io.github.affaan-m/ECC/configure-ecc

在 Claude Code、Codex 或 Kimi 内引导 ECC 安装、更新或重新配置，同时严格遵守各家工具真实的插件、范围和 Hook 能力。

io.github.affaan-m/ECC/configure-ecc

Claude Code、Codex、Kimi 内で ECC のインストール、更新、再設定を案内し、各ハーネスが実際に備えるプラグイン、スコープ、フック機能を守ります。

io.github.moeru-ai/airi/use-vishot-with-capacitor

Capture deterministic Capacitor application screens with Vishot. Use when the selected Vishot target is a Capacitor app and Codex must capture its locally served WebView at mobile dimensions or distinguish WebView evidence from native-shell evidence.

io.github.davila7/claude-code-templates/computer-use-agents

Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI automation.

io.github.danielmiessler/LifeOS/Migrate

Intakes external content, classifies chunks against LifeOS taxonomy, commits with provenance. Sources: .md/.txt, stdin, LifeOS dirs, CLAUDE.md/Cursor/OpenAI Custom Instructions, Obsidian/Notion/Apple Notes exports. MigrateScan classifies → routing table. MigrateApprove with --approve-all/--approve-target/--review/--dry-run. Confidence ≥70% auto, 40-70% confirm, <40% walk-through. USE WHEN /migrate, migrate content, import from other LifeOS, bring in old notes, import Cursor rules, import CLAUDE.md, bulk import, Obsidian/Notion/Apple Notes import. NOT FOR single-file edits, conversational interviews, identity edits.

io.github.astral-sh/uv/load-github-action-thread

Download retained Codex GitHub Action thread artifacts and load their rollout history into the local Codex app. Use when asked to open, load, import, resume, or inspect a Codex automation thread from a GitHub Actions run or a related GitHub issue or pull request.

io.github.openai/codex/openai-docs

Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex.

io.github.openclaw/openclaw/coding-agent

Delegate coding work to Codex, Claude Code, or OpenCode as background workers; not simple edits or read-only code lookup.

io.github.affaan-m/ECC/unified-memory

Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.

io.github.affaan-m/ECC/unified-memory

Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.

io.github.affaan-m/ECC/unified-memory

Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.

io.github.upstash/context7/find-docs

Retrieves up-to-date documentation, API references, and code examples for any developer technology. Use this skill whenever the user asks about a specific library, framework, SDK, CLI tool, or cloud service — even for well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot. Your training data may not reflect recent API changes or version updates. Always use for: API syntax questions, configuration options, version migration issues, "how do I" questions mentioning a library name, debugging that involves library-specific behavior, setup instructions, and CLI tool usage. Use even when you think you know the answer — do not rely on training data for API details, signatures, or configuration options as they are frequently outdated. Always verify against current docs. Prefer this over web search for library documentation and API details.

io.github.upstash/context7/context7-docs

Fetch up-to-date documentation and code examples for any library, framework, SDK, CLI tool, or cloud service. Use whenever the user asks about a specific library — even well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot — because training data may not reflect recent API changes or version updates. Always use for: API syntax questions, configuration options, version migration issues, "how do I" questions mentioning a library name, debugging that involves library-specific behavior, setup instructions, and CLI tool usage. Use even when you think you know the answer. Do not rely on training data for API details, signatures, or configuration options — they are frequently out of date. Prefer this over web search for library documentation.

io.github.bytedance/deer-flow/engineer-system-change

Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.

io.github.Shubhamsaboo/awesome-llm-apps/commit-archaeologist

Reconstructs why code exists from local git history, including the introducing commit, later changes, current authors, repeated companion files, and likely intent. Use when the user asks "why does this code exist", "who wrote this function and why", or to "explain the history of this function" before a rewrite, refactor, or risky edit. Runs entirely locally.

io.github.openclaw/openclaw/model-usage

Summarize CodexBar local cost logs by model for Codex or Claude, including current or full breakdowns.

io.github.meshery/meshery/quota-axi

Report local Claude, Codex, Cursor, GitHub Copilot, and Grok quota windows via the quota-axi CLI - remaining percentages, reset times, and provider status read from local auth sources, with no routing, recommendation, or provider mutation. Use before deciding whether it is safe to keep spending a provider's quota, when the user asks about usage, rate limits, or remaining quota, or when comparing local provider headroom.

io.github.microsoft/ai-agents-for-beginners/testing-course-samples

Use when asked to validate, test, smoke-test, or run the course's notebook and code samples against a live Microsoft Foundry / Azure OpenAI configuration. Covers environment setup (.env, az login, packages), the scripts/validate-notebooks.ps1 runner, interpreting PASS/FAIL results, and which lessons need extra resources (Azure AI Search, GitHub MCP, Foundry Local, Playwright).

io.github.code-yeongyu/oh-my-openagent/lcx-report-bug

Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing.

io.github.HKUDS/OpenSpace/python-execution-fallback

Four-step recovery workflow for code execution failures when inline Python fails

io.github.ruvnet/ruflo/browser-intent

Execute a natural-language browser intent via page-agent (browser_act) when the target is easier to describe than to select — degrades gracefully when page-agent or an OpenAI-compatible LLM provider isn't configured

io.github.microsoft/ai-agents-for-beginners/local-ai-agents

Bumuo ng mga local-first AI agents na tumatakbo nang buong-buo sa isang developer workstation gamit ang Microsoft Foundry Local at Qwen function-calling models. Saklaw nito ang Small Language Models (SLMs), ang OpenAI-compatible na lokal na endpoint, sandboxed local tools, lokal na RAG gamit ang Chroma, lokal na MCP servers, hybrid cloud/local routing, at ang privacy/cost/offline trade-offs. Batay sa Lesson 17 ng AI Agents for Beginners. GAMITIN PARA SA: pagpapatakbo ng agent nang lokal, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, lokal na RAG, Chroma vector database, lokal na MCP server, privacy-preserving agent, hybrid local at cloud agent, small language model agent, engineering assistant sa aking makina. HUWAG GAMITIN PARA SA: pag-deploy ng mga agents sa cloud nang malakihan (gamitin ang deploying-scalable-agents / Lesson 16), paggawa ng iyong unang agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.

io.github.microsoft/ai-agents-for-beginners/azure-openai-to-responses

Ilipat ang mga Python app mula sa Azure OpenAI Chat Completions papuntang Responses API. Saklaw nito ang pag-migrate ng AzureOpenAI/AsyncAzureOpenAI client sa v1 endpoint, streaming, tools, structured output, multi-turn, EntraID auth, at mga pagsusuri sa compatibility ng modelo. Nakatuon sa Python, para sa Azure OpenAI. GAMITIN PARA SA: pag-migrate sa responses API, paglipat mula sa chat completions, openai responses, pag-upgrade ng openai SDK, migration sa responses API, paglipat mula completions sa responses, gpt-5 migration, azure openai python migration, chat completions papuntang responses, AzureOpenAI papuntang OpenAI client, python azure openai upgrade. HUWAG GAMITIN PARA SA: paggawa ng mga bagong app mula sa simula (simulan direkta sa responses), Node/TypeScript/C#/Java/Go migrations (Python lang ang kasanayang ito), Azure infrastructure setup (gumamit ng azure-prepare), pag-deploy ng mga modelo (gumamit ng microsoft-foundry).

io.github.microsoft/ai-agents-for-beginners/azure-openai-to-responses

Migrasi aplikasi Python dari Azure OpenAI Chat Completions ke Responses API. Meliputi migrasi klien AzureOpenAI/AsyncAzureOpenAI ke endpoint v1, penstriman, alat, output berstruktur, multi-sesi, pengesahan EntraID, dan pemeriksaan keserasian model. Berfokus pada Python dan khusus untuk Azure OpenAI. GUNA UNTUK: migrasi ke responses API, bertukar dari chat completions, openai responses, peningkatan openai SDK, migrasi responses API, berpindah dari completions ke responses, migrasi gpt-5, migrasi python azure openai, chat completions ke responses, AzureOpenAI ke klien OpenAI, peningkatan python azure openai. JANGAN GUNA UNTUK: membina aplikasi baru dari awal (mulakan terus dengan responses), migrasi Node/TypeScript/C#/Java/Go (kemahiran ini hanya untuk Python), persediaan infrastruktur Azure (guna azure-prepare), penyebaran model (guna microsoft-foundry).