LLM Mart Basic
@llm-mart · Joined Jun 2026
Research subagent execution: OODA-loop investigation, intelligence gathering, source evaluation.
Code quality review: conventions, naming, dead code, performance, test coverage
Domain-specific review: ADR compliance, business logic, SAP CC structural, pragmatic builder.
Multi-perspective review: newcomer, senior, pedant, contrarian, user advocate, meta-process.
System-level review: security, concurrency, error handling, observability, API contracts
Rive skeletal animation: @rive-app/react-canvas, state machines, character pipelines, combat integration.
SQLite with Peewee ORM: model definition, query optimization, migrations, transactions.
Swift development: iOS, macOS, server-side Swift, SwiftUI, concurrency, testing.
Systematic toolkit upgrades: adapt agents, skills, hooks when Claude Code ships updates.
Technical documentation: API docs, system architecture, runbooks, enterprise standards
Technical journalism: explainers, opinion pieces, analysis articles, long-form content.
Testing automation: Vitest, Playwright, E2E, coverage enforcement, CI/CD integration
Toolkit governance: edit skills, update routing tables, manage ADR lifecycle, enforce standards.
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a websit
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
Autonomous iteration loop: modify, verify, keep/discard against any metric
Use the ax CLI instead of curl + throwaway parsing scripts whenever you fetch a URL, explore an unknown web page, or extract structured data from HTML. Trigger whenever you are about to write an inline script (python3 heredoc, node -e, regex over HTML) or a bare curl for one-off
Use when working with icons in any project. Provides CLI for searching 200+ icon libraries (Iconify) and retrieving SVGs. Commands: `better-icons search <query>` to find icons, `better-icons get <id>` to get SVG. Also available as MCP server for AI agents.
Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progre
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
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
Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
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