LLM Mart Basic
@llm-mart · Joined Jun 2026
Set up, repair, or migrate to Cloudflare Turnstile bot verification in an existing frontend and backend, including server-side Siteverify.
Audit, diagnose, or optimize website loading and interaction performance, Core Web Vitals, and Lighthouse performance scores.
Cloudflare Workers best practices for production applications. Use when writing, reviewing, or configuring Workers.
Run or troubleshoot Wrangler CLI commands and configure Worker projects for local development, deployment, and Cloudflare resource management.
Audit, diagnose, or optimize website loading and interaction performance, Core Web Vitals, and Lighthouse performance scores.
This skill should be used when user asks to "query OpenObserve", "create OpenObserve dashboard", "edit OpenObserve panel", "fetch OpenObserve logs", "run OpenObserve search", "list OpenObserve streams", "ingest into OpenObserve", or works with OpenObserve Cloud / self-hosted via
This skill should be used when user asks to "deploy to Hetzner", "create Hetzner server", "manage Hetzner Cloud", "hcloud CLI", or works with Hetzner Cloud infrastructure including servers, networks, firewalls, load balancers, DNS zones, and volumes.
This skill should be used when user asks to "deploy with Dokploy", "use Dokploy Cloud", "manage self-hosted Dokploy", "deploy Docker Compose on Dokploy", "manage Dokploy databases", "configure Dokploy domains", or "look up Dokploy CLI commands".
This skill should be used when user asks to "clean gone branches", "remove deleted local branches", "prune branches removed from remote", or explicitly invokes "clean-gone-branches".
This skill should be used when user asks to "commit these changes", "write commit message", "stage and commit", "create a commit", "commit staged files", or explicitly invokes "commit-staged".
This skill should be used when user asks to "address PR comments", "resolve PR feedback", "handle review comments", "fix PR issues", "respond to PR review", or explicitly invokes "resolve-pr-comments".
This skill should be used when user asks to "review a PR", "review pull request", "review this pr", "code review this PR", "check PR #N", provides a GitHub PR URL, or explicitly invokes "review-pr".
This skill should be used when the user asks "how to setup GitHub CLI", "configure gh", "gh auth not working", "GitHub CLI connection failed", "gh CLI error", or needs help with GitHub authentication.
This skill should be used when user asks to "update PR summary", "update PR description", "rewrite PR body", "refresh PR title and body", or explicitly invokes "update-pr-summary".
This skill should be used when user asks to "upload my model to Ultralytics Platform", "push this run to the platform", "upload a dataset to platform", "download a dataset from platform", "search platform datasets", "start cloud training", "train on platform GPUs", "export a mode
This skill should be used when user asks to "improve my mAP", "why is my model overfitting", "my training is diverging", "read my results.csv", "interpret my training curves", "my AP50 is good but AP50-95 is bad", "my recall is low", "how do I pick learning rate", "which augmenta
This skill should be used when creating Ultralytics-branded content of any kind, including PDF, PPTX, Canva, or Google Slides presentations, DOCX documents, marketing or newsletter HTML emails, social media post copy or visuals, website or landing page designs, and dataset or mod
This skill should be used when user asks to "query Azure resources", "list storage accounts", "manage Key Vault secrets", "work with Cosmos DB", "check AKS clusters", "use Azure MCP", or interact with any Azure service.
This skill should be used when user encounters "Azure MCP error", "Azure authentication failed", "az login required", "Azure CLI not found", or needs help configuring Azure MCP integration.
This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".
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.
/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.
Build AI Agents like playing LEGOs. Everything is a Plugin.
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13 views 0 likesruns anywhere. uses anything
18 views 0 likesOne macOS app for Claude Code, Codex, and every agent runtime you use — scheduled runs, global hotkey launcher, per-run git worktrees, one review board.
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4 views 0 likesClaude Code & Codex 本地 token 追踪 — 状态栏(Codex 业界首创伪 statusline)、GitHub 风格热力图、多模型成本分析。 | Local token tracker for Claude Code & Codex — status line (industry-first…
12 views 0 likesEmpower the Shell to think. Evolve Operations.
6 views 0 likes🤖 A full-stack Agent Chat Runtime for pre-production validation, built with act, TypeScript, and LangGraph JS combining streaming, multimodal, HITL, and tools…
14 views 0 likesCerul — video memory infrastructure for AI products. SDKs, CLI, MCP, and developer integrations.
17 views 0 likesStealth headless browser for AI agents — bypass Cloudflare, bot detection, and anti-scraping. Drop-in Puppeteer/Playwright replacement.
8 views 0 likesWeb research for your agents with smart and safe tooling + knowledge store
16 views 0 likesFuXi is a fast, self-contained AI coding agent that lives in your terminal — edit code, run commands, and drive tools, with cost-aware routing across LLM provid…
12 views 0 likes