LLM Mart Basic
@llm-mart · Joined Jun 2026
Configures GitHub Actions CI/CD workflows for testing, linting, and deployment. Use when setting up automation for a Python, Rust, or TypeScript project.
Applies client-server architecture for web/mobile apps. Use when designing systems with centralized backend services, trust boundaries, or offline-first sync.
Applies CQRS and Event Sourcing for read/write separation and audit trails. Use when designing systems with complex domain logic or full state-change history.
Models a business in its own language. Use when the domain has real business rules to capture.
Applies event-driven async messaging to decouple producers and consumers. Use when designing real-time or multi-subscriber systems needing loose coupling.
Applies Functional Core, Imperative Shell to isolate logic from side effects. Use when business logic is entangled with I/O or unit tests are slow and brittle.
Applies hexagonal architecture isolating domain from infrastructure. Use when designing systems where testability and port/adapter separation are priorities.
Applies layered n-tier architecture with enforced boundaries. Use when designing moderate systems needing clear presentation, domain, and persistence layers.
Applies microkernel architecture with minimal core and plugin extensibility. Use when building platforms where third parties extend core functionality.
Applies microservices for independent deployment and per-service scaling. Use when teams need autonomous release cycles with distinct capability scaling needs.
Applies modular monolith with enforced internal boundaries. Use when teams want service-level autonomy without distributed system overhead.
Applies pipes-and-filters for sequential data transformations. Use when data flows through discrete stages like ETL, streaming analytics, or CI/CD pipelines.
Applies serverless FaaS patterns for event-driven workloads. Use when designing bursty workloads with minimal infrastructure and pay-per-execution cost model.
Applies coarse-grained service architecture for deployment independence. Use when independent deployment is needed but shared databases rule out microservices.
Applies data-grid architecture for high-traffic stateful workloads. Use when a single database cannot scale and in-memory partitioning is needed.
Selects and routes to the right architecture paradigm. Use when choosing patterns for a new system or comparing trade-offs before making architecture decisions.
Generates a Mermaid architecture diagram showing high-level component relationships. Use when visualizing how plugins or modules fit together.
Traces execution paths through the code graph with criticality scoring and Mermaid charts. Use when understanding how a function propagates through the system.
Generates a Mermaid class diagram showing types, inheritance, and composition. Use when visualizing class hierarchies or documenting a module public API.
Detects architectural clusters and coupling boundaries via community detection on the code graph. Use when identifying module groupings or refactoring targets.
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.
/improve-agent
Improve agent
Improve an existing agent through performance baselines, prompt engineering, A/B testing, and staged rollout
/multi-agent-optimize
Multi agent optimize
Optimize multi-agent system performance through profiling, context window tuning, coordination efficiency, and cost and latency tradeoffs
/team-debug
Team debug
Debug issues using competing hypotheses with parallel investigation by multiple agents
/team-delegate
Team delegate
Task delegation dashboard for managing team workload, assignments, and rebalancing
/team-feature
Team feature
Develop features in parallel with multiple agents using file ownership boundaries and dependency management
/team-review
Team review
Launch a multi-reviewer parallel code review with specialized review dimensions
/team-shutdown
Team shutdown
Gracefully shut down an agent team, collect final results, and clean up resources
/team-spawn
Team spawn
Spawn an agent team using presets (review, debug, feature, fullstack, research, security, migration) or custom composition
/team-status
Team status
Display team members, task status, and progress for an active agent team
/api-mock
Api mock
Build realistic API mock servers with request stubbing, dynamic data, test scenarios, and contract testing
/performance-optimization
Performance optimization
Orchestrate end-to-end application performance optimization from profiling to monitoring
/feature-development
Feature development
Orchestrate end-to-end feature development from requirements to deployment
/block-no-verify
Block no verify
Set up PreToolUse hook to block --no-verify and other git bypass flags in Claude Code projects
/c4-architecture
C4 architecture
Generate comprehensive C4 architecture documentation (Context, Container, Component, Code) for a codebase using bottom-up analysis and four coordinated C4 agents.
/workflow-automate
Workflow automate
Automate CI/CD pipelines, releases, and development workflows with GitHub Actions, pre-commit hooks, and infrastructure automation
/code-explain
Code explain
Explain complex code, algorithms, and design patterns with step-by-step breakdowns, visual diagrams, and interactive examples
/doc-generate
Doc generate
Generate API, architecture, code, and user documentation from a codebase and automate keeping it current
/context-restore
Context restore
Restore saved project context and decisions to resume a session
/refactor-clean
Refactor clean
Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.
/tech-debt
Tech debt
Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.
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