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.
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.
/close-out
Close out
Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/audit-infra
Audit infra
Audit infra security: secrets, deps, CI/CD, webhooks, AI/skill files
/audit-solana
Audit solana
Audit Solana program code for exploitable bugs and write a findings report
/benchmark
Benchmark
Compare per-instruction CU with the stored baseline to catch regressions
/build-app
Build app
Build the web client (Next.js, Vite, React) and check env, types and bundle
/build-program
Build program
Build Solana programs (Anchor, Pinocchio, native), incl. verifiable builds
/build-unity
Build unity
Build the Unity project in batchmode for WebGL, desktop, Android or PSG1
/cleanup
Cleanup
Turn a solana-ai-kit fork into a project: set up CLAUDE.md, remove kit files
/commit-claude-config
Commit claude config
Un-ignore and commit the kit config dir, instruction file, .mcp.json and .gitmodules
/debug-user-tx
Debug user tx
Replay a user's failing transaction on forked state and map the error to source
/deploy
Deploy
Deploy a program to devnet, or to mainnet after the user's explicit go-ahead
/diff-review
Diff review
Review the branch diff for Solana security issues, CU waste and AI slop
/doctor
Doctor
Read-only check of toolchain and kit config, with one fix-it command per failure
/dream
Dream
Consolidate MEMORY.md and Project Learnings: dedupe, resolve conflicts, prune
/explain-code
Explain code
Explain Solana code with a diagram and a step-by-step walkthrough
AI agent orchestration kit for Windows, Linux/MacOS with Codex skills, hooks, routing rules and profiles for Claude, OpenCode, Cursor, Gemini and Windsurf.
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