LLM Mart Basic
@llm-mart · Joined Jun 2026
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision (middleware, simulation, data, visualization, training frameworks) plus a scaffold plan and a written architec
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision (middleware, simulation, data, visualization, training frameworks) plus a scaffold plan and a written architec
Entry-point skill for shaping new robotics applications: lightweight brainstorming, project ideation, requirement/risk discovery, stack selection, comparing or choosing simulators/models/visualization, a first user-visible slice, and a concise architecture decision record. Use wh
Entry-point skill for shaping new robotics applications: lightweight brainstorming, project ideation, requirement/risk discovery, stack selection, comparing or choosing simulators/models/visualization, a first user-visible slice, and a concise architecture decision record. Use wh
Deploy headless robotics / sim / demo containers to Google Cloud Run: the build → Artifact Registry → Cloud Run path plus the gotchas that bite sim workloads (no UDP multicast for gz-transport/DDS, CPU allocated only while a request is open, session affinity for per-visitor insta
Deploy headless robotics / sim / demo containers to Google Cloud Run: the build → Artifact Registry → Cloud Run path plus the gotchas that bite sim workloads (no UDP multicast for gz-transport/DDS, CPU allocated only while a request is open, session affinity for per-visitor insta
Deploy headless robotics / sim / demo containers to Google Cloud Run: the build → Artifact Registry → Cloud Run path plus the gotchas that bite sim workloads (no UDP multicast for gz-transport/DDS, CPU allocated only while a request is open, session affinity for per-visitor insta
Data sourcing strategy for robotics and physical-AI: choose between offline datasets (HuggingFace hub, Open X-Embodiment and similar), simulation-generated data, and teleop/real-robot collection; plan storage formats, episode structure, and dataset versioning. Use when: 'where do
Data sourcing strategy for robotics and physical-AI: choose between offline datasets (HuggingFace hub, Open X-Embodiment and similar), simulation-generated data, and teleop/real-robot collection; plan storage formats, episode structure, and dataset versioning. Use when: 'where do
Data sourcing strategy for robotics and physical-AI: choose between offline datasets (HuggingFace hub, Open X-Embodiment and similar), simulation-generated data, and teleop/real-robot collection; plan storage formats, episode structure, and dataset versioning. Use when: 'where do
Set up and start Infinite Pokémon when a user asks to install, play, or launch the game with their AI assistant. Clone missing game files, install dependencies, build, and launch the local desktop or browser game; not for background map or NPC generation jobs.
Design interior furniture layouts, rugs, room names and inspectable details for new Infinite Pokémon maps within the supplied protected room and service constraints.
Generate grounded NPC intentions, dialogue, memory and optional movement policies for Infinite Pokémon from a supplied saved-run observation or map-design context.
Generate Infinite Pokémon map stories, terrain features, content profiles, NPC policies, and interiors from a host-supplied saved-run snapshot and output schema.
This skill should be used when the user asks to "write a chapter", "next chapter", "chapter outline", "draft chapter", "continue the story", "write a scene", "outline a chapter", or wants to write prose for a story project.
This skill should be used when the user asks to "create a character", "update a character", "add a character", "build a family tree", "character relationships", "character timeline", "character arc", "character profile", or needs to manage characters in a story project.
This skill should be used when the user asks to "pantsing", "discovery write", "write without an outline", "discovery draft", "write into the dark", "story kernel", "reconcile a chapter", "reverse outline", "cut a subplot", "dead end", "drafting sprint", "writing cadence", or wan
This skill should be used when the user asks to "process beta reader feedback", "alpha reader feedback", "feedback round", "synthesize reader feedback", "reader notes", "beta feedback", "readiness check", or wants to collect, reconcile, and act on external reader feedback for a s
This skill should be used when the user asks to "mystery", "fair play", "clue", "red herring", "romance beats", "HEA", "thriller", "ticking clock", "horror", "dread", "MG", "YA", "middle grade", "young adult", "science fiction", "sci-fi", "serial", "episodic", "web serial", "genr
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.
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.
/prune
Prune
This is a Feature Forge preview command — the after-each-turn service ships **off** by default and
/reconcile
Reconcile
Arbitrates variances between the project's three architectural artifacts
/refactor
Refactor
This is the lane for moving or reshaping code without changing what it does — a rename, an extract,
/release
Release
This is the only sanctioned way a version tag gets created, and it holds no knowledge of any
/review
Review
A read-only review of the current change, dispatched by path against a reviewer-to-path matrix:
/spike
Spike
This is the outlet for "I need to write code to find out" rather than "I know what to build." The
/sprint
Sprint
This is codeArbiter's autonomy mode. It collapses the usual spec-plan-execute cycle into one
/standup
Standup
The daily hygiene checklist, made routine and gated: fetch and offer a fast-forward pull, list
/status
Status
A read-only snapshot of `.codearbiter/` state: the project's `stage:` maturity value, every
/statusline
Statusline
Wires codeArbiter's renderer into `~/.claude/settings.json`, or removes it. A plugin can't own a
/task
Task
The only blessed way to mutate `.codearbiter/open-tasks.md`. It runs a thin writer over pure
/threat-model
Threat model
An opt-in, lightweight STRIDE pass over a design before it's built — invoked deliberately, never
/tribunal
Tribunal
codeArbiter's deepest, most expensive review, convened rarely and never as a required gate. Eleven
/watch
Watch
Watches a pull request's CI checks to completion without polling by hand. The wait is a real
/debug
Debug
A fixture command named debug, colliding with the debug skill/agent.
/prune
Prune
A fixture command named prune, used to regression-test forge badges.
/another
Another
Another command, description only, no argument hint.
/sample
Sample
A sample command for fixtures — single sanctioned path to a thing.
/to-gif
To gif
Convert an animated HTML file (like /fig output) to a perfectly looping high-quality small GIF using Playwright + ffmpeg
/getpix
Getpix
Find a free licensed image on the internet and add it to the project, optimized
Paper trading simulator for Polymarket — built for AI agents. MCP server, live order books, strategy backtesting. Install: npx clawhub install polymarket-paper-…
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2 views 0 likesCollection of templates using the Alchemyst AI Platform for your next big AI app.
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