LLM Mart Basic
@llm-mart · Joined Jun 2026
Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.
Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.
Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.
Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.
Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.
Investigate data incidents and find root causes using Monte Carlo's observability data. Guides the agent through systematic investigation: alert lookup, lineage tracing, ETL checks, query analysis, and data profiling. Activates when a user asks about data issues, incidents, alert
Check the health of a data table/asset using Monte Carlo. Activates on "how is table X", "check health of X", "is X healthy", "status of X", "check on X table", or any health/status question about a data asset.
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
Build a Connection Auth Rules for a Monte Carlo connection type. Fetches live connector schemas and transform steps from the apollo-agent repo.
Route data-related requests to the right Monte Carlo skill or workflow. USE WHEN alerts, incidents, data broken, stale, coverage gaps, data quality, or any ambiguous data observability request.
Generate SQL validation notebooks for dbt changes. Pass a GitHub PR URL or local dbt repo path.
Orchestrate incident response — triage, root cause, remediate, prevent recurrence. USE WHEN active alerts, data broken, stale, pipeline failure, or investigate and fix a data incident.
Instrument a new AI agent in a Python codebase for Monte Carlo Agent Observability. Detects AI libraries, installs the Monte Carlo OpenTelemetry SDK, and proposes tracing setup and decorator placements as diffs. Asks before editing any file.
Create, edit, validate, and import Monitors-as-Code YAML files. CLI-first; falls back to MC MCP tools, then manual validation.
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.
/search-contacts
Search contacts
Search Clio contacts by name, company, or email
/search-matters
Search matters
Search or list Clio matters by name/client and status
/capacity-check
Capacity check
Capacity forecast for cloud resources, scoped to a resource type or covering everything connected
/cost-report
Cost report
Cloud cost anomaly and reclaimable-spend report for a given window
/network-sweep
Network sweep
Full network health sweep across all connected network-monitoring tools — devices down, degraded links, and topology changes
/drift-report
Drift report
Report control and configuration drift since the last known-good baseline for a client or the whole portfolio
/evidence-pack
Evidence pack
Build a source-cited compliance evidence package for a client against a named framework
/questionnaire
Questionnaire
Draft evidence-backed answers to the standard cyber-insurance questionnaire for a client
/list-computers
List computers
List computers in ConnectWise Automate with optional filters
/run-script
Run script
Execute a script on an endpoint in ConnectWise Automate
/create-quote
Create quote
Create a ConnectWise CPQ quote by copying a template or an existing quote
/get-quote
Get quote
Get a ConnectWise CPQ quote with its tabs, line items, customers, and terms
/list-templates
List templates
List ConnectWise CPQ quote templates available to copy
/search-quotes
Search quotes
Search ConnectWise CPQ quotes by account, status, or date range
/add-note
Add note
Add an internal or external note to a ConnectWise PSA ticket
/check-agreement
Check agreement
View agreement status and entitlements for a company in ConnectWise PSA
/close-ticket
Close ticket
Close a ConnectWise PSA ticket with resolution notes
/create-ticket
Create ticket
Create a new service ticket in ConnectWise PSA
/get-ticket
Get ticket
Retrieve detailed ticket information from ConnectWise PSA
/log-time
Log time
Log a time entry against a ConnectWise PSA ticket
Your car as a chat-room agent: Raspberry Pi 5 + dashcam + local AI. CodeWatch's sibling for the garage.
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