LLM Mart Basic
@llm-mart · Joined Jun 2026
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when cre
Use when needing global or relational understanding of codebases or knowledge corpora. Keywords: GraphRAG, knowledge graph, entity extraction, community summarization, graph traversal, Microsoft GraphRAG.
Internationalization and localization patterns. Detecting hardcoded strings, managing translations, locale files, RTL support.
Implement a piece of work based on a spec or set of tickets.
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-
Automatic quality control, linting, and static analysis procedures. Use after every code modification to ensure syntax correctness and project standards. Triggers onKeywords: lint, format, check, validate, types, static analysis.
Use when validating, benchmarking, or monitoring LLM application performance. Keywords: RAG evaluation, LLM-as-a-judge, CI/CD gating, trajectory scoring, test suites, prompt quality.
Next.js App Router principles. Server Components, data fetching, routing patterns.
Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.
Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled refer
Performance profiling principles. Measurement, analysis, and optimization techniques.
Use when the task requires automating a real browser from the terminal (navigation, form filling, snapshots, screenshots, data extraction, UI-flow debugging) via `playwright-cli` or the bundled wrapper script.
Persistent browser and Electron interaction through `js_repl` for fast iterative UI debugging.
Use when designing, optimizing, testing, or deploying robust prompt systems for AI agents. This skill provides frameworks for structured prompt engineering, meta-prompting, and automated optimization workflows.
Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.
Modern React patterns and principles. Hooks, composition, performance, TypeScript best practices.
Deploy applications to Render by analyzing codebases, generating render.yaml Blueprints, and providing Dashboard deeplinks. Use when the user wants to deploy, host, publish, or set up their application on Render's cloud platform.
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
/smart-fix
Smart fix
Intelligent issue resolution with multi-agent debugging, root cause analysis, and verified fix implementation
/typescript-scaffold
Typescript scaffold
Scaffold a TypeScript project (Next.js, React with Vite, Node.js API, or library) with pnpm, testing, and dev tooling
/ai-assistant
Ai assistant
Build AI assistant application with NLU, dialog management, and integrations
/langchain-agent
Langchain agent
Create LangGraph-based agent with modern patterns
/prompt-optimize
Prompt optimize
Optimize prompts for production with CoT, few-shot, and constitutional AI patterns
/finetune
Finetune
Run the eval-gated fine-tuning lifecycle end to end — eval harness, method selection, data, environment, training, checkpoint gate, export
/promote-checkpoint
Promote checkpoint
Re-gate an existing fine-tuned checkpoint against the current eval harness and export it on PROMOTE
/ml-pipeline
Ml pipeline
Orchestrate specialized agents to build a production ML pipeline from data analysis through training, deployment, and monitoring
/find
Find
Quick gallery search. Use when user runs /meigen-ai-design:find with keywords to browse inspiration.
/gen
Gen
Quick image generation. Use when user runs /meigen-ai-design:gen with a prompt. Skips intent assessment, generates directly.
/multi-platform
Multi platform
Orchestrate cross-platform feature development across web, mobile, and desktop with API-first architecture
/monitor-setup
Monitor setup
Set up monitoring and observability with Prometheus metrics, Grafana dashboards, distributed tracing, log aggregation, and alerting
/slo-implement
Slo implement
Implement SLOs with SLI selection, error budgets, burn-rate alerting, dashboards, and reporting
/ai-review
Ai review
Run an AI-assisted code review that combines static analysis tools with AI review of security, performance, and architecture
/multi-agent-review
Multi agent review
Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review
/certify
Certify
Full quality certification with badge
/compare
Compare
Compare two skills head-to-head
/eval
Eval
Evaluate a plugin or skill for quality
/audit-chain
Audit chain
Verify every receipt in ./receipts/receipts.jsonl against the signer's public key. Detects tampered or malformed receipts across the audit trail.
/verify-receipt
Verify receipt
Verify a single Ed25519-signed receipt file against the signer's public key. Returns exit 0 if valid, 1 if tampered, 2 if malformed or the key is missing.
Make any song you can imagine
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