LLM Mart Basic
@llm-mart · Joined Jun 2026
Structured debugging methodology — reproduce, isolate, hypothesize, verify. Covers git bisect, binary search, logging, and minimal reproduction.
Monitor a build process (webpack, turbo, docker) for warnings and errors as they stream. Summarize issues and fix them before the build finishes.
Safely update an npm package by checking npmjs.com for the latest version, reading release notes, and handling minor vs major upgrades differently. For minor updates, just do it. For major updates, find the upgrade guide, validate breaking changes, and produce a detailed migratio
Enforce a configuration-driven design system when generating UI. Ensures consistent spacing, colors, typography, dark mode, interactions, and accessibility across all AI-generated components.
After making code changes, start the dev server, open the app in Cursor's built-in browser, and verify everything works — check rendering, console errors, and network health. Use proactively after any UI or API change.
Verify that a Markdown file has correct formatting — headings, lists, links, code blocks, spacing, and consistent style.
Visually QA a web application by launching it in Cursor's built-in browser, taking screenshots, checking console errors, and auditing network requests. Use after making UI changes to verify they look correct.
Write clear, conventional commit messages with proper type prefixes, scopes, and body content.
Write marketing copy for landing pages, product descriptions, CTAs, emails, and app UI text.
Analyze existing code and write comprehensive unit and integration tests for it. Detects the test framework, identifies untested code paths, and generates tests with proper mocking, edge cases, and assertions. Use when the user asks to add tests, improve coverage, or test a speci
A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
"Memory is the cornerstone of intelligent agents. Without it, every
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
Expert in designing and building autonomous AI agents. Masters tool
AI驱动的综合健康分析系统,整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
/deps-audit
Deps audit
Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.
/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.
/full-review
Full review
Orchestrate comprehensive multi-dimensional code review using specialized review agents across architecture, security, performance, testing, and best practices
/pr-enhance
Pr enhance
Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report
/implement
Implement
Execute tasks from a track's implementation plan following TDD workflow
/manage
Manage
Manage track lifecycle: archive, restore, delete, rename, and cleanup
/new-track
New track
Create a new track with specification and phased implementation plan
/revert
Revert
Git-aware undo by logical work unit (track, phase, or task)
/setup
Setup
Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)
/status
Status
Display project status, active tracks, and next actions
/context-restore
Context restore
Restore saved project context and decisions to resume a session
/context-save
Context save
Save project context, decisions, and progress for a later session
/data-driven-feature
Data driven feature
Build features guided by data insights, A/B testing, and continuous measurement
/data-pipeline
Data pipeline
Design and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring
/cost-optimize
Cost optimize
Reduce cloud costs across AWS, Azure, and GCP through rightsizing, reserved and spot capacity, storage tuning, and cost monitoring
/migration-observability
Migration observability
Migration monitoring, CDC, and observability infrastructure
/sql-migrations
Sql migrations
SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server
/smart-debug
Smart debug
AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.
/deps-audit
Deps audit
Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.
Make any song you can imagine
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