LLM Mart Basic

TypeScript best practices. Use when reading or editing any .ts or .tsx file.

Cut AI tells from any writing. Must always apply.

Summarize authored commits over a user-specified time period into a concise update

Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability,

Anti-AI detection pass for any written text. Hard rules that strip the statistical fingerprints AI writing leaves behind — em-dash density, contrastive formula ("not X, it's Y"), nuclear phrases, copula inflation, sycophantic filler, uniform contractions, colon overuse, register

Channel-agnostic writer for any piece of content that doesn't yet belong to a specific channel. Use when you have something to say but don't know where it goes — could become a blog post, X thread, newsletter section, web copy, journal entry, or just stay as a plain doc. Runs the

Channel-master writer for long-form blog posts. Owns the SHAPE of a post — beat structure, title/preview/slug commitments, per-post container layout, per-site voice anchor discovery — and delegates VOICE (prose generation) to /authors-voice and PUBLISH mechanics to the openwriter

Orchestration skill for book-scale long-form writing (fiction or nonfiction). Owns the SHAPE of a book project — chapter architecture, beats methodology, workspace management, book mode, scene/science split, vignette library, long-form orchestration. Delegates VOICE (prose genera

Channel-master writer for email newsletter. Weekly pipeline: scaffold structure, gather data, query the author, synthesize in their voice, review, send. Companion doc workflow. Voice-matched via the authors-voice skill. Works for any behind-the-scenes weekly newsletter built on p

OpenWriter — the writing surface for AI agents. A markdown-native rich text editor where agents write via MCP tools and users accept or reject changes in-browser. 40 core MCP tools for document editing, multi-doc workspaces, and organization, plus 21 publish platform tools for ne

Polish copy to 90/100. Channel the top 10 advertising practitioners in history. Score, rewrite, score again. Don't stop until 90%. Use when: "/polish", "polish this", "polish", "rewrite this", "improve this copy", "make this better", "score my copy"

Writing format, image generation, and pipeline for X (Twitter) content. Paragraph-based medium form, Fischerian Hooks, anti-performance writing. Progressive disclosure: article format scoring, thread/article images, comic strip generation, full brainstorm→polish→schedule pipeline

OpenWriter — the writing surface for AI agents. A markdown-native rich text editor where agents write via MCP tools and users accept or reject changes in-browser. 40 core MCP tools for document editing, multi-doc workspaces, and organization, plus 21 publish platform tools for ne

Author's Voice — constructed-voice skill. Anchors writing to a training-data author blend, progressively layers NEVER rules, presentation fingerprints, sentence stats, coined terms, and curated examples from a growing local corpus. Pure markdown, opus sub-agent (the minion) write

Guides creation, audit, and improvement of portable Agent Skills using the shared

Use this skill when the user asks to "enable cache protection", "block on cache miss", "avoid cache expiration cost", "/ar:cache", "protect against compaction", "cache pressure guard", "cache hit ratio threshold", or "set cache-miss threshold". Covers the /ar:cache slash command

Use before writing any git commit message or reviewing one, and when the user asks for "commit requirements", "commit message guidelines", "/ar:commit", or "/ar:gc". Carries the 17-step pre-commit analysis, the concrete-subject rules that ban vague verbs and session-internal jarg

Design and review caller-facing names and contracts: functions, tools, commands, CLI flags, parameters, config keys, env vars, profiles, event types, and node/edge identifiers. Check names, descriptions, help, docstrings, schemas, defaults, bounds, units, errors, outputs, mutatio

Use when the user asks to "test the marketplace plugins", "run marketplace tests", "check every installed plugin", or "/ar:marketplace-test". Walks the installed marketplace plugins, finds each one's test suite, runs them from the plugin's own directory, and reports per-plugin re

Render Mermaid diagrams to SVG using beautiful-mermaid and bun. Use when the user asks to "render mermaid", "generate diagram", "create flowchart", "update diagrams", "render SVG from mermaid", "beautiful-mermaid", "regenerate diagrams", or needs to convert Mermaid diagram syntax

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.

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.