LLM Mart Basic

Expert assistant for building Model Context Protocol (MCP) servers in Go using the official SDK.

Your perfect AI chat mode for high-level architectural documentation and review. Perfect for targeted updates after a story or researching that legacy system when nobody remembers what it's supposed to be doing.

Generate an implementation plan for new features or refactoring existing code.

Specialized agent for tracking and analyzing accessibility improvements in VS Code Insiders builds

Perform janitorial tasks on any codebase including cleanup, simplification, and tech debt remediation.

Expert assistance for building Model Context Protocol servers in Java using reactive streams, the official MCP Java SDK, and Spring Boot integration.

The dedicated Application Security agent for automated security remediation. Verifies package and version compliance, and suggests vulnerability fixes using JFrog security intelligence.

Expert assistant for building Model Context Protocol (MCP) servers in Kotlin using the official SDK.

Kubernetes operations expert for KubeStellar Console — helps you set up the console, configure kc-agent (MCP server), connect clusters, deploy workloads, and query live Kubernetes data via AI chat.

Expert KQL assistant for live Azure Data Explorer analysis via Azure MCP server

Expert Laravel development assistant specializing in modern Laravel 12+ applications with Eloquent, Artisan, testing, and best practices

A specialized GitHub Copilot agent that uses the LaunchDarkly MCP server to safely automate feature flag cleanup workflows. This agent determines removal readiness, identifies the correct forward value, and creates PRs that preserve production behavior while removing obsolete fla

Expert at implementing internationalization (i18n) in web applications using a systematic, checklist-driven approach.

Draft and format compelling LinkedIn posts with Unicode bold/italic styling, visual separators, and engagement-optimized structure. Transforms raw content, technical material, images, or ideas into copy-paste-ready LinkedIn posts.

Improves the accessibility of markdown files using five GitHub best practices

Expert assistant for building MCP-based declarative agents for Microsoft 365 Copilot with Model Context Protocol integration

Help mentor the engineer by providing guidance and support.

Socratic mentor for junior developers. Guides through questions, never gives direct answers. Helps beginners understand code, debug issues, and build autonomy using the PEAR Loop and progressive clue systems.

Meta agentic project creation assistant to help users create and manage project workflows effectively.

Activate your personal Microsoft/Azure tutor - learn through guided discovery, not just answers.

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.

Validate application configuration with schemas, per-environment rules, runtime checks, and secure handling of sensitive values

Preflight a DGX Spark system for an ML training or inference workload and emit env-report.json

Set up debugging and tracing with remote debugging, distributed tracing, debug logging, profiling, and production diagnostics

Generate API, architecture, code, and user documentation from a codebase and automate keeping it current

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Generate comprehensive migration plans and scripts for transitioning codebases between frameworks, languages, versions, or platforms with minimal disruption.

Plan and execute safe, incremental dependency upgrades with minimal risk — including breaking-change migration paths and proper test verification.

Orchestrate legacy system modernization using the strangler fig pattern with gradual component replacement

Scaffold React and React Native components with TypeScript, tests, styles, and Storybook stories

Scan React, Vue, Angular, and vanilla JavaScript code for XSS vulnerabilities and report fixes with secure coding examples

Orchestrate end-to-end full-stack feature development across backend, frontend, database, and infrastructure layers

Orchestrate git workflow from code review through PR creation with quality gates

Create a role-specific onboarding plan for a new team member, from pre-arrival setup through the first 90 days

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning

Your efficient agentic AI coding CLI assistant

AI coding with Aegis governance built into execution: baseline-aware changes, evidence-backed delivery. Free desktop client, your choice of model. 将哲科思维融入 AI 开发…

Android in docker solution with noVNC supported, video recording, mcp server and AI-agent