LLM Mart Basic

Use Codex (OpenAI's codex app-server) as a full agent provider — planning, tool orchestration, MCP tools, server-side history, session resume — alongside or instead of Claude. ChatGPT subscription or OpenAI API key, vault-only via OneCLI. Per-group via `ncl groups config update -

Add a monitoring dashboard to NanoClaw. Installs @nanoco/nanoclaw-dashboard and a pusher that sends periodic JSON snapshots.

Add DeltaChat channel integration via @deltachat/stdio-rpc-server. Native adapter — no Chat SDK bridge. Email-based messaging with end-to-end encryption.

Add Dial channel integration — a real phone number for SMS and AI voice calls via the Dial platform (getdial.ai). Native adapter — no Chat SDK bridge.

Add another phone number to an existing Dial channel — a second (or third) public line for the agent, so one NanoClaw install answers SMS and AI voice calls on multiple numbers. Use when Dial is already installed and the operator wants an additional number (e.g. a personal line p

Give chosen NanoClaw agents a real phone number as a container tool — the `dial` CLI baked into the agent image plus OneCLI credential injection for api.getdial.ai, scoped per agent, so the agents you pick can send SMS, place AI voice calls, and receive verification codes from in

Add Discord bot channel integration via Chat SDK.

Add Emacs as a channel. Opens an interactive chat buffer and org-mode integration so you can talk to NanoClaw from within Emacs (Doom, Spacemacs, or vanilla). Local HTTP bridge — no bot token or external service needed.

Add Google Chat channel integration via Chat SDK.

Add GitHub channel integration via Chat SDK. PR and issue comment threads as conversations.

Add iMessage to NanoClaw — one channel, two backends. Local (this Mac's chat.db via the Chat SDK bridge; macOS + Full Disk Access) or Hosted iMessage (via photon.codes — native spectrum-ts with a device-login wizard; any OS, no Mac relay). Triggers on "add imessage", "connect ime

Add a persistent wiki knowledge base to a NanoClaw group. Based on Karpathy's LLM Wiki pattern. Triggers on "add wiki", "wiki", "knowledge base", "llm wiki", "karpathy wiki".

Add Linear channel integration via Chat SDK. Issue comment threads as conversations.

Add a macOS menu bar status indicator for NanoClaw. Shows a bolt icon with a green/red dot indicating whether NanoClaw is running, with Start, Stop, and Restart controls. macOS only.

Add Matrix channel integration via Chat SDK. Works with any Matrix homeserver.

Add persistent graph-based memory via mnemon. Agents recall past context before responding and remember insights after each turn.

Route a NanoClaw agent group to a local Ollama model instead of the Anthropic API. Ollama speaks the Anthropic API natively (v1/messages), so no provider code changes are needed — just env var overrides and a model setting. Use when the user wants to run their agent locally, cut

Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

Use OpenCode as an agent provider. OpenRouter, OpenAI, Google, DeepSeek, etc. via OpenCode config — not the Anthropic Agent SDK. Per group via `ncl groups config update --provider opencode`; host passes OPENCODE_* and XDG mount when spawning containers.

Add Resend (email) channel integration via Chat SDK.

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

Daily standup: all 8 departments report on the current project in parallel

Identify skills injected where not needed, propose regex and description tightening

Draft X/Twitter announcement post (or thread) for the latest plugin release

Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste

Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes

Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization

Propose a skill revision and compare fresh executions under a frozen rubric

Prune stale entries from the whetstone sync decision log

Bump version, commit, push, mirror to ai-skills, and update local plugin

Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).

Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns

Triage all open PRs with parallel agents, label, group, and review one-by-one

Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).

Create Architecture Decision Records with format selection and lifecycle management

Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps

Explore requirements and approaches through collaborative dialogue before planning implementation

Create engaging changelogs for recent merges to main branch

Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps

Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.

Record a video walkthrough of a feature and add it to the PR description

AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.

嘉立创EDA专业版(EasyEDA Pro)自动化：给 AI harness 装上画板的「手」—— 一套 typed 原理图/PCB 动作，CLI / Agent Skill / stdio MCP 三形态融合接入。承接嘉立创「不以卖板赚钱，以培养中国工程师为己任」 | EasyEDA Pro automation:…

Claude Code session log viewer for JSONL files in ~/.claude/projects. Browse conversations, tool calls, tokens, and live tail sessions on desktop, web, and TUI.

Shared memory MCP server — persistent, searchable, cross-client Claude, Opencode

OpenAI Codex CLI session log viewer for JSONL files in ~/.codex/sessions. Browse conversations, tool calls, tokens, collaboration chains, and live sessions on d…

High-performance Google Drive CLI and Model Context Protocol (MCP) Server for LLM/AI agents. Natively execute Google Apps Script (GAS) under a secure whiteliste…

"Vibe-Trading: Your Personal Trading Agent"

Local-first chat history analyzer with AI. | 本地优先的 AI 聊天记录分析工具

Official Oxylabs MCP integration

Persistent memory for Claude Code & Codex CLI. Auto-extracted knowledge graph, multi-representation embeddings, 3D WebGL visualization. LongMemEval R@5=97.45%.…

One person, a team of agents. Multi-session CLI that collaborates across terminals; /goal keeps long tasks running; WeChat/WeCom/Feishu gateway lets you call th…

AI 基础知识 - GPU 架构、CUDA 编程、大模型基础及AI Agent 相关知识。

Self-hosted, open-source agent skill registry for enterprises. Publish & version skill packages, govern with RBAC and audit logs, deploy on-premise with Docke…

深度调研报告生成 Skill — 一条命令，十分钟出券商级深度调研报告 / Professional deep research report generation Skill · Supports 19 languages

The OKF toolkit for Claude Code — author, maintain, validate & visualize Open Knowledge Format bundles. Plugin, agent skills, and a GitHub Action.

Autonomous AI pentesting agents — real-time reconnaissance, vulnerability detection, and exploitation orchestration. Go + TypeScript.

Native macOS and iOS App for the Hermes AI agent — multi-window, multi-server (local + remote over SSH). Chat, dashboard, sessions, memory, cron, MCP, and more.

Multiplayer Claude Code and Codex. Self-hosted team workspace for Claude Code and Codex. Multi-user, browser-based, AI mates with memory.

Every past session, subagent, and workflow -- queryable by your agent, browsable by you

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