LLM Mart Basic

Abnormal Security threat detection: threat types (BEC, phishing, malware, socially-engineered attacks, spam, graymail, credential theft), attack vectors, severity assessment, remediation actions, and investigation workflows.

Atera alerts: alert types, severity levels, alert sources, the acknowledge/resolve lifecycle, and alert-to-ticket conversion.

Atera REST API fundamentals: X-API-KEY header authentication, OData-style pagination, the 700 requests/minute rate limit, endpoint conventions, and error handling.

Atera customers and contacts: customer records and fields, contact management, custom fields, and customer lifecycle operations.

Atera service desk tickets: ticket fields, statuses, priorities, comments, work hours, and billing duration.

Auvik alerts: severity tiers, status lifecycle, dismissal semantics, and the common alertName patterns that show up in MSP NOC queues.

Auvik MCP fundamentals: the JSON:API envelope shape, basic-auth credential model, region routing, cursor-based pagination, rate-limit handling, and the v1 vs v2 device API distinction.

Auvik device records: device types, manageStatus and onlineStatus, lifecycle and warranty fields, and choosing between the v1 list endpoint and the detailed device endpoints.

Auvik network and interface entities: the network entity model, IP-range scoping, interface-to-device relationships, and adminStatus vs operStatus.

Autotask REST API fundamentals: header-based authentication, zone detection, the query/filter DSL (14 operators, logical grouping, includes), pagination, rate limits, and CRUD conventions across the 215+ entity PSA.

Autotask billing item retrieval, approval-level workflows, and invoice search — covering billing item types, approval status filtering, and reconciliation of billable work against invoices for MSP finance teams.

Autotask Configuration Item (CI) asset management: CI types and categories, lifecycle status codes, the CI field schema, related-item relationships, DNS records, notes, and contract/billing associations for MSP infrastructure tracking.

Autotask contract and service agreement management - contract types (recurring services, block hours, time & materials, fixed price, retainer), service/service bundle associations, SLAs, and how contracts drive billing for MSP account managers.

Autotask CRM entities - companies (accounts), contacts, and sites/locations - including field references, company type classifications, and how these records underpin tickets, contracts, and projects for MSP account management.

Autotask expense report and expense item structure - the report/item parent-child relationship, approval status workflow, expense categories, payment types, and the billable vs reimbursable distinction for MSP operational expenses.

Autotask picklist and reference-data lookups — queues, ticket statuses, ticket priorities, and project phases — the instance-specific configured values required before creating or filtering tickets and other entities.

Autotask product catalog structure - Products, Services, and Service Bundles - and how Price Lists override default unit pricing. Covers product/service fields, inventory tracking, and cost-vs-billing margin analysis for MSP quoting and procurement.

Autotask project structure - projects, phases, tasks, and milestones - including project and task fields, status values, resource assignment, and how project work links to contract billing for MSP project managers.

Autotask quote structure and line items - quote item types (product, service, service bundle, labor, expense, shipping), the mutually-exclusive catalog reference rules, and the three discount mechanisms (unit, line, percentage) used to build customer proposals.

Autotask Service Call data model - the ServiceCall / ServiceCallTicket / ServiceCallTicketResource three-layer structure - covering fields, status codes, and how tickets and technicians (resources) are linked to scheduled work.

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.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Human risk score report for one client or the whole portfolio, built from training completion and phishing-simulation performance

Training completion snapshot for one client or the whole portfolio — completion rates, overdue users, and cadence status

Check backup health for one Axcient-protected device

Backup health overview across every device for one Axcient client

Azure cost and pricing analysis for a subscription — Advisor cost recommendations, retail pricing lookups, and quota-driven right-sizing signals, scoped to one subscription

Resource health and diagnostics triage for an Azure resource or subscription — Resource Health status, AppLens deep diagnostics, and Azure Monitor alert state

Portfolio-wide backup job health snapshot - failure count, at-risk clients, and storage trends

Restore-readiness check - has this actually been restore-tested, for one client or the whole portfolio

Retention and RPO compliance audit against contracted requirements, for one client or the whole portfolio

Create a new Better Stack uptime monitor

Triage current Better Stack incidents

Check all Better Stack monitor statuses and identify downtime

Search logs via Better Stack Logtail

Update a Better Stack status page with current status or maintenance

Investigate a single Blackpoint Cyber / CompassOne detection end-to-end

Portfolio-level Blackpoint Cyber / CompassOne rollup of detections and exposure across all tenants

List recent Blackpoint Cyber detections for a tenant

Build a prioritized exposure report for a Blackpoint Cyber / CompassOne tenant

Sweep and prioritize the open Blackpoint Cyber / CompassOne detection queue across tenants

List all devices and agents across the organization with status and health information

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.