1,628 件 ・ 関連度順
概要と使いどころ
Use when converting an agentic repository into a ChatGPT/Codex Plugin or when building, repairing, validating, packaging, submitting, publishing, or auditing an existing Plugin.
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 whenever the user wants to find, shortlist, vet, or enrich US AI/ML/data consulting firms (consultancies) — AI/ML development, MLOps, generative AI / LLM apps (RAG, chatbots, agents), computer vision, NLP, recommendation systems, data engineering, BI/analytics. Triggers on "find an AI/ML consulting firm to build our recommendation engine", "shortlist three RAG/LLM consultancies for an enterprise chatbot", "compare three AI/ML consulting firms with strong ratings", or "pull contact info for these 8 AI consultancy domains", even when described indirectly (we want to use AI for X, deploy ML to production). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for general app/backend work where AI is just a feature. Skip in-house ML/data hires, LLM/AI-tool comparisons (ChatGPT vs Claude), "how do I fine-tune X" DIY questions, AI courses for individuals, non-US firms, individual freelancers.
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 the user says "review bugs", "/review-bugs", "pull new bugs", "what was reported in Bugs", "update the bug list", or asks for an auto-review of reported bugs. Pulls the new messages from the Voxt Bugs and Bugs (Mobile) chats, turns them into entries in docs/bugs.md, reconciles the list with GitHub issues, pull requests and dev commits, moves finished bugs to docs/bugs-closed.md, and lists what needs a human decision.
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。
Answer questions about Voxt — its features, what shipped and when, and how to use it — grounded in three sources: the public "Voxt Announcements" chat, the Landing pages, and the user guide. Use when asked things like "what features shipped this year", "list new features", "how do I use <feature>", "what is Voxt", or any product/usage question about Voxt. Answers are cited to the 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。
Show status of all running ActualChat servers
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。
Instruments and workflow for debugging the VirtualList — the chat transcript (`InfiniteList`) and the sidebar (`FiniteList`). Covers the built-in consistency checker, the on-screen overlay, the five `?vl*` URL flags, the touch-gesture rig, the frame recorder, attaching to a real Android device over CDP, and how to read a trace without being fooled by a measurement artifact. Use when the list jumps while scrolling, blanks, sticks on skeletons, or the overscroll/bounce misbehaves. The component's specification is `docs/ui/virtual-list.md`; this skill is only how to *measure* it. Pairs with /debug-ui (browser side) and /server-loop (server side).
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。
Stop the ActualChat 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。
Cut a new Voxt release. Use when the user says "prepare a release", "cut a release", "release Voxt", "do a release", "/prepare-release", or wants to run nbgv prepare-release, bump the version, generate end-user release notes, and announce them in the Releases chat.
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。
Runs an existing coding agent behind Slack, Telegram, Discord, Feishu, DingTalk, WeCom, WeChat, or HTTP so teams can invoke real agent sessions from chat without rebuilding the agent stack.
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。
AIChat is a comprehensive LLM command-line tool written in Rust that combines chat-REPL, shell command generation, RAG, AI tools, and multi-provider support into a single binary. It connects to 20+ LLM providers including OpenAI, Claude, Gemini, and Ollama.
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 the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.
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。
Cloudflare platform management via Wrangler CLI, Agents SDK (v0.13+), and Browser Rendering API. Deploy Pages, Workers, KV, R2, D1, Queues, Vectorize, Workflows, Hyperdrive. Build stateful AI agents with the full SDK stack — Agent, AIChatAgent, Think, Voice, sub-agents, fibers, HITL, scheduling, observability, Code Mode (Dynamic Worker sandboxes). Budget web scraping via cf_browser.py. Use when deploying to Cloudflare, managing CF infrastructure, configuring wrangler.toml/wrangler.jsonc, building AI agents or chat agents on Workers, adding voice, orchestrating sub-agents, or for cheap web scraping. Triggers: Cloudflare, wrangler, Pages, KV, R2, D1, Workers, Vectorize, Queues, Workflows, Hyperdrive, cf_browser, Browser Rendering, Agents SDK, Code Mode, codemode, MCP, Think, AIChatAgent, Voice agent, sub-agents, fibers, HITL, Dynamic Workers.
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。
Designs Claude Code prompts and CC environments. Produces CLAUDE.md drafts, agent topologies, scope-authorization frameworks, halt triggers, Skills/hooks/MCP plans, chat-to-CC handoff specs, and EXECUTION_PLAN.md remediation plans. Five modes: DESIGN (new CC deployments), EVOLVE (updates from friction), RESEARCH (evaluate a CC tool/pattern), TEMPLATE (reusable artifacts), REMEDIATE (consume hygiene findings → produce + execute plan). Do NOT use REMEDIATE for direct cleanup (Cat 1–10 — use rootnode-repo-hygiene Phase 2). Do NOT use for hygiene scanning (rootnode-repo-hygiene), chat prompts (rootnode-prompt-validation), or chat Projects (rootnode-project-audit).
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。
Compress any conversation into a portable JSON context graph for handoff to a new chat or LLM. Trigger on: "compress this chat", "save context", "new chat", "hand off", "transfer context", "too many tokens", "start fresh", "export conversation", "context graph", "continue in new session". Also trigger proactively when the user mentions starting over in a long session.
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。
将群聊记录转化为规避微信折叠、无列表符号、Emoji 标题的精简中文总结。当用户已导出群聊记录（见 wechat skill）并想生成可直接发回微信群的摘要时使用。
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。
当用户想写或发布微信公众号文章时使用——他们给出零散思路、草稿或笔记，请你润色、生成题图和解释图，或准备上传到 mp.weixin.qq.com。触发词："写一篇微信文章"、"公众号"、"润色"、"题图"、"发公众号"、"/wjs-publishing-wechat"。
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 analytics for AI chatbot performance. TRIGGERS - Use when user needs help with ai-chatbot-analytics related 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。
Design AI chatbot conversation flows with fallbacks. TRIGGERS - Use when user needs help with ai-chatbot-flow related 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。
"Design conversational commerce experiences across messaging platforms including chatbot flows, product cards, and conversion strategies. Use this skill when the user needs to sell through LINE, WhatsApp, Instagram DM, or other messaging channels, design chatbot purchasing flows, or integrate messaging into their sales funnel — even if they say 'sell through LINE', 'build a shopping chatbot', 'customers ask to buy in our DMs', or 'conversational sales strategy'.".
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。
Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.
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 AI chatbots end to end — conversation design, persona, retrieval grounding, escalation, and deployment. Use when creating a chatbot for support, sales, or internal assistance.
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。
Generate ready-to-paste AI image-gen prompts for 2D game art (character/sprite, icon/UI/item, background/tileset) that stay consistent with the project's art style across separate chat sessions in Claude/Gemini/ChatGPT chat UIs. Use when the user wants to render, generate, or create game art/sprites/icons/backgrounds with AI, or mentions an "art style bible" for a game project. Maintains a persistent `art-style-bible.md` so style doesn't drift between requests, and gives a post-generation checklist plus post-processing guidance for common technical misses (transparency, size, aspect ratio).
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。
Bridge Codex to web-based AI model products by packaging local task context, scrub-checking it, sending it through an approved browser surface to ChatGPT Pro, Claude, Grok, Gemini, or another web model, waiting for the answer, and returning the model response to the user or Codex. Also guide DevSpace-like MCP Connector Mode when the user wants ChatGPT Pro or another MCP-capable web host to access approved local workspaces without relying on Codex browser automation. Use when the user asks for GPT Pro, ChatGPT Pro, Claude web, Grok, Gemini web, web model bridge, external model consult, ask another model, second opinion, use a web AI model, browserless agent access to GPT Pro, MCP connector, DevSpace-like workflow, or send local repo context to a browser-based model for planning, review, debugging, architecture discussion, or implementation guidance.
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。
Expert bot developer specializing in Discord, Telegram, Slack automation with deep knowledge of rate limiting, state machines, event sourcing, moderation systems, and conversational AI integration. Activate on 'Discord bot', 'Telegram bot', 'Slack bot', 'chat automation', 'moderation system'. NOT for web APIs (use backend-architect), general automation scripts (use python-pro), or frontend chat widgets (use frontend-developer).
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。