv, choosing an installer, or writing run instructions for a Python project.
io.github.asgeirtj/system_prompts_leaks/forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely means cancel the current task.
io.github.asgeirtj/system_prompts_leaks/muse_db
Inspect database-backed Muse records for diagnosis and cross-table tracing when purpose-built product tools do not expose the needed state.
io.github.asgeirtj/system_prompts_leaks/lovable
Read, create, edit, and deploy web apps and projects in Lovable. Use to turn a product brief into a working website or prototype, inspect existing project code, update pages and features, and publish changes through Lovable's official MCP server.
io.github.asgeirtj/system_prompts_leaks/vercel
Inspect and manage the user's Vercel websites, web apps, projects, and deployments. Use to read build and runtime logs, investigate production errors and failed deployments, check deployment status, and deploy projects through Vercel's official MCP server.
io.github.asgeirtj/system_prompts_leaks/document
Create, read, edit, or manipulate Word documents (.docx) and Word templates (.dotx). Use whenever a build task's artifact kind is document with the default docx output, or the task mentions a Word doc, .docx, or .dotx, extracts or reorganizes content from one, inserts or replaces images, does find-and-replace in one, or works with tracked changes (redlines) or comments. Covers python-docx generation, raw OOXML editing of existing files, document structure and formatting, and render verification. Not for PDFs, spreadsheets, or Google Docs.
io.github.affaan-m/ECC/frontend-design-direction
为生产级 UI 工作确定一套 ECC 专属的前端设计方向。当构建或改进网站、仪表盘、应用、组件、落地页、可视化工具,或任何需要更强产品化设计判断的 Web UI 时使用。
io.github.pytorch/pytorch/scrub-issue
获取、分析、复现并精简 GitHub issue 的复现步骤。仅在用户要求验证某个 GitHub issue 是否可复现、精简其复现用例、分析 bug 报告,或为可复现性对 issue 做审查/分诊时使用。不适用于没有对应 GitHub issue 的独立复现请求。
io.github.pytorch/pytorch/ci-metrics
查询 PyTorch CI、GitHub Actions、HUD、Grafana 与基础设施指标。当用户询问 CI 耗时、任务失败、排队时长、工作流趋势、runner 健康度、看板数据或 PyTorch 基础设施指标时使用。
io.github.pytorch/pytorch/fix-issue
复现并定位 PyTorch GitHub issue 报告的 bug,在本地工作区实现修复。当用户要求修复 PyTorch GitHub issue 时使用。
io.github.pytorch/pytorch/triaging-issues
对 GitHub issue 进行分诊:路由到值班团队、打标签并关闭咨询类问题。在处理新的 PyTorch issue 或被要求分诊 issue 时使用。
io.github.pytorch/pytorch/pt2-bug-basher
调试 PyTorch 2 编译器栈故障,包括 Dynamo 图断裂、Inductor 代码生成错误、AOTAutograd 崩溃与精度不一致。在遇到 torch.compile 错误、BackendCompilerFailed 异常、重编译问题、Triton kernel 失败、FX 图问题,或用户提到调试 PT2、Dynamo、Inductor 或编译模型问题时使用。
io.github.TriliumNext/Trilium/maintaining-docker-hub
Use when working on Trilium's published Docker images on Docker Hub or GHCR rather than on the Dockerfiles — "how many pulls does the image get?", "why is the Docker Hub repository so big?", "clean up old tags", "delete untagged images", "which tags do we publish?", the legacy repositories (triliumnext/notes, zadam/trilium) and their mirroring, the main-docker.yml copy-to-Docker-Hub step, mirror-legacy-docker.yml, Docker Hub categories, stars or the overview. Includes hub.mjs (stats, tag listing/deletion, the manifest inventory and a safe untagged-image purge, all dry-run by default) and the storage model that decides how a cleanup works. Do NOT use for building or running the image locally (see the Developer Guide's Docker page).