LLM Mart Basic

Building applications ON Claude - the Anthropic API and Claude Agent SDK. Use for: anthropic api, claude api, messages api, tool use, function calling, prompt caching, agent sdk, claude-agent-sdk, structured output, json schema output, batches api, extended thinking, adaptive thi

Patterns for building production-quality CLI tools with predictable behavior, parseable output, and agentic workflows. Triggers: cli tool, command line tool, build cli, cli patterns, agentic cli, cli design, typer cli, click cli.

Cloudflare Workers + Wrangler edge ops: runtime, bindings, local dev, secrets, deploy/CI, Pages-vs-Workers. Triggers on: cloudflare workers, wrangler, wrangler deploy, wrangler.toml, KV, D1, R2, durable objects, queues, vectorize, compatibility_date, edge functions, illegal invoc

Analyze codebase with tokei (fast line counts by language) and difft (semantic AST-aware diffs). Get quick project overview without manual counting. Triggers on: how big is codebase, count lines of code, what languages, show semantic diff, compare files, code statistics.

Color for developers: color spaces, accessibility contrast, palette generation, CSS color functions, design tokens, dark mode. Triggers on: color, palette, contrast, WCAG, APCA, OKLCH, color-mix, dark mode colors, design tokens, CVD, color blind, P3, sRGB.

Docker, Kubernetes, and AWS ECS/Fargate patterns. Triggers on: Dockerfile, docker-compose, kubernetes, k8s, helm, pod, deployment, service, ingress, container, image, ecs, fargate, task definition, ecs service, awsvpc, FARGATE_SPOT, ALB, ecs vs kubernetes.

Craft CMS 5 development - content modeling, Twig templating, element queries, GraphQL, plugins, and the Craft 4-to-5 Matrix-as-entries change. Use for: craft cms, craftcms, craft 5, twig, pixel & tonic, matrix field, entry types, sections, element query, eager loading, blitz, pro

Cypress end-to-end and component testing operations - selector/retry-ability strategy, cy.intercept network stubbing, cy.session auth, component vs e2e, flake diagnosis, CI, Test Replay. Use for: cypress, e2e test, component test, cy.get, cy.intercept, cy.session, data-cy, data-t

Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data.

Build and run evals for LLM and agent systems: golden datasets, LLM-as-a-judge with bias control, trajectory/step/outcome scoring, adversarial refuters, and CI regression gates. Triggers on: eval, evals, eval harness, golden dataset, golden set, LLM-as-a-judge, judge rubric, judg

Deep explanation of complex code, files, or concepts. Dispatches skill-preloaded agents, uses structural search, generates mermaid diagrams. Triggers on: explain, deep dive, how does X work, architecture, data flow.

Comprehensive ffmpeg/ffprobe media processing: transcode, cut/trim/concat, color grading, loudness normalization, subtitles, GIFs, HLS packaging, hardware encoding, and quality gates (VMAF). Triggers on: ffmpeg, ffprobe, transcode, compress/convert video, extract audio, color gra

Router and composition workflows for Figma via the official Figma MCP: which Figma skill/tool for which job, capture-to-canvas (screenshots or shotcraft crops into a Figma file), moodboard and reference-board composition (grid, plus, loose-plus arrangements with a deterministic l

Modern find-and-replace using sd (simpler than sed) and batch replacement patterns. Triggers on: sd, find replace, batch replace, sed replacement, string replacement, rename.

Landing discipline for parallel work: sequential test-gated landing queue, pre-land scrub, auto-rebase of in-flight lanes, fleet status, one-shot revert. Native primitives spawn; fleet-ops lands. Triggers: landing queue, land branches, merge queue, test gate, fleet status, land a

Generative art programming - three.js scenes, p5.js sketches, SVG generation, GLSL shaders, procedural algorithms, and color for creative coding. Use for: generative art, creative coding, three.js, p5.js, SVG, GLSL, shader, noise, perlin, simplex, flow field, particle system, SDF

Git + worktree orchestrator: status survey, per-worktree triage, commits, PRs, branches, releases, rebases — reads inline, writes to a background agent. Triggers on: git status, anything to commit, anything to push, commit, push, create PR, rebase, release, tag, changelog, worktr

GitHub remote operations and README authoring: repo creation, metadata, releases, issue/PR management with preview-before-send, README as a landing page (badge row, features-as-benefits, screenshots, Recent Updates), and read-only security auditing. Triggers on: write a README, i

Go development patterns, concurrency, error handling, testing, and project structure. Use for: golang, go, goroutine, channel, context, errgroup, go test, go mod, go build, interface, generics, table-driven tests, worker pool, sync.Mutex, sync.WaitGroup, pprof, go vet, golangci-l

Hono on Cloudflare Workers - composition, middleware, typed bindings, validation, RPC, streaming, testing. Use for: hono, hono middleware, app.route, hono rpc, c.env bindings, onError, zValidator, vitest-pool-workers, spa fallback worker.

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.

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.

Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.

Orchestrate comprehensive multi-dimensional code review using specialized review agents across architecture, security, performance, testing, and best practices

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

Execute tasks from a track's implementation plan following TDD workflow

Manage track lifecycle: archive, restore, delete, rename, and cleanup

Create a new track with specification and phased implementation plan

Git-aware undo by logical work unit (track, phase, or task)

Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)

Display project status, active tracks, and next actions

Restore saved project context and decisions to resume a session

Save project context, decisions, and progress for a later session

Build features guided by data insights, A/B testing, and continuous measurement

Design and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring

Reduce cloud costs across AWS, Azure, and GCP through rightsizing, reserved and spot capacity, storage tuning, and cost monitoring

Migration monitoring, CDC, and observability infrastructure

SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server

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

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…