1.4万 件 ・ 人気順
概要と使いどころ
Build a new holaOS app using @holaboss/app-builder-sdk (5 backend primitives + optional shadcn dashboard UI). The canonical path for vibe-coded apps — integration modules AND dashboard apps both live here.
日本語の概要は準備中です。原文の説明を表示しています。
Guide for modifying an already-installed workspace capability — adding or editing its MCP servers, skills, integrations, or agent guidance. Use when the user wants to customize, change, or extend an existing capability.
日本語の概要は準備中です。原文の説明を表示しています。
Install workspace skills from curated sources or import open-source skills from GitHub.
日本語の概要は準備中です。原文の説明を表示しています。
当用户在选择合作者/生意模式/人生策略、问「要不要长期投入这段关系/这个项目」「如何积累声誉」时调用。 核心理念: 财富、知识、声誉、关系都遵循复利; 只玩长期正和游戏, 与能想象共事一辈子的人合作, 拒绝短期思维交易。 不适用于: 紧急止损、短期现金周转等必须立即决策的场景。 Triggers: 长期/复利/声誉/合作/信任/compounding/long-term/trust
日本語の概要は準備中です。原文の説明を表示しています。
Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub
日本語の概要は準備中です。原文の説明を表示しています。
Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.
日本語の概要は準備中です。原文の説明を表示しています。
Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.
日本語の概要は準備中です。原文の説明を表示しています。
Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.
日本語の概要は準備中です。原文の説明を表示しています。
Use terminal_rg / terminal_glob for all filesystem search — your project tree as well as system configs, /var/log, /etc, archive contents. Teaches the rg vs glob vs terminal_exec("find/ls/du/tree") split, common rg flag combos for code/logs/configs, glob patterns for finding files by name, the rule that mtime/size/type predicate queries drop to terminal_exec("find ..."), and that for tree views or single-file stat info you should just use terminal_exec instead of inventing a tool. Read before reaching for raw shell to grep or find anything.
日本語の概要は準備中です。原文の説明を表示しています。
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
日本語の概要は準備中です。原文の説明を表示しています。
Handle trusted reviewers' change requests on Otto PRs.
日本語の概要は準備中です。原文の説明を表示しています。
Draft or refresh Omnigent package release notes for the next version using the existing GitHub Actions preview, merged PR material, and release-note composer. Use when preparing release highlights before a tag exists or reviewing a release-note draft; does not cut or publish a release.
日本語の概要は準備中です。原文の説明を表示しています。
Verify the Omnigent CLI's setup/onboarding flow, terminal UI/UX, and critical user journeys in a completely isolated, reproducible loop. Drives the real `omnigent` binary through a PTY (pexpect) inside a throwaway OMNIGENT_CONFIG_HOME / OMNIGENT_DATA_DIR sandbox that never touches the user's real ~/.omnigent, captures ANSI-stripped frames for UX inspection, and proves a change is verifiable via a before→fix→after baseline diff. Load when developing or reviewing a CLI setup/onboarding/REPL/picker change (omnigent/cli.py, omnigent/onboarding/*, omnigent/repl/*, scripts/install_oss.sh), reproducing a cold-start/first-run UX bug, or confirming a fix actually lands. Several agents can run it concurrently on separate worktrees.
日本語の概要は準備中です。原文の説明を表示しています。
Document a module or public API surface (functions, classes, CLI commands, endpoints) from the code itself. Use when the user asks for API reference, to document a module, or to write usage docs for a public interface.
日本語の概要は準備中です。原文の説明を表示しています。
Turn a breaking change (an API rename, removed flag, changed default, or moved module) into concrete upgrade steps with before/after examples. Use when the user asks how to migrate, upgrade, or adapt to a breaking change.
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Reference guide for building new Omnigent harness integrations — covers SDK/subprocess harnesses and native harnesses as separate tracks, each with their own feature matrix, implementation patterns, and prioritized checklist.
日本語の概要は準備中です。原文の説明を表示しています。
Detect Python agent frameworks from code imports and map them to Omnigent executor types. Load when the user has existing agent code to integrate.
日本語の概要は準備中です。原文の説明を表示しています。
Build, modify, debug, migrate, review, or verify TypeScript MCP servers and MCP Apps with mcp-use. Use for tools, resources, prompts, middleware, Views, authentication, Skills over MCP, scaffolding, and advanced features.
日本語の概要は準備中です。原文の説明を表示しています。
Build, modify, debug, migrate, review, or verify TypeScript MCP servers and MCP Apps with mcp-use. Use for tools, resources, prompts, middleware, Views, authentication, Skills over MCP, scaffolding, and advanced features.
日本語の概要は準備中です。原文の説明を表示しています。
Build and deploy an MCP server from an OpenAPI / Swagger spec using the mcp-use TypeScript SDK. Use this skill whenever the user wants to "turn this OpenAPI spec into an MCP server", "make this API usable from Claude/ChatGPT", "wrap this Swagger doc as MCP tools", "expose this REST API to an LLM", "generate MCP tools from a spec", or pastes/attaches an `openapi.yaml`, `openapi.json`, or `swagger.json` and asks for a Claude-compatible version. Trigger even if the user doesn't say "MCP" — if they describe an existing HTTP API (REST endpoints, an internal service, a third-party API they have a key for) and want an LLM to call it, this is the right skill. Covers spec ingestion (file path, URL, or pasted), operation-to-tool mapping, auth wiring (apiKey, bearer, basic, OAuth bearer), scaffolding with `create-mcp-use-app`, tool generation with proper zod schemas, live testing in the mcp-use inspector, and deploying to Manufact / mcp-use cloud.
日本語の概要は準備中です。原文の説明を表示しています。
Safe git revert. Roll back phase or plan commits using the phase manifest with dependency checks.
日本語の概要は準備中です。原文の説明を表示しています。
Create a clean PR branch by filtering out .planning/ commits — ready for code review
日本語の概要は準備中です。原文の説明を表示しています。
Guide existing codebase onboarding through mapping, doc ingest, and planning setup
日本語の概要は準備中です。原文の説明を表示しています。
Systematic debugging with persistent state across context resets
日本語の概要は準備中です。原文の説明を表示しています。