LLM Mart Basic

Create a merge request or pull request from the current branch: verify quality gates, enforce conventional commits, validate the title, and create it without a confirmation step. Use when the user says 'create MR', 'create PR', 'open a merge request', or 'raise a PR'.

Builds 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.

Reviews code exclusively for over-engineering and lists what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. Use when the user says 'review for over-engineering', 'is this over-engineered', or invokes /prune. Complements

Starts Phase 1 (Research) for a topic: reads every relevant file, optionally runs a panel of Explore teammates, and saves a research artifact to .claude/state/research/. Use when the user says 'research <topic>' or '/research', or before planning work in unfamiliar code. Research

Reviews a pull request with structured severity-based feedback. Use when asked to review a PR, asked for a code review, or given a PR number/URL.

Fetches and digests Sentry issue data (summary, tags, stack trace, breadcrumbs, latest event) by short ID, numeric issue ID, or sentry.io URL, for any Sentry org the local token can access. Use when the user mentions a Sentry issue or short ID (e.g. MY-PROJECT-4X2), pastes a sent

Runs pre-launch validation and the release workflow. Use when the user says 'ship', 'release', 'deploy', or 'ready to merge'.

Summarizes the current session's work into a diary entry at .claude/state/sessions/ and runs worktree auto-cleanup. Use when the user says 'summarize' or '/summarize', or when closing out a completed work session.

Breaks a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices. Use when the user wants to convert a plan into issues, create implementation tickets, or break down work into issues.

Runs the comprehensive quality gate before declaring work done: discovers the checks CI actually runs, executes them in order, then reviews git status and the session diff. Use when the user says 'verify done' or '/verify-done', or before pushing any branch.

Plans a huge chunk of work - more than one agent session can hold - as a shared map of decision tickets in a local file, and resolves them one at a time until the way to the destination is clear. Use when the user invokes /wayfinder on an effort too big for a single session.

Creates an isolated git worktree for the current task and switches into it, so the task never collides with the main checkout. Use when the user says '/worktree <slug>' or wants an isolated working copy for a new task.

Cleans up a worktree after its branch has been merged: removes the worktree directory and deletes the local branch. Use when the user says '/worktree-merge' or asks to clean up a merged worktree.

Audits and optionally prunes git worktrees: current repo by default, cross-repo scan under ~/dev/ with --all. Use when the user says '/worktrees', 'audit worktrees', or 'prune worktrees'.

Provides the reference and principles for writing and editing skills well - the vocabulary that makes a skill predictable. Use when creating, writing, editing, reviewing, or refactoring an agent skill.

Designs and reviews ArgoCD Applications, ApplicationSets, AppProjects, sync policies, and Argo Rollouts progressive delivery. Use when the task involves ArgoCD manifests, sync behavior, GitOps repo layout, or canary/blue-green rollouts. General Kubernetes and CI pipeline work bel

Designs and reviews AWS architecture, IAM, networking, and cloud cost. Use when the task involves AWS services, Terraform targeting AWS, a Well-Architected review, or AWS cost optimization. Not for GCP work (use GCP Expert); cross-provider IaC and pipeline concerns belong to DevO

Designs and reviews Node.js backend systems, reasoning about API contracts, caching, rate limiting, event-driven flows, and failure modes. Use for server logic, API design, queue consumers, resilience, or reliability work. Pairs with PostgreSQL Expert, who owns database internals

Threat-models code and architecture changes across trust boundaries, authn/authz flows, secrets handling, and injection surfaces, returning severity-ranked findings with concrete attack scenarios. Use when a change touches authentication, sessions, tokens, user-input processing,

Builds and reviews infrastructure-as-code, CI/CD pipelines, containers, and Kubernetes deployments. Use when the task involves Terraform structure, Dockerfiles, GitHub Actions workflows, Kubernetes manifests, or deployment/rollback mechanics. Provider-specific IAM and cost questi

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.

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.

Design concise overview, mechanism, or workflow figures as editable PowerPoint objects

Run the implement-review staged-change review loop

Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill

Run prun: parallel delegation fan-out on Agy workers (the session coordinates)

Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim

Vet the staged change: run the implement-review review loop (short alias)

Extract a learning from the recent conversation and add it to the appropriate instruction file

Extract a learning from the recent conversation and add it to the appropriate instruction file

Create a new pipeline from a task description. Fans out agent, skill, and hook scaffolding in parallel, then integrates into the routing system.

Jev-first router: A/B variant of /do. One TypeSafe call replaces the manifest read; falls back to /do when unavailable or unconfident.

Smart router: classify requests and route to the correct agent + skill

Generate project-specific CLAUDE.md from repo analysis.

Triage GitHub notifications: fetch, classify, report actions needed.

`github-profile-rules` — extract programming rules and coding conventions from a GitHub user's public profile via API.

Run the complete 34-stage implementation workflow for a large, multi-system, multi-wave, or CPU-delegated 5 Star Booker GM program.

Verify installation, diagnose issues, and guide first-time setup

Comprehensive PR review using specialized agents, with automatic retro knowledge capture

Reddit moderation: fetch modqueue, classify content, take mod actions

Learning system interface: stats, search, graduate learnings. Backed by learning.db (SQLite + FTS5).

Systematic upgrade pipeline for adapting agents, skills, and hooks when Claude Code ships updates, user goals change, or retro learnings accumulate.

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.