LLM Mart Basic
@llm-mart · Joined Jun 2026
Nx monorepo build system — workspace configuration, project graph, task pipelines, caching, generators, plugins, and release management
pnpm workspace protocol, filtering, catalogs, shared dependencies, publishing, and CI/CD for monorepo management
Turborepo, workspaces, package architecture, @repo/* naming, exports, tree-shaking
Secrets management, XSS prevention, CSRF protection, dependency scanning, DOMPurify sanitization, CSP headers, CODEOWNERS, HttpOnly cookies
Biome v2 unified linter, formatter, and import organizer — single Rust-powered tool replacing ESLint + Prettier with 97% Prettier compatibility and 20x faster performance
An agent designed to assist with software development tasks for .NET projects.
A transcendent coding agent with quantum cognitive architecture, adversarial intelligence, and unrestricted creative freedom.
Ultimate Transparent Thinking Beast Mode
Support development of .NET (OOP) WinForms Designer compatible Apps.
Runtime accessibility specialist for keyboard flows, focus management, dialog behavior, form errors, and evidence-backed WCAG validation in the browser.
Expert assistant for web accessibility (WCAG 2.1/2.2), inclusive UX, and a11y testing
Address PR comments
Expert agent for creating comprehensive Architectural Decision Records (ADRs) with structured formatting optimized for AI consumption and human readability.
Expert assistant for developing AEM components using HTL, Tailwind CSS, and Figma-to-code workflows with design system integration
AI agent governance expert that reviews code for safety issues, missing governance controls, and helps implement policy enforcement, trust scoring, and audit trails in agent systems.
Runs the AgentRC readiness assessment on the current repository and produces a self-contained, static HTML dashboard at reports/index.html. Explains every readiness pillar, the maturity level, and an actionable remediation plan, framed by AgentRC measure → generate → maintain loo
AI development team (Nova, Sage, Milo). Use when implementing features, fixing bugs, writing tests, improving user experience, or preparing a pull request across the project's actual stack.
AI team producer (Remy). Use when planning work, clarifying scope, coordinating Dev and optional QA, triaging issues, maintaining project context, or preparing and merging pull requests. Never writes application code.
Optional AI QA engineer (Ivy). Use when testing behavior, running automated or exploratory checks, filing reproducible bugs, verifying fixes, or providing release confidence for changes that warrant dedicated QA.
Your role is that of an API architect. Help mentor the engineer by providing guidance, support, and working code.
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.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
/session-replay
session-replay
Convert a Claude Code or Codex session JSONL file into an animated replay of the conversation.
/session-to-post
session-to-post
Convert the current session's work into a shareable blog post, case study, or social thread.
/style-learn
style-learn
Extract writing style from exemplar text to create a reusable style profile.
/voice-extract
voice-extract
Extract your writing voice from samples into a reusable profile
/voice-generate
voice-generate
Generate text in your extracted writing voice
/voice-learn
voice-learn
Run learning pass on manually edited text to improve voice profile
/voice-review
voice-review
Review existing text against a voice profile
/record-browser
record-browser
Record browser sessions using Playwright
/record-terminal
record-terminal
Create terminal recordings with VHS tape scripts
/speckit-analyze
Speckit analyze
Cross-artifact consistency analysis across spec.md, plan.md, and tasks.md after task generation
/speckit-checklist
Speckit checklist
Generate a custom checklist for the current feature based on user requirements.
/speckit-clarify
speckit-clarify
Ask targeted questions to resolve spec ambiguities
/speckit-constitution
Speckit constitution
Create/update project constitution from principle inputs, syncing dependent templates
/speckit-converge
Speckit converge
Assess the codebase against spec, plan, and tasks, then append unbuilt work as new convergence tasks
/speckit-implement
Speckit implement
Execute the implementation plan by processing all tasks from tasks.md
/speckit-plan
Speckit plan
Execute implementation planning from spec to generate design artifacts.
/speckit-specify
Speckit specify
Create or update the feature specification from a natural language feature description.
/speckit-startup
Speckit startup
Bootstrap spec-driven development workflow at the start of a session
/speckit-tasks
speckit-tasks
Generate dependency-ordered tasks.md from design artifacts
/speckit-taskstoissues
speckit-taskstoissues
Convert tasks.md entries into GitHub Issues
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