LLM Mart Basic
@llm-mart · Joined Jun 2026
Solve a hard problem by trying multiple approaches in parallel using isolated git worktrees. Each attempt runs in its own branch, and the best solution is selected. Use for complex refactors, tricky bugs, or architectural decisions where multiple strategies could work.
When the same multi-step workflow repeats in Cursor (user corrections or agent redos), capture it as a new SKILL.md under .cursor/skills/ so future sessions load it automatically.
Launch multiple explore subagents in parallel to investigate architecture, data models, auth, APIs, and deployment. Synthesize into an onboarding document.
Check out two branches in separate worktrees, start both dev servers on different ports, screenshot the same pages, and produce a visual diff.
Migrate CSS Modules (.module.css/.module.scss) to Tailwind utility classes. Handles styles object removal, className interpolation, composition, and global overrides.
Convert plain CSS stylesheets to Tailwind CSS utility classes. Handles selectors, media queries, pseudo-classes, custom properties, and animations.
Create a clean, review-ready pull request with a good title, structured description, linked issues, and appropriate reviewers.
Toggle between light and dark mode in Cursor's browser, screenshot both states, and flag missing token mappings or contrast issues.
Design database schemas — tables, relationships, indexes, constraints, and ORM setup. Covers relational design, normalization, and common patterns.
Detect EADDRINUSE and port conflicts, find what's using the port, and resolve it by killing the process or suggesting an alternative port.
Export code, terminal output, diagrams, or UI components to PNG images using headless browser rendering or CLI tools.
Scan running terminals for dev server URLs (localhost ports), report them, and optionally open the app in Cursor's built-in browser.
Crawl all links in a file or project, test each for a valid HTTP response, report broken ones, and fix or remove them.
Use Cursor's browser to fill and submit every form in the app with valid and invalid data, verifying validation, error states, and success flows.
Generate or edit images using the OpenAI Image API (gpt-image-2). Use when the user asks to generate, create, draw, render, illustrate, mock up, or edit an image, icon, logo, mockup, illustration, OG image, blog hero, marketing asset, or similar visual. Also use when the user sup
Keep iterating on code changes until the tests pass, the build succeeds, or linting is clean. Runs in a tight loop of fix → run → check → repeat. Use when you want the agent to autonomously grind through test failures or build errors.
Handle production incidents — triage, mitigate, communicate, and write postmortems.
Deploy applications to Kubernetes — Deployments, Services, Ingress, ConfigMaps, Secrets, health checks, and scaling.
Watch running terminal processes for crashes and stack traces. When an error appears, navigate to the failing file and line, diagnose, and fix it automatically.
After navigating and interacting in Cursor's built-in browser, use browser_network_requests to audit every fetch/XHR for failures, slowness, duplicate calls, and suspicious payloads. Use for API-heavy pages and after backend or client networking changes.
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.
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.
/new
New
Create new spec and start research phase
/prototype
Prototype
Run or resume an optional prototype
/refactor
Refactor
Update spec files methodically after execution (requirements -> design -> tasks)
/requirements
Requirements
Generate requirements from goal and research
/research
Research
Run or re-run research phase for current spec
/start
Start
Smart entry point that detects if you need a new spec or should resume existing
/status
Status
Show all specs and their current status
/switch
Switch
Switch active spec
/tasks
Tasks
Generate implementation tasks from design
/triage
Triage
Decompose a large feature into multiple dependency-aware specs (epic triage)
/tree-ring-update
Tree ring update
Check for or install a verified Tree Ring Memory CLI update without changing installation scope
/README
README
This directory contains the command implementations for the fast-agent CLI.
/close
Close
They operate it without you.
/outcome
Outcome
Promised, measured, accepted. A number nobody signed is claimed, not delivered.
/prep
Prep
Prepare the meeting. One page from the record.
/receipts
Receipts
Find the receipt. A dated line, or it did not happen.
/trust
Trust
Diagnose trust. Process gap, or they stopped trusting you.
/awesome-docs
awesome-docs
Generate, convert, and maintain animated GitHub-safe Markdown documents with animated SVG diagrams. Covers four SVG patterns (architecture flow, lifecycle loop, field carousel, timeline phases), guided interview for any doc type (README, architecture guide, runbook, API reference, tutorial, RFC, post-mortem, how-it-works, or custom), converting existing plain Markdown, diffing for stale diagrams, quality auditing, local preview, and multi-platform export. Use when asked to "create a README for X", "write an architecture doc", "animate this guide", "convert my doc to animated", "check if my diagrams are stale", or "export my doc for Confluence".
/aws-profile
aws-profile
AWS profile management for MCP servers — discover profiles across SSO, Granted, and assumed-role chains, check credential TTL, switch profiles across VS Code and Claude Code MCP configs, and scan AWS Organization accounts.
/aws
aws
Structured guidance for AWS CloudFront distributions, WAF web ACLs, Lambda@Edge, CloudFront Functions, Firewall Manager multi-account enforcement, and IAM/IRSA patterns. Covers OAC, cache policies, security headers, managed rule groups, rate limiting, FMS FIRST/MIDDLE/LAST ownership model, and production-ready Terraform generation.
Atom Agent, Open-Source Governed AI Agent Platform for Self-Hosted Automation
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