LLM Mart Basic
@llm-mart · Joined Jun 2026
Generates a Mermaid sequence diagram showing how data moves between components. Use when tracing request flows or documenting data transformation pipelines.
Route work into the right maestro tier and drive the SPEC/NOTES/VERIFY bundle lifecycle - open, resume, close, recall.
Settle unknowns and lock decisions before implementation - pick the mode per unknown (grill, research, prototype, model, wayfind), recall past bundles, walk one fork at a time, record every settled choice with a rationale, and open the bundle only when a Full trigger holds.
Verify and close - cross-check coverage, run the VERIFY table, deliver the verdict, harvest durable lessons into decisions, close the bundle, and never claim remote state from local evidence.
Drive one accepted implementation unit - smallest falsifiable behavior, minimum edits, evidence that names the real falsifier; red tests only inside a Full bundle.
Use the Unoplat Code Confluence CLI to run the local app, configure providers, add repositories, and generate AGENTS.md artifacts with automatic PR publication. Trigger when users mention Unoplat, Code Confluence, repository setup, AGENTS.md generation, or agent-md workflows.
Author and visually review evidence-based software architecture diagrams as D2 v0.7.1 source rendered with ELK to canonical SVG.
Guidance for TypeScript monorepos with mixed package managers. Use when codebase has inherited package manager and a workspace root.
Long-term Markdown project memory for AI coding agents. Use when the user wants to record, recall, audit, sync, or compress project decisions, architecture, conventions, monorepo scopes, or `.lore/` entries, including natural-language requests like "remember this decision" or exp
Refactor large DataRobot skill files by moving detailed content into directly linked reference files while preserving meaning. Use when a skill triggers context-window warnings, needs progressive disclosure, or should be chunked without changing guidance.
Use when the user wants to design, build, code, simulate, or deploy an AI agent (not a predictive model) to DataRobot; mentions agent_spec.md, dr-assist, datarobot-agent-assist, dress rehearsal, swarm simulation, or the DataRobot agent template; wants to scaffold a LangGraph, Cre
Guidance for setting up CI/CD pipelines for DataRobot application templates using GitLab, GitHub Actions, and Pulumi for infrastructure as code. Use when setting up CI/CD pipelines, configuring deployments, or managing infrastructure for DataRobot application templates.
Tools and guidance for data upload, dataset management, data validation, and preparing data for DataRobot projects. Use when uploading datasets, managing data, or validating data for DataRobot.
Use when the user wants to find DataRobot capabilities — skills, MCP servers, agents, or platform resources — for a task. Fetches the live DataRobot catalog directly so results are always current, regardless of third-party search index lag. Also checks the user's own DataRobot in
Instrument any external or existing AI agent with OpenTelemetry to send traces, logs, and metrics to DataRobot for monitoring, observability, and governance. Use when the user says "add tracing/observability/monitoring to my agent", wants to instrument an existing agent project i
Guidance for feature engineering, feature discovery, feature importance analysis, and understanding DataRobot's automated feature engineering capabilities. Use when working with feature engineering, feature discovery, or analyzing feature importance in DataRobot.
Tools and guidance for deploying DataRobot models, managing deployments, configuring prediction environments, and deployment operations. Use when deploying models, creating or updating deployments, or configuring prediction environments.
Tools and guidance for model explainability, prediction explanations, feature impact analysis, SHAP values, SHAP distributions, anomaly assessment, and model diagnostics. Use when analyzing model explanations, feature impact, SHAP values, SHAP distributions, anomaly assessment, o
Tools and guidance for monitoring model performance, tracking data drift, managing model health, and detecting prediction anomalies. Use when monitoring deployed models, tracking drift, or investigating prediction anomalies.
Comprehensive guidance for training models in DataRobot, including project creation, AutoML configuration, feature engineering, and model selection. Use when training models, creating AutoML projects, or selecting models in DataRobot.
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.
/lookup-config
Lookup config
Search for configuration items (assets) in ConnectWise PSA
/schedule-entry
Schedule entry
Create a schedule entry/appointment in ConnectWise PSA
/search-tickets
Search tickets
Search for tickets in ConnectWise PSA by various criteria
/update-ticket
Update ticket
Update fields on an existing ConnectWise PSA ticket
/search-surveys
Search surveys
Search recent Crewhu surveys, surfacing detractors and promoters
/error-budget
Error budget
Run the reliability scorecard for one service, or every connected service if omitted - error-budget burn rate where an SLO is defined, trend reporting otherwise
/oncall-brief
Oncall brief
Generate the current on-call handoff brief - what's paging, what's escalated without an owner, last-shift history, and known-flaky alerts to watch
/postmortem
Postmortem
Draft a blameless postmortem for a given incident (by ID or name), or the most recent significant incident within a time window
/device-inventory
Device inventory
List all devices at a Domotz-monitored site
/device-lookup
Device lookup
Find a Domotz device by name, IP address, or MAC address
/site-overview
Site overview
Overview of a Domotz site's network health
/check-threat
Check threat
Pull full detail for one Checkpoint Harmony Email detection and the message behind it
/release-quarantine
Release quarantine
Restore quarantined mail to its recipients in Checkpoint Harmony Email, with task polling
/search-quarantine
Search quarantine
Find messages in Checkpoint Harmony Email by sender, subject, attachment hash or quarantine state
/search-threats
Search threats
Sweep security events in Checkpoint Harmony Email by type, state, severity and date range
/campaign-summary
Campaign summary
Get summary of recent phishing and training campaigns from KnowBe4
/group-report
Group report
Get security awareness metrics for a KnowBe4 group
/phishing-results
Phishing results
View phishing campaign results and click rates from KnowBe4
/training-status
Training status
Check training completion status for users or groups in KnowBe4
/user-risk
User risk
Get risk score and risk history for a KnowBe4 user
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
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