LLM Mart Basic
@llm-mart · Joined Jun 2026
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.
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.
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.
/schema
Schema
Check frontmatter against the schema
/scope
Scope
Pull knowledge into a project
/secrets
Secrets
Scan for credentials
/sources
Sources
Show what a claim rests on
/split
Split
Split an overloaded page
/stale
Stale
Find concept pages nobody has touched
/tags
Tags
Audit the tag vocabulary
/timeline
Timeline
How my sources developed over time
/trace
Trace
Show which pages an answer used
/typed-links
Typed links
Add relation types where they matter
/weekly
Weekly
The weekly review
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/ia-refine-prompt
ia-refine-prompt
Transform a vague prompt into precise, structured AI instructions
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
AI agent orchestration kit for Windows, Linux/MacOS with Codex skills, hooks, routing rules and profiles for Claude, OpenCode, Cursor, Gemini and Windsurf.
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