LLM Mart Basic

Use when the user is explicitly working with Quarto, .qmd files, _quarto.yml, Quarto projects, or Quarto features such as callouts, cross-references, citations, Mermaid diagrams, extensions, websites, books, presentations, and reports. Also use for explicit migration from or comp

Deploy or publish Python and R content to a Posit Connect server using rsconnect-python or the R rsconnect package. Handles interactive apps and dashboards, web APIs, rendered documents, and prepared bundles/manifests. Use whenever the user asks to deploy, publish, or redeploy co

Guide for drafting issue closure and decline responses as an open-source package maintainer. Use when helping compose a reply that says "no" to a feature request, closes an issue as won't-fix, redirects a user to a different package, explains why a design choice is intentional, o

Use when the user wants to find, evaluate, audit, or install an open-source AI agent skill or MCP server — e.g. "find an MCP server for Postgres", "is this skill safe to install", "what should I use to scrape a website". Searches a quality-scored, security-graded catalog of ~20K

Generator-evaluator separation and review methodology — loaded by review agents to enforce fresh-context review discipline and gate verdicts; findings from the code, security, and docs reviewers are formatted per the conventional-comments skill. Trigger on "review this diff", "re

Adversarially review a technical design document with fresh context. Dispatches the built-in read-only `Explore` subagent (clean context, no shared history with the design-author) against `docs/plans/<id>/design.md` and presents its verdict — APPROVE, REQUEST CHANGES, or COMMENT.

Tear down local and remote branch state after a pull request is finished, in one of two modes. Mode A (merged): verify the PR actually merged, remove the branch's worktree, resync the default branch, and delete the local branch. Mode B (closed / abandoned): close the PR(s), then

Bring a feature branch up to date with its base without changing what the branch does: capture a pre-rebase check baseline, fetch, rebase onto the latest base, resolve each conflict from both sides' intent with the rationale recorded to disk, re-run the same checks, and treat any

Watch your own pull request for review feedback: undraft it when the cue clearly says it is ready (an ambiguous cue watches the draft), take a baseline snapshot, then poll GitHub in ~31-minute cycles for up to 24 hours and triage new feedback as it arrives — inline review threads

Watch a pull request you are reviewing until your feedback is settled, re-review each settlement, then approve once: poll GitHub in ~31-minute cycles for up to 24 hours until every review thread you opened is resolved and every plain PR comment you posted has a later push behind

Land a reviewed pull request: discover the open PR for the current branch, push any unpushed commits, wait for CI to go green, then squash-merge it so the PR title (which may carry a version) lands as the commit subject. Handles a PR that has fallen behind its base (rebase + forc

Decide the approach before any code is written. The design-author drafts the ~200-line design document, resolving its own open questions autonomously as recorded assumptions, then an adversarial design review gates advancement. Trigger on "design this", "let's align on the approa

Compressed bug-fix pipeline — reproduce, write failing test, minimal fix, verify, and open a draft PR. Skips Question/Research/Design/Structure/Plan phases. Invoke ONLY on explicit pipeline intent — the user says "run the bug-fix pipeline", "team-fix this bug", or runs "/team-fix

Execute the implementation phase. Includes test-first sub-step (writing failing tests, mechanical confirmation gate) and adversarial verification (5 parallel reviewers with hard-gate retry loop). Trigger on "implement this", "execute the plan", or "/team-implement".

Produce the tactical implementation plan from the structure. The plan is an autonomous artifact for the implementer — no approval gate at this phase (the design was already gated by the adversarial design review). Trigger on "plan the implementation", "spell out the steps", or "/

Open the pull request after verification passes. Updates the changelog, optionally surfaces the tracking ticket, and closes out the topic. Trigger on "open the PR", "open a draft PR", or "/team-pr". To land/merge a reviewed PR (wait for CI, then squash-merge) use the separate /sh

Decompose a feature description, ticket, or issue link into the QRSPI Question artifacts (task.md, questions.md). Trigger on "shape this idea", "decompose this task", or "/team-question".

Research a codebase area before making changes. Dispatches parallel read-only agents (file-finder + researcher) that read questions.md only — never task.md. Trigger on "research this", "explore the codebase for", or "/team-research".

Break the reviewed design into vertical slices with verification checkpoints. Runs autonomously and advances to PLAN — no approval gate. Trigger on "slice this up", "break the design into steps", or "/team-structure".

Prepare one or more isolated git worktrees — one per repository the topic touches. Router action — no agent. Trigger on "set up the worktree", "isolate this work", or "/team-worktree".

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.

`crabbox inspect` prints the full record for a single lease: state, provider,

Run named, repo-local jobs defined in your Crabbox config.

`crabbox list` shows the current Crabbox machines (leases) for a provider. It is

`crabbox login` authenticates the CLI against a coordinator, stores the

`crabbox logout` clears the stored broker token from your user config so the CLI

`crabbox logs` prints the retained command output for a recorded run.

`crabbox marketplace` previews the Crabbox credits gateway: one Crabbox billing

`crabbox media` turns a recorded desktop video into lightweight review

`crabbox open` prepares an existing SSH-capable lease for an external editor.

`crabbox pause` pauses a single lease, freeing the remote compute while

`crabbox pond` is the cross-provider peer-discovery and lifecycle surface for a

`crabbox pool` contains machine-pool helpers. `pool list` keeps the older

`crabbox ports` bridges provider-native port publishing for an existing Crabbox

`crabbox prewarm` leases a reusable box and prepares it for test runs. For

`crabbox providers` prints the provider capability matrix that the CLI compiles

`crabbox receipt <run-id>` retrieves a brokered run's committed terminal

`crabbox results` prints the structured test summary attached to a recorded

`crabbox resume` resumes a lease previously paused with [`pause`](pause.md),

`crabbox run` syncs the current dirty checkout to a box, runs a command there,

`crabbox screenshot` captures a single PNG from a desktop lease without opening a

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.