LLM Mart Basic

Runs scoped browser probes for focus, hit targets, overflow, themes, request failures, and performance attribution, with evidence linked to UI rule IDs. Use when asked to "verify this in the browser", "reproduce this finding", or "check the fix". For source audits and severity us

Data analysis and reference enrichment.

Maximize information density: preserve all instructions, remove prose filler.

Generate headlines, titles, and subject lines: charge, volume, tighten.

FFmpeg-based video creation from image and audio.

Plan multi-part content series: structure, cross-linking, cadence.

Generate blog topic ideas: problem mining, gap analysis, expansion.

Writing: voice creation and validation, prose editing, anti-AI cleanup, professional communication, translation.

Domain-specific: SAP Commerce, OpenSearch detection, WordPress validation, enterprise search.

Design a CLI interface: args, flags, help, output, errors, exit codes, config.

Frontend: UI design, distinctive visual styles, HTML artifacts, Three.js 3D.

CPU-only motion data processing pipeline for game animation: BVH import, contact detection, root decomposition, motion blending, FABRIK IK. No GPU required.

Jev-driven browser automation: Jev picks operations, programs execute, a text model writes field values only when Jev cannot pick one from the goal.

Audit CVE/vulnerability source coverage for a technology stack. Maps each component (container, library, base image, runtime) to authoritative CVE feeds, flags gaps, and produces audit-ready reports. Generic: works for any service or stack.

Kubernetes operations: debugging, security, RBAC, and infrastructure tooling.

GitHub: notification triage, profile rule extraction.

Write, compose, integrate, and improve programs that call Jev, TypeSafe's System One judgment model.

Run benchmark-selected GPT-5.6 work through the Codex CLI.

Jev request router: validates the requested outcome, then dispatches to the matched agent, skill, and pipeline.

Toolkit management: create and evaluate skills and agents, manage routing tables, generate Claude.md.

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.

Plural alias for task status, pause, prompts, recovery, and ignore

Verify that the autorun plugin command surface is loaded

Tmux session management - create, list, cleanup isolated sessions, short for /ar:tmux

Tmux session management - create, list, cleanup isolated sessions

CLI testing in isolated tmux sessions, short for /ar:ttest

CLI testing in isolated tmux sessions

Graceful stop - finish current task then stop (short for /ar:stop)

Set AutoFile policy to ALLOW — permit creation of new files without justification

Refresh git commit guidelines before staging changes

Set AutoFile policy to FIND — restrict edits to existing files only

Start an autorun task with three-stage verification (initial → critical review → final verification)

Refresh the universal system design philosophy before designing or reviewing code

Show the current AutoFile policy and any active autorun state

Extract text from PDF files or directories to markdown

Trigger: `/ship` or "ship it" or "deploy to production"

Suppress 5-question enforcement for rapid sessions

Check a Dutch address for KPN outages and report what connectivity is available there

Find the KPN business-mobile contract for a lost or stolen phone and block its SIM after confirmation

Run the SkillOpt-Sleep cycle with the handoff backend — no API subprocess; this session answers the engine's model calls via prompt/answer files, in isolated fresh-context subagents

Run or manage the SkillOpt-Sleep self-evolution cycle (review past sessions, replay tasks through a selected backend, consolidate validated memory + skills, or schedule nightly runs)

Open-source MCP servers for Latin American commerce — Pix, NF-e, banking, fiscal, logistics, and messaging across Brazil, Mexico, Argentina, Colombia, Chile, an…

pi coding agent in a technicolor web trenchcoat

Open-source AI Search Intelligence Platform — track, analyze, and improve AI visibility, citations, prompts, competitors, and content opportunities across ChatG…

Open-source toolkit for the QVeris capability routing network: CLI, MCP server, Python SDK, skills, and REST API docs for agents to discover, inspect, call, and…

⚡ The Complete X/Twitter Automation Toolkit — Scrapers, MCP server for AI agents (Claude/GPT), CLI, browser scripts. No API fees. Open source. Unfollow people w…

The AI agent that interacts with you in the real world.

Offline Codex Desktop migration for Windows and macOS.

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashbo…

Your smart, reliable, and friendly personal AI assistant.

The LLM Anti-Framework

A general-purpose AIGC video engine: script to finished film in one pipeline — dramas, ads, product videos, otome games, and more. | 通用 AIGC 视频引擎 —— 从剧本到成片一条流水线…

GTM agent for technical founders. Pay-per-result. Signed receipts. Two surfaces: terminal CLI + local web dashboard.

Desktop automation MCP server — computer use for any AI agent: control screen, windows, mouse/keyboard, and Chrome via Model Context Protocol (stdio)

DeepSeek Harness (dsh) Windows desktop client - bundled Node.js + dsh CLI, one-click launch

Open-source, real-time collaborative AI canvas - notes, mini-apps, and agents on one infinite board.

MCPSafari: Native Safari MCP Server for AI Agents

197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Po…

The AI agent with a wallet — spends USDC autonomously to get real work done. Apache-2.0, TypeScript.

The fastest browser for AI agents to run browser automation, built for sharing your logged-in browser state with your AI agents, like Codex or Claude Code, with…

Ouroboros — self-creating AI agent. Born Feb 16, 2026.