LLM Mart Basic

Finds deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI

Read and write Jira work items through the acli CLI. Use when the user mentions a Jira ticket, issue, story, bug, or epic, drops a Jira key like SER-123, or pastes an atlassian.net/browse URL.

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

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.

Systematic workflow for fixing bugs including issue creation, branch management, and PR submission

Bulk import GitHub issues to Linear

Explore multiple business timeline scenarios with constraint validation and decision optimization.

Demo changelog automation features

Perform comprehensive analysis of $ARGUMENTS to identify code quality issues, security vulnerabilities, and optimization opportunities.

Run project checks and fix any errors without committing

Setup continuous integration pipeline

Clean up merged and stale git branches

Fix all linting and formatting issues across the codebase

Test multiple code variations through simulation before implementation with quality gates and performance prediction.

Perform comprehensive code quality review

Convert code analysis to Linear tasks

Perform comprehensive code analysis with quality metrics and recommendations

Automatically create and execute a git commit using the first suggested commit message

Create well-formatted git commits with conventional commit messages and emoji

Model world constraints with assumption validation, dependency mapping, and scenario boundary definition.

Containerize application for deployment

Load project context by reading README.md and exploring relevant project files

Generate comprehensive architecture documentation

Create a new command following existing patterns and organizational structure

The fastest way to put Volcengine Ark in your terminal and your AI agent — go from prompt to generated media, multimodal answer, or deployed endpoint in a sin…

本地私有、开源的自进化跨平台 AI 内容发现 Agent：先理解你，再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。（支持 deepseek harness 插件） | Local-first open-source cross-platform AI cont…

Persistent memory for AI coding agents — one verified kb_search replaces the grep/find/ls orientation loop. Cross-repo, CPU-only, zero token spend.

AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Co…

The batteries-included, No-Code FinOps automation platform, with the AI you trust.

Open-source 3D AI agent framework — GLB/glTF avatars with LLM brains, memory, emotions, and autonomous payments. MCP server · x402 · Solana/EVM · Three.js. Embe…

XLSX parser for LLMs, RAG, LangChain, LangGraph, CrewAI, Claude, MCP — turns Excel (.xlsx) into citation-ready JSON with formulas, charts, dependency graphs, an…

Hermes-Relay — Your Hermes AI agent, in your pocket — chat, voice, and control.

A minimalist, terminal-native coding agent written in C.

AI-powered OSINT agent with interactive REPL, MCP server, and CLI. 19 tools. Works with Claude, GPT-4, or local models. For authorized security research only.

AI pair programming in your terminal — one static binary, sub-ms startup, any model

Where data access meets operational intelligence

Build your own security agents. Open-source framework for agents with live, read-only access to your infrastructure, with no path to widen it. Reasons across AW…

Multi-workspace terminal aggregator with Claude Code AI integration

Go implementation of AI coding agent

Harness engineering beginner tutorial, from 0 to 1

Generate images directly in DeepSeek Harness chats

A smarter, self-hosted AI assistant — multi-user, multi-agent.

Turn any research paper into a commercialization report — 6 AI agents, TRL/MRL scoring, patent landscape, market intelligence, verified citations. DeepSeek / Op…

Power BI CLI - semantic models (.NET TOM) and PBIR reports for token-efficient AI agent usage, built for Claude Code