3,177 件 ・ 関連度順
概要と使いどころ
AI DevKit · Publish a ready feature branch for review. Use when the user wants to sync, push, and open or update a code review request on GitHub, GitLab, or another Git host.
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 DevKit · Testing phase guidance for adding and validating feature test coverage. Use when the user wants to write tests, update testing docs, run coverage, close coverage gaps, or run dev-lifecycle phase 8.
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 DevKit · Implementation phase guidance for executing feature plans and checking implementation against design. Use when the user wants to implement planned tasks, update implementation docs, verify code matches design, or run dev-lifecycle phases 5 and 7.
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 DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.
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 when forecasting, estimating, or sizing risk — anchor on base rates, give ranges, update prior→likelihood→posterior on evidence, and factor unmeasured quantities into order-of-magnitude bounds.
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。
Before rejecting a proposal or reflexively agreeing, build the strongest faithful opposing case, state agreement conditions, then update or reaffirm.
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, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.
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, track and update team goals in Hivemind via the `hivemind` CLI. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.
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。
Capture semantic-layer and knowledge updates from a live database schema snapshot.
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。
Accept screenshot baseline changes and commit the updated version.json.
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。
Single entry point for every Agentlas command: /agentlas network, /agentlas build, /agentlas storm, /agentlas graph, /agentlas one, /agentlas upload, /agentlas cloud, /agentlas hub, /agentlas local, /agentlas browser, /agentlas call, /agentlas search, /agentlas connect, /agentlas login, /agentlas orch, /agentlas update.
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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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 Azure Advisor recommendations. WHEN: "show Advisor recommendations", "service retirements", "update recommendation status". DO NOT USE FOR: fixes or remediation (use azure-advisor-actionability).
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, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
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 company update into 3-7 structurally distinct, journalist-shaped story angles. Runs the fact through proven newsroom lenses (perspective, abstraction, news values, data, contrarian, news peg) and refuses rephrasings, invented facts, named-journalist guesses, and AI-marketing slop.
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 and control VFX in Unreal Engine 5 with Niagara: systems and emitters, modules and the spawn/update stages, exposed User parameters, and spawning or driving effects from Blueprints or C++. Use when building particle effects, NS_/NE_ assets, spawning a Niagara system at runtime, setting User parameters, or when the user mentions Niagara, VFX, or a particle system in Unreal.
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 and update a game on itch.io: create the project page and upload builds with the butler CLI (butler push) to named channels. Use for itch.io publishing, butler push, channel naming for Windows/macOS/Linux/HTML5, versioning uploads, or shipping a jam or release build to itch.io.
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 or update a game on Steam with Steamworks and SteamPipe: configure depots and packages, upload builds with steamcmd, set a build live on a branch, and run the release checklists. Use for Steam publishing, app_build.vdf/steamcmd uploads, depots, beta branches, or a store page 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。
Structure and debug a LÖVE (Love2D) game in Lua: the love.load/update/draw loop, delta-time movement, input, and screen states. Use when building a LÖVE 11.x game (main.lua, conf.lua, .love).
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。
Structure a pygame (pygame-ce) game in Python: the init/event/update/draw loop, delta-time movement, Surface/Rect blitting, keyboard/mouse input, and Sprite/Group management with collision. Use when building or debugging a pygame game — when the user mentions pygame, pygame-ce, the game loop, blit, Surface, Rect, sprite groups, or clock.tick. Targets pygame-ce.
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。
Design and harden Roblox client/server networking with RemoteEvent, RemoteFunction, and UnreliableRemoteEvent; server authority, argument and Instance validation, rate limits, proximity/ownership checks, targeted replication, streaming, lifecycle, prediction, and reconciliation. Use for Roblox remotes, exploits, request spam, multiplayer replication, network ownership, high-frequency cosmetic updates, or server/client desynchronization.
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。
Tune game physics for stable, good-feeling motion — fixed vs variable timestep, render interpolation, mass/gravity/drag, continuous collision detection (CCD) to stop tunneling, fixing jitter, and collision layers/masks. Engine-neutral. Use when the user mentions physics feel, jitter, tunneling, fixed timestep, FixedUpdate, CCD, bouncing/unstable physics, or collision layers.
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。
Design and build game UI/UX — HUDs, menus, and overlays — that survive every screen: anchor- based responsive layout, resolution/aspect scaling and safe areas, keyboard/gamepad focus navigation, a screen/menu state stack, and event-driven (not polled) HUD updates. Engine- neutral patterns that pair with the detected engine's UI skill. Use when the user mentions HUD, health bar, main menu, pause menu, settings screen, UI layout, anchors, UI scaling, aspect ratio, safe area, controller/keyboard menu navigation, or wiring UI to game state.
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 or update project cspell configuration by resolving the loaded config, active dictionaries, curated words, ignore paths, and validation evidence. Use when spell-check configuration needs project words or ignores.
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。