LLM Mart Basic

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.

Source, vet, normalize and ship SVG icons for web UI - set selection, licence and trademark traps, currentColor theming, sprite/inline delivery, and accessibility. Triggers on: icon, icons, svg icon, find an icon, add an icon, icon set, icon library, iconify, lucide, heroicons, p

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

Daily standup: all 8 departments report on the current project in parallel

Identify skills injected where not needed, propose regex and description tightening

Draft X/Twitter announcement post (or thread) for the latest plugin release

Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste

Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes

Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization

Propose a skill revision and compare fresh executions under a frozen rubric

Prune stale entries from the whetstone sync decision log

Bump version, commit, push, mirror to ai-skills, and update local plugin

Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).

Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns

Triage all open PRs with parallel agents, label, group, and review one-by-one

Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).

Create Architecture Decision Records with format selection and lifecycle management

Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps

Explore requirements and approaches through collaborative dialogue before planning implementation

Create engaging changelogs for recent merges to main branch

Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps

Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.

Record a video walkthrough of a feature and add it to the PR description

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.