LLM Mart Basic

Orchestrate end-to-end DevOps/SysOps work - plan the ops chain, delegate to specialized agents (Kubernetes, cloud, GitOps, SRE, sysops), enforce approvals, and verify outcomes.

Design multi-touch outreach sequences - email, LinkedIn, phone - with timing, angles, and stop conditions. Use to systematize prospect follow-up.

Create, audit, install, and manage Navin plugin packs - self-contained bundles of skills and MCP servers (npx/uvx/docker). Use when the user wants to package capabilities, install a pack from git or a folder, or extend Navin with external MCP tooling.

Plan and operate Google Ads, Microsoft Ads, Meta Ads, TikTok Ads, Reddit Ads, and LinkedIn Ads - real analysis of exports / MCP rows with the `ads` engine, targeting, creatives, budgets, and approval-gated optimization loops. Use when paid acquisition is on the table.

Generate PDF documents - reports, one-pagers, certificates, agreements, product sheets, quotes - from HTML laid out as A4 pages (Chromium) or from a finished DOCX/PPTX/XLSX (LibreOffice). Use when the deliverable must be a polished PDF.

Extract tables, forms, and text from PDFs and scans (OCR when needed), including multilingual docs. Use for contracts, invoices, and document intake.

Think like an attacker - chain weaknesses into realistic exploit paths, build proof-of-concept reproductions, and prioritize by real-world impact. Use for /redteam, attack simulation, or "how would someone break in?" analysis. Ethical, authorized, in-scope only.

Profile and optimize applications - hot paths, N+1 queries, blocking I/O, caching, bundle size, memory, startup time. Use for /turbo, "why is it slow?", or pre-launch performance passes.

Enforce least privilege for commands, file paths, domains, and APIs. Use before destructive exec, broad writes, or when the user asks to lock down what the agent may do.

Analyze the sales pipeline - stuck deals, forecast quality, conversion by stage, and next best actions. Use for weekly pipeline reviews and forecasting.

Browser automation - navigate, click, fill forms, multi-tab, upload, extract, infinite scroll, download, screenshot, and deliver web tasks end-to-end. Prefer the built-in `browser` tool (Playwright + optional browser-use). Use with scrape-operator for project delivery.

Create PowerPoint (.pptx) decks - layouts, text, tables, charts, images, and brand templates - using python-pptx. Use whenever the deliverable is a presentation file.

Design the story, structure, and slide-by-slide plan of presentations - pitch decks, client presentations, reports. Use before generating any deck.

Build pricing scenarios - options, margins, discount policies, and negotiation floors - for offers and deals. Use before pricing any proposal or negotiation.

Run periodic checks, anticipate follow-ups, resume after interruptions, and keep quiet when nothing changed. Use with cron, .navin/HEARTBEAT.md, and sustained goals (/goal) for autonomous monitoring.

Generate product imagery - packshots, lifestyle scenes, e-commerce sets, mockups, and short product videos from reference photos. Use for product pages, catalogs, marketplaces, and launches.

Write business letters, reports, memos, meeting notes, and formal documents in French, English, or Arabic. Use for any professional document that must be polished and correctly toned.

Generate hundreds of structured pages from data (locations, integrations, glossaries, comparisons) with unique value per page. Use when a dataset can answer many long-tail queries.

Work the shared project task board (kanban + dependency-aware plan + milestones + timeline) that humans edit in the Dev workbench - decompose objectives, claim tasks, track progress, file findings, assign to subagents or humans, and run the board in a loop. Use for /board, task t

Create and maintain the .navin/metadata project knowledge base - file roles, dependencies, and the metagraph index - so questions map instantly to the right files without grepping. Use at project start and whenever files are added, moved, or repurposed.

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.

Search for Autotask contacts by name, email, phone, or company

List tickets currently assigned to you with optional filtering

Reassign a ticket to a different resource or queue

Search the Autotask product catalog for products, services, or inventory items

Search for tickets in Autotask PSA by various criteria

Log time against tickets or projects in Autotask PSA

Update fields on an existing Autotask ticket (status, priority, queue, due date)

Find a device in Datto RMM by hostname, IP address, or MAC address

Resolve an open alert in Datto RMM

Run a quick job on a device in Datto RMM

List all devices at a site in Datto RMM

Read, edit, and restructure sections of an IT Glue document

Find an organization in IT Glue by name

Retrieve a password from IT Glue (with security logging)

Find a configuration item (asset) in IT Glue by name, hostname, serial number, or IP address

Search IT Glue documentation by keyword or phrase

Get a security posture summary for a RocketCyber customer account

Search RocketCyber security incidents by account, status, severity, verdict, and date range

Locate a Keeper record by description and return its UID and metadata without revealing any credential

Report exactly what the connected Keeper KSM application can reach - folders, record counts, and record types - reading no credential values

Conduit — native SwiftUI iOS client for Hermes Agent

一个现代化的可视化规则引擎平台，用于编排复杂的 AI 工作流。在无限画布上设计、测试和部署 AI 流程——无需编写代码。结合 flowgram.ai 的能力与 Java 服务端，提供生产级工作流管理。在此之上提供AI Agent / Copilot的助手编排能力。

Job application tracker and AI-powered job search assistant. Helps job seekers manage their search journey with AI resume review, job matching, task logging, an…

📝 Markdown and HTML renderer for Svelte 5 — built for streaming AI agent output from Claude Code, ChatGPT, and agentic workflows. XSS-safe defaults, token cach…

ServiceNow MCP server: 500+ tools and 26 AI capabilities for any AI (Claude, ChatGPT, Gemini, Cursor, Copilot). Multi-transport (stdio, SSE, HTTP), A2A, dynamic…

Free crypto news API - real-time aggregator for Bitcoin, Ethereum, DeFi, Solana & altcoins. No API key required. RSS/Atom feeds, JSON REST API, historical archi…

Build production-ready AI agents in both Python and Typescript.

From agent user to agent builder: build a Claude Code-style coding agent from scratch in Python: 8 articles, 4 videos, one codebase

🪁 A lightweight, modern Kubernetes dashboard that unifies multi-cluster and resource management, enterprise-grade user governance (OAuth, RBAC, and audit logs)…

Stateful runtime management for LLM agents—inject, manipulate, and retrieve Python objects across turns.

AgentCall lets AI Agents join meetings with voice, video & screen-share to build together. Supports Google Meet, Teams, Zoom (Beta)

Kition brings Markdown, DataTable, WhiteBoard, a tool-using AI agent, browser research, and visual workflows into one desktop workspace.

IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.

A powerful Model Context Protocol (MCP) server providing comprehensive Google Maps API integration with LLM processing capabilities.

Turn your Claude Pro/Max subscription into an OpenAI-compatible API for your IDEs and devices — LAN auth, per-key quotas, response cache, disciplined cli.js ali…

Paw Work - selection-first web agent for Chrome: select on the live page, describe the outcome, take away an editable office file. BYOK, sandboxed, no server.

基于 AI Agent + MCP 工具链 + 渗透 Skill 编排， 配合大语言模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。

Lexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台

First AI Journey for DevOps - with comprehensive learning paths, practical tips, and enterprise guidelines

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-…