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.

Generate a typed client from an Anchor or Shank IDL (Codama or Anchor TS)

Migrate TypeScript from @solana/web3.js 1.x to @solana/kit

Plan a Solana feature before coding: accounts, PDAs, instructions, risks, tests

First-time-user product review: scorecard and fix roadmap; --harsh for a roast

Measure compute units per instruction and flag the expensive ones

Format, lint and commit with a conventional message on a kit-named branch

Resync external skill submodules to latest upstream versions

Scaffold a Solana project (Anchor, fullstack, frontend, Pinocchio) with the kit

Set up GitHub Actions CI for Solana programs: lint, build, test, audit

Configure MCP server API keys in .env and add the optional MCP servers

Run tests, auto-fix fmt and lint, and fix failures until green or stuck

Run C# tests: Unity Test Framework in batchmode, or dotnet test

Run Rust tests for programs (LiteSVM, Mollusk, Surfpool, Trident) and backends

Run TypeScript tests for programs (Anchor TS, Kit) and dApp frontends

Update solana-ai-kit to latest version from upstream

Write docs for a Solana program, SDK or component from its code and IDL

Allow all file creation (short for /ar:allow)

Set AutoFile policy to allow-all mode (full file creation permissions)

Set AutoFile policy to justify-create mode (require justification for new files)

Set AutoFile policy to strict-search mode (only modify existing files)

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it.…

Curated systems, benchmarks, and papers etc. on memory for LLMs/MLLMs --- long-term context, retrieval, and reasoning.

:memo: Vimlike Modal Text Editor in Rust

CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.

Hermes Agent memory plugin/provider for scope-aware recall, SQLite truth, LanceDB semantic search, and hybrid retrieval.

For You Agent——AI 时代的个人随身数字人格。把你的模型、AI 账号、技能、提示词和工作方式，带到每一个 AI 工具里。

A coding agent: give it a prompt and it reads, writes, runs commands, and searches code in a loop until the work is done, using native tool-calling across OpenA…

A secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, Telegram, WhatsApp, Discord, Teams, and…

Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption

DeepSeek Harness Desktop (dsh-desktop). EAC: Embracing All Creation (揽尽万象). Bundled Node.js runtime with full dsh-CLI kernel, one-click startup, 10 built-in UI…

See your agent think. Zero-config observability & governance for 26 AI agent runtimes: Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Cline, Ope…

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP…

Yet another coding agent harness, lightweight and written in go.

a coding Agent from pi. ∞ providers, sub-agents, hashline edits, and a permission gate

Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting…

🧠 Leon is your open-source personal assistant.

The Station, an open-world multi-agent environment that models a miniature scientific ecosystem.

The Frontend Stack for Agents & Generative UI. React, Angular, Mobile, Slack, and more. Makers of the AG-UI Protocol

VelaTerm = iTerm2 + Codex, The Best Terminal for AI Coding