LLM Mart Basic
@llm-mart · Joined Jun 2026
When GitHub Actions fails, fetch failing job logs and assign each failing job to a separate subagent that fixes its slice of the problem in parallel. Use for multi-job CI failures where jobs are independent.
Run four parallel read-only subagents that each review the same diff from a different lens — security, performance, correctness, and readability — then merge findings into one report. Use before merging large or risky PRs.
Explore a large codebase in parallel by launching multiple explore subagents that each investigate a different area simultaneously. Use when onboarding onto a new project, understanding architecture, or investigating a cross-cutting concern.
When multiple tests fail, assign each failing test file to a separate subagent that fixes it independently in parallel.
Profile a running web application's CPU performance using Cursor's built-in browser profiler. Captures call stacks, identifies slow functions, and suggests optimizations. Use when a page feels slow or janky.
Write effective prompts for LLMs — structure, few-shot examples, chain-of-thought, system prompts, and output parsing.
Test-driven development in Python using uv as the package manager. Covers the red-green-refactor cycle, vertical slicing, and uv project setup.
Build mobile apps with React Native and Expo — navigation, platform-specific code, performance, and native modules.
Execute a user flow step-by-step in Cursor's built-in browser while documenting each action, then emit a Playwright test that replays the same flow using stable selectors derived from the accessibility tree.
Open the app in Cursor's browser at multiple viewport sizes, screenshot each, and report any layout breakage.
Perform a thorough code review focused on correctness, maintainability, performance, and best practices.
Automatically persist useful context — research, decisions, learnings, templates — to workspace files so knowledge survives across conversations.
Generate a visual changelog or PR description by taking before/after screenshots of UI changes using Cursor's built-in browser. Use when preparing a PR with visual changes.
Audit technical SEO — meta tags, structured data, Open Graph, sitemaps, robots.txt, performance, and accessibility signals.
Set up a GitHub Actions CI/CD pipeline with linting, testing, type-checking, and deployment steps.
Set up Terraform infrastructure-as-code for cloud resources, including provider configuration, modules, state management, and CI integration.
When the user keeps asking for the same check to run (lint, tests, type-check), suggest a Cursor hook to automate it.
When the user repeats the same correction or convention multiple times, suggest a Cursor rule to encode it permanently.
When the user struggles with a task that a known skill could handle, suggest installing it.
Switch the current Cursor workspace to a different project directory using the cursor-app-control MCP. Use when the user asks to switch projects, open another repo, jump to a different codebase, or move to a worktree.
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.
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.
/inspect
Inspect
`crabbox inspect` prints the full record for a single lease: state, provider,
/job
Job
Run named, repo-local jobs defined in your Crabbox config.
/list
List
`crabbox list` shows the current Crabbox machines (leases) for a provider. It is
/login
Login
`crabbox login` authenticates the CLI against a coordinator, stores the
/logout
Logout
`crabbox logout` clears the stored broker token from your user config so the CLI
/logs
Logs
`crabbox logs` prints the retained command output for a recorded run.
/marketplace
Marketplace
`crabbox marketplace` previews the Crabbox credits gateway: one Crabbox billing
/media
Media
`crabbox media` turns a recorded desktop video into lightweight review
/open
Open
`crabbox open` prepares an existing SSH-capable lease for an external editor.
/pause
Pause
`crabbox pause` pauses a single lease, freeing the remote compute while
/pond
Pond
`crabbox pond` is the cross-provider peer-discovery and lifecycle surface for a
/pool
Pool
`crabbox pool` contains machine-pool helpers. `pool list` keeps the older
/ports
Ports
`crabbox ports` bridges provider-native port publishing for an existing Crabbox
/prewarm
Prewarm
`crabbox prewarm` leases a reusable box and prepares it for test runs. For
/providers
Providers
`crabbox providers` prints the provider capability matrix that the CLI compiles
/receipt
Receipt
`crabbox receipt <run-id>` retrieves a brokered run's committed terminal
/results
Results
`crabbox results` prints the structured test summary attached to a recorded
/resume
Resume
`crabbox resume` resumes a lease previously paused with [`pause`](pause.md),
/run
Run
`crabbox run` syncs the current dirty checkout to a box, runs a command there,
/screenshot
Screenshot
`crabbox screenshot` captures a single PNG from a desktop lease without opening a
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