LLM Mart Basic
@llm-mart · Joined Jun 2026
Nx monorepo build system — workspace configuration, project graph, task pipelines, caching, generators, plugins, and release management
pnpm workspace protocol, filtering, catalogs, shared dependencies, publishing, and CI/CD for monorepo management
Turborepo, workspaces, package architecture, @repo/* naming, exports, tree-shaking
Secrets management, XSS prevention, CSRF protection, dependency scanning, DOMPurify sanitization, CSP headers, CODEOWNERS, HttpOnly cookies
Biome v2 unified linter, formatter, and import organizer — single Rust-powered tool replacing ESLint + Prettier with 97% Prettier compatibility and 20x faster performance
An agent designed to assist with software development tasks for .NET projects.
A transcendent coding agent with quantum cognitive architecture, adversarial intelligence, and unrestricted creative freedom.
Ultimate Transparent Thinking Beast Mode
Support development of .NET (OOP) WinForms Designer compatible Apps.
Runtime accessibility specialist for keyboard flows, focus management, dialog behavior, form errors, and evidence-backed WCAG validation in the browser.
Expert assistant for web accessibility (WCAG 2.1/2.2), inclusive UX, and a11y testing
Address PR comments
Expert agent for creating comprehensive Architectural Decision Records (ADRs) with structured formatting optimized for AI consumption and human readability.
Expert assistant for developing AEM components using HTL, Tailwind CSS, and Figma-to-code workflows with design system integration
AI agent governance expert that reviews code for safety issues, missing governance controls, and helps implement policy enforcement, trust scoring, and audit trails in agent systems.
Runs the AgentRC readiness assessment on the current repository and produces a self-contained, static HTML dashboard at reports/index.html. Explains every readiness pillar, the maturity level, and an actionable remediation plan, framed by AgentRC measure → generate → maintain loo
AI development team (Nova, Sage, Milo). Use when implementing features, fixing bugs, writing tests, improving user experience, or preparing a pull request across the project's actual stack.
AI team producer (Remy). Use when planning work, clarifying scope, coordinating Dev and optional QA, triaging issues, maintaining project context, or preparing and merging pull requests. Never writes application code.
Optional AI QA engineer (Ivy). Use when testing behavior, running automated or exploratory checks, filing reproducible bugs, verifying fixes, or providing release confidence for changes that warrant dedicated QA.
Your role is that of an API architect. Help mentor the engineer by providing guidance, support, and working code.
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.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
/deploy-software
Deploy software
Stage and reconcile an ImmyBot desired-state software deployment to a tenant or computer
/list-computers
List computers
List and filter ImmyBot-managed computers, optionally scoped to a tenant
/maintenance-status
Maintenance status
Show ImmyBot maintenance session status — active sessions, or detail and logs for a specific session
/run-script
Run script
Find and execute an ImmyBot PowerShell script on a target computer (destructive, SYSTEM context)
/search-software
Search software
Search the ImmyBot software catalog (per-tenant + global)
/drift-report
Drift report
Portfolio-wide Inforcer baseline drift report — every managed tenant's alignment vs its assigned baseline, classified aligned / semi-aligned / drifted and sorted drifted-first, with secure score
/tenant-posture
Tenant posture
Single-tenant Microsoft 365 posture snapshot from Inforcer — secure score plus alignment score, band, and the per-policy drift detail against the tenant's assigned baseline
/classify-email
Classify email
Get an Ironscales AI verdict on a raw email, then act on it with a remediation action
/triage-incidents
Triage incidents
Triage open Ironscales phishing incidents — list by status and severity, investigate, and remediate
/get-quote
Get quote
Get a Kaseya Quote Manager quote with its sections and line items
/get-sales-order
Get sales order
Get a Kaseya Quote Manager sales order with its lines and payments
/list-quotes
List quotes
List Kaseya Quote Manager quotes, optionally scoped to a recent window
/add-note
Add note
Add a note or comment to an existing Autotask ticket
/check-contract
Check contract
View contract status, entitlements, and remaining hours for a company or specific contract
/check-pricing
Check pricing
Check pricing details for an Autotask product or service from price lists
/create-quote
Create quote
Create a new Autotask quote with line items for products, services, and service bundles
/create-ticket
Create ticket
Create a new service ticket in Autotask PSA
/expenses
Expenses
Use this skill when working with Autotask expense reports - creating reports, adding expense items, searching by status or submitter, and tracking reimbursable and billable expenses
/lookup-asset
Lookup asset
Search for Autotask configuration items/assets by name, serial number, or company
/lookup-company
Lookup company
Search for Autotask companies by name, ID, or other attributes
VCP 部署在 AI 模型 API 与前端应用之间,是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架,将原本“无状态、无记忆、无工具调用能力”的大语言模型,彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。
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