LLM Mart Basic

Autotask ticket notes, attachments, and charges — the secondary entities attached to tickets: retrieving/searching notes and attachments, and creating, updating, or searching ticket charges for labor and expenses billed directly to a ticket.

Autotask ticket lifecycle: status/priority codes and transition rules, the ticket field schema, SLA calculation and clock behavior, escalation rules, ticket metrics, and the MCP tool surface (create, update, search, history, notes) for MSP service desk operations.

Autotask time entry structure: approval status codes and workflow, the time entry field schema, the billing rate hierarchy, budget and contract-limit validation, utilization analytics, and the MSP business rules for rounding and minimum billing increments.

The Autotask MCP lazy-loading pattern - four meta-tools (list_categories, list_category_tools, execute_tool, router) that expose the full 39+ tool catalog progressively instead of loading every tool schema upfront, plus the natural-language router for intent-based tool lookup.

Kaseya Quote Manager (Datto Commerce) API fundamentals: API-key auth and the gateway's header translation, the read-only `kqm_<entity>_list`/`_get` tool surface across the sales, procurement, catalog, CRM, and org domains, page/pageSize/modifiedAfter pagination, rate limits, and

Kaseya Quote Manager procurement data: purchase orders with their lines and costs, the suppliers they are placed with, and product-supplier records mapping catalog products to supplier SKUs and pricing. Read-only tool surface.

Kaseya Quote Manager quoting data: the quote → section → line item hierarchy, and the sales orders, order lines, and payments a quote becomes once accepted. Read-only tool surface.

Better Stack MCP and API surface across Uptime, Telemetry (Logtail), and Error Tracking: available tools, Bearer token authentication, API structure, cursor-based pagination, rate limiting, and error handling.

Better Stack incidents: incident records raised by uptime monitors or reported manually, and the triage, acknowledgment, and resolution lifecycle.

Better Stack log management (Logtail): log sources, structured log search and query syntax, log-based alerting, and log analysis workflows.

Better Stack uptime monitors: check types, monitor fields, heartbeat monitors, monitor groups, and create/update/pause/delete operations.

Better Stack on-call: on-call calendars and rotations, escalation and notification policies, alert routing, and determining who is currently on call.

Better Stack status pages: status page configuration, resources and components, maintenance windows, and public service-status communication.

Blumira agents (sensors) and the devices they run on: device inventory and filtering, agent health via last-seen timestamps, and agent deployment keys.

Blumira REST API fundamentals: JWT authentication, the dual `/org/*` vs `/msp/*` path structure, suffix-based filter operators, pagination parameters and response metadata, the stateful MCP navigation tools, and HTTP error causes.

The Blumira finding lifecycle: status and severity codes, resolution types, list filtering, enriched detail retrieval, assignment, and comment threads.

Blumira's MSP path group (`/msp/*`): managed-account enumeration, cross-account and per-account finding queries, per-account device, agent-key and user management, and how MSP paths differ from org paths.

Blumira resolution types (Valid, Not Applicable, False Positive): how to choose between them, their effect on security metrics and detection tuning, and the org- and MSP-level resolve calls.

Blumira organization users: listing and filtering users, user roles, and looking up the user IDs required for finding assignment and access audits.

Shape of the Checkpoint Harmony Email (Avanan) `hec_*` tool surface: the thirteen tools and what each reaches, the event/entity split that governs which tool accepts which id, the `responseEnvelope`/`responseData` result shape, `scrollId` pagination, and the auth, regional-routin

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

A green PR, a controller reporting success, and not one line of the new code running

Triage open Blumira findings by severity, presenting a prioritized list for review

Deep investigation of a specific Blumira finding with details, context, and comment history

MSP dashboard showing all managed accounts with open finding counts and severity breakdown

Resolve a Blumira finding with the appropriate resolution type and notes

Overall security posture review including open findings by severity, agent coverage, and trends

Run the complete CIPP M365 offboarding workflow for a departing user — capture audit state, revoke access, handle mailbox, reclaim licenses

Generate a portfolio-wide M365 security posture report — Secure Score equivalents, MFA enrollment, conditional access coverage, and domain authentication across all managed tenants

Find tenants that have drifted from the MSP's configured CIPP standards baseline — missing standards, standards in Report-only mode, recent compliance failures

Quick health snapshot for a single tenant — BPA failures, conditional access enforcement, MFA gaps, domain authentication, standards compliance

Log a time entry (billable activity) against a Clio matter

Consolidated view of one Clio matter — contacts, open tasks, recent activities, recent communications, and bills

Search Clio contacts by name, company, or email

Search or list Clio matters by name/client and status

Capacity forecast for cloud resources, scoped to a resource type or covering everything connected

Cloud cost anomaly and reclaimable-spend report for a given window

Full network health sweep across all connected network-monitoring tools — devices down, degraded links, and topology changes

Report control and configuration drift since the last known-good baseline for a client or the whole portfolio

Build a source-cited compliance evidence package for a client against a named framework

Draft evidence-backed answers to the standard cyber-insurance questionnaire for a client

List computers in ConnectWise Automate with optional filters

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.