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概要と使いどころ
Send prints to Bambu Lab printers through Bambu Connect, Bambu Lab's official app for printing from other software, or Bambu Studio. Use when the user wants to print a sliced `.gcode.3mf`, a Bambu `.gcode` or an unsliced model on a Bambu Lab printer, over Bambu Cloud or LAN. The agent opens the file in the app; the user picks the printer and starts the print there.
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。
Slice 3D models into printer-ready G-code with OrcaSlicer, the open-source slicer with built-in profiles for most FDM printers (Prusa, Bambu Lab, Creality, Voron and more). Use when the user wants an `.stl`, `.3mf` or `.obj` model sliced for their printer, as a sliced `.gcode.3mf` or plain `.gcode`, headless with OrcaSlicer's command line or by opening the model in OrcaSlicer. Never contacts a printer.
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。
How to roll Kortix PRODUCTION back to an older already-released version — the inverse of a release. Covers the one-dispatch rollback-prod.yml engine, the per-surface mechanics (API + gateway = ECS Fargate image-tag swap; frontend = Vercel promote), the all-important Vercel frontend behavior (why a backend-only push can 'clobber' a FE rollback, and the 'don't rebuild the FE for backend-only pushes' skip that fixes it), the DB/migration-drift safety check that is the real blocker, and how a later promote returns prod to latest. Load WHENEVER the user wants to roll back / revert / downgrade / 'go back a version' on prod, asks how the rollback or the frontend clobber/skip behavior works, or needs to run rollback-prod.yml. Pairs with kortix-release (the forward direction).
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。
How to cut a Kortix production release — the versioning philosophy (when patch vs minor vs major) and the exact flow: promote the newest dev SHA with a green Tests run to staging, let the staging PR's checks be the gate, fix forward on dev until it is green, then run Promote to Production and deploy + verify prod. Load WHENEVER the user wants to release, promote, cut/ship a version, publish a release, bump the version, or asks why a promotion is stuck. Load it too whenever another skill or doc needs to describe the release/promotion flow — this file is the one place it is written out in full.
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。
Route and complete Composio work across Composio For You and Composio Platform. Use when the user mentions Composio; wants an agent to use apps such as Gmail, Slack, GitHub, Notion, Calendar, or Linear; needs first-time setup, an SDK or MCP integration, CLI operation, migration guidance, current documentation, or help diagnosing a connection or tool call.
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。
Publish a website or web app from the sandbox to a public URL, and deploy to cloud providers — get a live link to share, ship a static site or SPA, put a built site online, or deploy a framework app / container. Use when the user says 'publish this', 'deploy it', 'put it online', 'give me a live URL', 'host this', 'share a preview link', or wants to make a site/app they (or you) just built reachable on the web. Covers the zero-account instant path (Cloudflare) and permanent hosting (Vercel, incl. any Dockerfile). Also owns the publish GUARDRAILS: never publish unprompted, how to honestly take a site down, the runtime-dependency and data-persistence checks, and the mandatory pre-publish security review. Prefers Kortix Apps (a stable Kortix URL behind Kortix sign-in) when the project has Apps on. Points at kortix-marketplace for other providers and deeper provider-specific 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。
The Kortix marketplace — how to discover capabilities and IMPORT them into this project. The marketplace is a catalog of open git repos: whole ready-made PROJECTS (registry:project) and individual skills/agents/tools. There is no deterministic 'installer' — you (the agent) import an item by reading its source and merging the files that fit into this project, then opening a change request. Use when the user wants to browse/search the Kortix catalog, 'add/clone the <X> project', 'import that skill/agent', pull in a marketplace capability, or add a new source.
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。
Route code, repository, and data/SQL work to isolated Kortix sessions instead of burning your main context on it. Use when asked to implement a feature, fix a bug, make failing tests pass, work a ticket/issue, refactor, navigate or change a codebase, ship a PR, review a pull request, or run SQL/warehouse analysis against a dataset — and when the user wants two agents or parallel reviewers/investigators on the same work. Covers the explore-vs-session routing call, deciding where the code lives (this project's repo vs cloning an external GitHub repo) or where the data lives, finding the repo with gh, spawning sessions in parallel, dual PR reviews, and reporting results back. Triggers: 'implement', 'fix the bug', 'make the tests pass', 'work this ticket', 'refactor this', 'open a PR', 'review this PR', 'run two agents on it', 'query the warehouse', 'analyze this dataset'.
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 for PUA/try-harder productivity coaching when the user expresses frustration, repeated failure, quality complaint, passive behavior, says retry/change approach/don't give up, asks for evidence/completion check/test before done, or wants Ding-style workplace reminders. Triggers include: try harder, stop giving up, figure it out, again??, why still failing, change approach, no evidence, run tests, done without proof, 换个方法, 再试试, 别摆烂, 别偷懒, 为什么还不行, 又错了, 证据呢, 没跑测试别说完成, 验收, 闭环, 自嗨, 置身钉外, 无招, 老板体感. Do not use for calm first-attempt requests.
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。
FLOW framework integration: evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO prompts.
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。
Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill), or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill). This skill is purely DeepEval-SDK instrumentation — producing well-formed traces, not running evals.
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。
Export raw OpenTelemetry traces from an AI application to Confident AI's Observatory. TRIGGER when the user wants to send OpenTelemetry or OTLP traces/spans from an LLM app, agent, RAG pipeline, or chatbot to Confident AI; configure the Confident AI OTLP endpoint; set confident.span.* or confident.trace.* attributes; export AI-app traces without the deepeval Python package; wire an OTLPSpanExporter, OpenTelemetry Collector, or vendor-neutral OTel SDK to Confident AI; or pick the US vs EU OTLP endpoint. Language-agnostic: the mechanism is OTLP attribute keys plus an exporter endpoint. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill); for instrumenting with the DeepEval SDK's @observe decorator or framework integrations (use the `deepeval-tracing` skill); or for non-AI software such as web servers, CRUD backends, or infrastructure: the confident.* attributes describe AI components only.
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。
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, traced evals, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval; for instrumenting an app with DeepEval tracing, @observe, or framework integrations (use the `deepeval-tracing` skill); or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill).
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 tech-spec directory into an interactive, marketing-grade web presentation — built so engineers understand the design, the reader is convinced of the why, and the result is shareable in public. Use when someone wants a spec turned into a deck.
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 the iii engine, set up your first worker, and get a working backend running. Use when a user wants to start a new iii project, install the SDK, or needs help with initial setup and configuration.
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。
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' or 'viral content.' This skill covers content creation, repurposing, and platform-specific strategies.
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。
Review code changes for correctness, clarity, and potential issues. Use when the user asks for a review, code review, PR review, or wants feedback on a diff or file.
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。
Drop-in inspector panel for any json-render app. Use when the user wants to debug a generative UI, inspect the spec tree, edit state at runtime, see dispatched actions, follow stream patches live, browse a catalog, or pick DOM elements to find their spec keys. Triggers include "add devtools", "debug json-render", "inspect the spec", "why is this element not rendering", "see the state at runtime", or requests to tap streams / capture action logs for `@json-render/devtools`.
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。
React adapter for the json-render devtools inspector. Use whenever the user wants to add, configure, or troubleshoot @json-render/devtools-react in a React json-render app, including spec inspection, state editing, action and stream timelines, catalog browsing, or DOM picking.
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。
Vue adapter for the json-render devtools inspector. Use whenever the user wants to add, configure, or troubleshoot @json-render/devtools-vue in a Vue json-render app, including spec inspection, state editing, action and stream timelines, catalog browsing, or DOM picking.
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。
SolidJS adapter for the json-render devtools inspector. Use whenever the user wants to add, configure, or troubleshoot @json-render/devtools-solid in a SolidJS json-render app, including spec inspection, state editing, action and stream timelines, catalog browsing, or DOM picking.
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。
Svelte 5 adapter for the json-render devtools inspector. Use whenever the user wants to add, configure, or troubleshoot @json-render/devtools-svelte in a Svelte json-render app, including spec inspection, state editing, action and stream timelines, catalog browsing, or DOM picking.
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。
Explain how a public GitHub repository is built using GitDiagram's architecture diagram. Use when the user asks how a GitHub repository or open-source project is structured or organized, wants an architecture or system diagram of a repo, or is starting work in an unfamiliar codebase hosted on 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。
Show the architecture of a public GitHub repository with GitDiagram (gitdiagram.com) - a written explanation, its main components and source paths, how they connect, and a Mermaid diagram. Use when the user wants to understand, map, visualize or get an overview of a GitHub repository or open-source project's architecture, structure or data flow, or asks for an architecture diagram of a repo, e.g. "/gitdiagram fastapi/fastapi" or "how is vercel/next.js structured?".
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。