LLM Mart Basic
@llm-mart · Joined Jun 2026
Use when authoring a rig spec member or `rig expand` payload that needs to start a new managed seat from a prior runtime conversation source — `session_source: { mode: fork, ref: { kind, value } }`. v1 supports `mode: fork` with `ref.kind: native_id` for Claude and Codex. The new
Use when authoring rig specs, agent specs, workflow specs, startup/context fragments, operating-mode declarations, or designing the user spec library. Covers the 4 failure modes (spec instantiates topology but not workflow/mode; spec depends on local paths and fails on another ho
Use when changing a rig while it is alive — `rig expand` / `rig shrink` / `rig launch` / `rig remove` / `rig discover` / `rig bind` / `rig adopt` / `rig attach`. Covers the 4 failure modes (newly created seat lacks queue/startup/role; edges and permissions not updated; adopt/bind
Use when configuring `rig watchdog` policies, authoring wake/refocus/alignment-checkpoint messages, or choosing the right intervention level for a stale-owner situation. The 3-level continuity-check stack (wake / refocus / alignment-checkpoint), the discipline that prevents caden
Quickly capture product ideas, feature requests, or insights from meetings and conversations. Rapid documentation with smart categorization and deduplication.
Gather and distill context from meetings, competitors, regulatory sources, and internal discussions. Produces background.md for a feature and updates shared context docs when new knowledge is discovered.
Generate a 1-2 page executive summary for a feature — orients sales, leadership, and engineering from a single document.
YC-style product validation using six forcing questions. Pressure-tests a feature idea before it becomes a requirement — ensuring real demand, a clear wedge, and evidence behind assumptions.
Conversational intake that produces a structured requirements.md following a standardized PM schema. Enforces PM lane — no architecture, no estimates, no implementation details. Uses GIVEN/WHEN/THEN acceptance criteria.
Create UI mockups at three fidelity levels — ASCII wireframes for quick iteration, standalone HTML mockups for delivery with requirements, and live prototypes for interaction testing.
How the development pod coordinates implementation, QA, and design without skipping gates.
Operating manual for the orchestration pod. Covers lead vs peer roles, monitoring with rig commands, permission handling, implementation pair gating, dogfood loops, review routing, agent behavioral models, intervention discipline, and communication culture.
Use when you are a seat on the oversight pod (a standing monitor-mode rig that keeps OTHER rigs healthy), configuring or running the drift detectors, or choosing whether to intervene vs escalate. Covers the pull-not-poll posture, the v0 detectors (premature-park, process-drift, o
Complete operating manual for the review pod. Covers everyday review discipline, anti-slop analysis, empirical verification, context priming, the full deep review protocol (independent → cross-exam → convergence → roundtable), artifact management, and reviewer behavioral awarenes
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a websit
Use when designing, reviewing, or debugging how an agent's context window gets filled, pruned, or shared — choosing what loads at boot versus on demand, sizing an install or an always-loaded file, fixing an agent that drifts, repeats itself, or forgets constraints mid-task, plann
Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or w
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when implementing any feature or bugfix, before writing implementation code
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.
/config-validate
Config validate
Validate application configuration with schemas, per-environment rules, runtime checks, and secure handling of sensitive values
/spark-preflight
Spark preflight
Preflight a DGX Spark system for an ML training or inference workload and emit env-report.json
/debug-trace
Debug trace
Set up debugging and tracing with remote debugging, distributed tracing, debug logging, profiling, and production diagnostics
/doc-generate
Doc generate
Generate API, architecture, code, and user documentation from a codebase and automate keeping it current
/error-analysis
Error analysis
Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.
/error-trace
Error trace
Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.
/multi-agent-review
Multi agent review
Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review
/error-analysis
Error analysis
Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.
/error-trace
Error trace
Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.
/smart-debug
Smart debug
AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.
/code-migrate
Code migrate
Generate comprehensive migration plans and scripts for transitioning codebases between frameworks, languages, versions, or platforms with minimal disruption.
/deps-upgrade
Deps upgrade
Plan and execute safe, incremental dependency upgrades with minimal risk — including breaking-change migration paths and proper test verification.
/legacy-modernize
Legacy modernize
Orchestrate legacy system modernization using the strangler fig pattern with gradual component replacement
/component-scaffold
Component scaffold
Scaffold React and React Native components with TypeScript, tests, styles, and Storybook stories
/xss-scan
Xss scan
Scan React, Vue, Angular, and vanilla JavaScript code for XSS vulnerabilities and report fixes with secure coding examples
/full-stack-feature
Full stack feature
Orchestrate end-to-end full-stack feature development across backend, frontend, database, and infrastructure layers
/git-workflow
Git workflow
Orchestrate git workflow from code review through PR creation with quality gates
/onboard
Onboard
Create a role-specific onboarding plan for a new team member, from pre-arrival setup through the first 90 days
/pr-enhance
Pr enhance
Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report
/incident-response
Incident response
Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
14 views 0 likesScale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.
17 views 0 likesThe go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.
19 views 0 likesTransform and optimize your markdown documentation for Large Language Models (LLMs) and RAG systems. Generate llms.txt automatically.
29 views 0 likes合乎周礼:DeepSeek-powered Zhouli-style Chinese translator, web app, and distributable Skill package.
27 views 0 likesThis is a fork of the https://dockbox.dev project I made
25 views 0 likes🏆 Curated, ranked list of AI agent harnesses (100+) — plus an MCP server, llms.txt & JSON so agents can recommend them too. Rescored weekly.
28 views 0 likesA Python framework for modular, self-contained skill management for machines.
32 views 0 likesADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cogn…
34 views 0 likesAI Agent 驱动的开源可自部署视频工作台:将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿,支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video producti…
15 views 0 likesDeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.
13 views 0 likesAutonomous Offensive Security, Bug Bounty & Red Teaming Agent Framework powered by Hermes Agent, specialized reasoning skills, and multi-model LLM orchestration…
14 views 0 likes⌥ Coding agent with the IDE wired in
17 views 0 likesSupercharge AI Agents, Safely
33 views 0 likesX (Twitter) Scraper API and X API Alternative. You do not need an official X developer account. You do not need to connect or use an X account for supported scr…
16 views 0 likesMy AI Stand. Realtime by day, rewriting itself by night. Summon my AI superpower.
14 views 0 likesOpen-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.
15 views 0 likes观澜 / Guanlan:AI Agent 的中文互联网研究、阅读与信源路由工具。
13 views 0 likesMac Agent for macOS 26: the agentic AI harness for your Mac Desktop. Computer use, automation, scripting, coding, and more. Powered by 18+ providers across loca…
15 views 0 likesSemantic version control => entity-level diffs, blame, and impact analysis on top of git. 28 languages via tree-sitter. Built for coding agents.
28 views 0 likes