323 件 ・ 関連度順
概要と使いどころ
微博（Weibo）公开社交数据查询与热点分析 skill，通过 MaxHub API 查询微博内容、评论、转发、用户资料、粉丝/关注、搜索、热搜、话题和榜单。适合舆情监测、热点追踪、KOL 画像、内容传播分析和竞品研究。默认 read-only；agent 应优先使用 recipes 串联搜索→微博详情→评论/用户画像等流程，避免自行猜测 mid/uid/container_id 参数。所有请求发送到 https://www.aconfig.cn。
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。
西瓜视频（Xigua）公开视频数据查询与内容分析 skill，通过 MaxHub API 查询视频详情、作者、评论、搜索、推荐和相关视频。适合长视频/中视频选题、作者画像、互动分析、热点跟踪和内容复盘。默认 read-only；agent 应按 recipes 匹配视频详情、评论、作者、搜索等意图，并通过字段流传递 item_id/video_id/user_id。所有请求发送到 https://www.aconfig.cn。
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。
今日头条（Toutiao）内容数据查询与资讯分析 skill，通过 MaxHub API 查询文章/视频详情、评论、用户/媒体号、搜索、热榜和推荐内容。适合资讯选题、舆情监控、内容互动分析、媒体号画像和热点跟踪。默认 read-only；agent 应按 recipes 匹配文章、评论、搜索、热榜等意图，并用字段流字典传递 item_id/group_id/user_id 等参数。所有请求发送到 https://www.aconfig.cn。
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。
YouTube 公开视频与频道数据分析 skill，通过 MaxHub API 查询视频详情、评论、字幕、播放/流信息、频道资料、频道视频/Shorts/帖子、搜索、趋势和相关视频。适合海外视频研究、频道画像、字幕语料、评论分析、内容选题和竞品监控。默认 read-only；播放/下载相关信息需遵守版权与平台规则，agent 应优先走 recipes 并按 video_id/channel_id/keyword 字段流链式调用。所有请求发送到 https://www.aconfig.cn。
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。
快手（Kuaishou）公开数据查询与短视频分析 skill，通过 MaxHub API 查询作品详情、作者主页、评论、搜索、热榜、直播和相关内容。适合快手内容选题、达人分析、作品互动追踪、热门趋势监控和运营复盘。默认 read-only；agent 应按 recipes 选择单次或链式调用，使用字段流字典传递 photo_id/user_id 等参数，禁止自行拼接路径或猜测参数。所有请求发送到 https://www.aconfig.cn。
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。
Quality-assure integrated tdmcp features: run the four PR gates + recipe/bridge tests, cross-boundary coherence checks (tool schema↔CLI↔docs↔registry, operator↔createable, bridge↔client), and live TouchDesigner validation (preview + post-cook error check) when the bridge is reachable. Use when validating/QA-ing/testing tdmcp tools, checking a feature actually cooks in TD, verifying CLI matches a tool, or gating 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。
Orchestrates the dedicated Kinect wall harp implementation team. Use whenever the user asks to build, implement, continue, fix, QA, document, or ship the Kinect wall harp, Kinect v2 wall-depth harp, FreenectTD depth-blob hand tracking, projected wall strings, pluck synth harp, or this feature's Layer 1 tool/recipe/docs. Use this before the generic tdmcp-pipeline for this feature.
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。
Plan and implement native RayTK (t3kt/raytk) raymarching/SDF toolkit integration into tdmcp — beyond the existing package-manager staging, into AI-driven RayTK operator (ROP) node graphs. Use whenever the user wants to build, plan, design, implement, continue, fix, QA, or ship RayTK support: create/wire RayTK ROPs, a RayTK operator knowledge catalog, a RayTK-native raymarch/SDF scene tool, RayTK recipes, or the RayTK setup/doctor flow — including follow-ups (re-run, continue, refresh after a new RayTK release, re-QA, docs). Also triggers on 'raytk', 'raymarching toolkit', 'SDF toolkit', 't3kt', 'montar um build para o raytk', 'integrar o raytk'. This owns RayTK integration specifically; use it before the generic tdmcp-pipeline for this feature. Simple questions about RayTK can be answered directly.
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。
Drive the ENTIRE tdmcp roadmap-to-1.0 to completion as a resumable, wave-by-wave campaign — Milestone 4 (generative-AI bridge wave), Milestone 5 (mixer scene arming), and the v1.0 consolidation gates G1–G6 — routing each class of work to the right existing sub-harness. Use whenever the user wants to "implement everything / all the milestones / the whole roadmap / finish the road to 1.0", run the next milestone, close the consolidation gates, or build a long autonomous campaign across M4/M5/G1–G6. ALSO use for every follow-up: continue/resume the roadmap campaign, run the next wave, re-run a failed wave, fold in QA results, check campaign status, re-prioritize, or scope to one milestone/gate. This is the CAMPAIGN layer ABOVE tdmcp-pipeline / tdmcp-feature-lead / tdmcp-backlog-campaign — it sequences across MULTIPLE sub-harnesses (tools, mixer, coverage, docs, bridge, recipes, submission), which the generic backlog-campaign does not. For a SINGLE feature use tdmcp-pipeline; for one tool-shaped backlog file use tdmcp-backlog-campaign. Simple questions can be answered directly.
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。
Orchestrator skill that chains /slideshow-script → /paper-marketing → /video-content for end-to-end TikTok slideshow production. Each phase is an independent Lego block — this orchestrator is just one recipe that combines them. Produces 5 publishable TikTok videos from a single positioning angle. Triggers on "TikTok slideshow", "TikTok video", "make TikTok", "slideshow video", "TikTok content".
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。
Conventions for writing justfile recipes in Nix-based projects.
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。
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
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。
Consult this skill BEFORE proposing a fix to any CLI gap or schema gap that touches evidence, trust magnitude, evidence types, evidence grades, the TM formula, or star-level promotion gates. Also read it whenever an issue mentions citations, stars, commits, contributors, views, reviewers, percentile, arxiv, github-stars-own, repo-own, social-signal, benchmark-result, peer-review, self-attestation, fusion-recipe, verifier-attestation, or proxy-containment — those are the 10 canonical evidence types and the raw inputs that feed their formulas. Also read it when asked whether a skill qualifies for a given star level (0★–6★): the Star Bar and promotion gates live in `META.md`, not in the TM methodology page. Reading both prevents proposing a calibration that satisfies the TM grade threshold but violates a Star Bar installability or link requirement.
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。
Connect and operate the Loophole Bridge (Ableton Live MCP server). Use when the user wants to check Live/bridge prerequisites, wire an MCP client to Loophole, or run a Live editing recipe (humanize, build arrangement, batch rename, chord from prompt). Triggers: "is my Ableton bridge working", "set up loophole", "connect Claude to Ableton", "/doctor", "/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。
Conventions for writing justfile recipes in Nix-based projects.
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。
Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-*), Well-Architected Framework reviews or audits (use google-cloud-waf-*), or workloads covered by specialized solution skills.
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。
Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.
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。
Guides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.
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 the Skmtc CLI to scaffold projects, install or clone generators from JSR, configure schema sources and enrichments, and produce code artifacts from an OpenAPI v3 or GraphQL SDL schema. Teaches the workspace mental model (`<root>/.skmtc/<project>/`, client.json, bundle, manifest) and the agent contract (strict text / strict JSON modes, exit codes, recipe errors, `agent-context` + `doctor`); the command surface itself is discovered from the binary — `skmtc --help`, `skmtc <cmd> -h` — rather than carried in this skill. Use this skill when the user asks to "run skmtc", "generate code from an OpenAPI schema", "install a skmtc generator", "scaffold a skmtc project", "watch a skmtc project", "configure enrichments", "publish a stack", "deploy to skmtc-hub" (the command is `publish`; there is no `deploy`), "skmtc in CI", or invokes any CLI subcommand. For *authoring* a generator package (Projections, Snippets, transform functions), defer to `skmtc-generator`. When something is broken (no output, wrong output, error messages, a failed bundle build), verify before proposing a fix: read the manifest and the parse issues, and reproduce the failure first.
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。
AI pastry chef — sourdough, lamination (croissant), cake decoration, recipe scaling, food cost, HACCP, Thai climate baking
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。
AI bartender — cocktail recipe, mixology technique, bar setup, menu engineering, food pairing, responsible alcohol service
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。
สร้าง shot list + mood board + retouching plan + Lightroom preset recipe สำหรับงานถ่ายภาพ
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。
Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.
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。
Guidance for a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource.
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。