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.

Validate application configuration with schemas, per-environment rules, runtime checks, and secure handling of sensitive values

Preflight a DGX Spark system for an ML training or inference workload and emit env-report.json

Set up debugging and tracing with remote debugging, distributed tracing, debug logging, profiling, and production diagnostics

Generate API, architecture, code, and user documentation from a codebase and automate keeping it current

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Generate comprehensive migration plans and scripts for transitioning codebases between frameworks, languages, versions, or platforms with minimal disruption.

Plan and execute safe, incremental dependency upgrades with minimal risk — including breaking-change migration paths and proper test verification.

Orchestrate legacy system modernization using the strangler fig pattern with gradual component replacement

Scaffold React and React Native components with TypeScript, tests, styles, and Storybook stories

Scan React, Vue, Angular, and vanilla JavaScript code for XSS vulnerabilities and report fixes with secure coding examples

Orchestrate end-to-end full-stack feature development across backend, frontend, database, and infrastructure layers

Orchestrate git workflow from code review through PR creation with quality gates

Create a role-specific onboarding plan for a new team member, from pre-arrival setup through the first 90 days

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…