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.
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.
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.
/social
Social
Run an organic-social (ECHO) workflow: channel portfolio and voice dossiers, platform-native content and calendars, the social-quality gate with a pre-publish go/no-go, community/inbox/crisis operations, and the listening/SOV/dark-social measurement loop. Not sure? Use /aaron-marketing:auto.
/minutes-mcp-recall
Minutes mcp recall
Route meeting-recall questions to the right Minutes MCP tool.
/minutes-x1-closeout
Minutes x1 closeout
Prepare a sourced Minutes meeting outcome for human-governed closeout of existing X1 work. Use when the user wants a meeting decision or commitment to close, defer, escalate, or retire a specific X1 coordination thread. Never use it to infer settlement, move money, contact anyone, or close X1 work automatically.
/minutes-mcp-recall
Minutes mcp recall
Route meeting-recall questions to the right Minutes MCP tool.
/minutes-x1-closeout
Minutes x1 closeout
Prepare a sourced Minutes meeting outcome for human-governed closeout of existing X1 work. Use when the user wants a meeting decision or commitment to close, defer, escalate, or retire a specific X1 coordination thread. Never use it to infer settlement, move money, contact anyone, or close X1 work automatically.
/capacity
Capacity
`crabbox capacity [--json]` reports the authenticated owner's current admission
/code-review
Code review
Code review the current proposed code change
/merge-conflict
Merge conflict
Resolve a merge conflict
/pr-review
Pr review
Code review for pull request $1
/6hats
6hats
Six Thinking Hats Analysis
/README
README
Slash commands shipped by the plugin. Portable framework commands work in any Claude Code session; the workflow commands embed one author's personal setup and are opt-in - see [Adapting for your workflow](../README.md#adapting-for-your-workflow) before relying on them. Back to th
/fix-develop
fix-develop
Autonomous fix loop for failing CI on the repo's default branch
/fix-pr
fix-pr
Autonomous PR fixing loop - iterates on CI failures and review comments until green
/issues
issues
GitHub-issue marathon - triage open issues, then run agent-ready ones to merge with Agent Teams
/tm-marathon-config-example
tm-marathon-config-example
Example Marathon Configuration for CLAUDE.md - copy the section below into your project's CLAUDE.md
/tm
tm
Task Master - plan, start, review, and close
/understand
understand
Deep understanding mode (nemawashi) - exhaustive context-gathering before action
/burp-search
Burp search
Searches Burp Suite project files for security analysis
/ct-check
Ct check
Detects timing side-channels in cryptographic code
/diff-review
Diff review
Performs security-focused differential review of code changes
Make any song you can imagine
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