LLM Mart Basic
@llm-mart · Joined Jun 2026
Analyze task complexity and route to a mode by artifact: direct fix for clear-scope changes, or a plan file when the approach needs to be written down. Use when the user asks to "turboplan", "run turboplan", "plan this task", "turbo plan mode", "plan and implement", or "use turbo
Teach the user to deeply understand a change through interactive tutoring: restating understanding, drilling into why/what/how, and quizzing until mastery. The active counterpart to a one-shot explanation. Use when the user asks to "understand this change", "teach me this change"
Update the Unreleased section of CHANGELOG.md based on current changes. No-op if CHANGELOG.md does not exist. Use when the user asks to "update changelog", "add to changelog", "update the changelog", "changelog entry", "add changelog entry", or "log this change".
Upgrade project dependencies with breaking change research for major version updates. Use when the user asks to "update dependencies", "upgrade packages", "upgrade dependencies", "update deps", "upgrade deps", "update npm deps", "update Swift packages", "cargo update", "go get up
Update an existing GitHub pull request's title and description to reflect the current state of the branch. Use when the user asks to "update the PR", "update PR description", "update PR title", "refresh PR description", or "sync PR with changes".
Update installed Turbo skills from the local repo with a dynamic changelog, conflict resolution for customized skills, and guided user experience. Use when the user asks to "update turbo", "update turbo skills", "reinstall turbo", or "upgrade turbo".
Apply a UX lens to a user-facing change: whether it serves the user's real goal and whether the path through it holds together, using the Understanding, Bridging, and Flowing contexts. Use when scoping, planning, or assessing any change that affects what a user sees or does. Load
For each reviewer question on a PR, recall implementation reasoning and compose a raw answer. Use when the user asks to "answer reviewer questions", "draft answers to PR questions", or "explain reviewer questions".
Apply findings by making the suggested code changes. Applies accepted verdicts, escalates ambiguous findings to the user, and offers to note genuine improvements for later. Use when the user asks to "apply findings", "apply fixes", "apply suggestions", "apply accepted findings",
Assess project-wide structural technical debt: complexity hotspots, deprecated API usage, duplication clusters, and architecture rot. Ranks findings by impact and refactor effort into a report at .turbo/technical-debt.md. Use when the user asks to "assess technical debt", "find t
Project-wide health audit pipeline that fans out to all analysis skills in parallel, evaluates findings, and produces a unified report at .turbo/audit.md. Use when the user asks to "audit the project", "run a full audit", "project health check", "audit my code", "codebase audit",
Shared changelog conventions and formatting rules referenced by $create-changelog and $update-changelog. Not typically invoked directly.
Run a non-interactive Claude Code print-mode call from Codex. Use when the user asks to "claude print", "ask claude", "run claude", "consult claude", or when a Codex Turbo skill needs Claude as an independent peer reviewer.
Enforce existence, reuse, mirror, and symmetry principles to keep new code minimal and consistent with surrounding code. Use when writing new code in an existing codebase, adding new features, refactoring, or making any code changes.
Shared commit message rules and technical constraints referenced by $stage-commit and $commit-staged. Not typically invoked directly.
Commit already-staged changes with a message matching existing commit style. Use when the user asks to "commit staged changes" or "commit what's staged".
Commit already-staged changes and push in one step. Use when the user asks to "commit and push staged changes", "commit and push what's staged", or "commit staged and push".
Consult Claude Code for second opinions, brainstorming, or difficult debugging from Codex. Use when the user asks to "consult claude", "ask claude", "get claude's opinion", "brainstorm with claude", or "discuss with claude".
Consult ChatGPT Pro via ChatGPT browser automation for problems that resist standard approaches. Use when stuck on a very hard problem, when standard approaches have failed, when multiple debugging attempts haven't worked, or when the user says "ask the oracle", "consult oracle",
Propose a turbo skill improvement upstream by filing a GitHub issue against the turbo repo. Use when the user asks to "contribute to turbo", "submit turbo changes", "contribute back", "suggest a turbo improvement", or "upstream my changes".
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.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
/weekly
Weekly
The weekly review
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
Close a finished session: sweep for unfinished work, land and hand off, file the follow-ups, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/ia-refine-prompt
ia-refine-prompt
Transform a vague prompt into precise, structured AI instructions
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/build-unity
Build unity
Build the Unity project in batchmode for WebGL, desktop, Android or PSG1
/cleanup
Cleanup
Turn a solana-ai-kit fork into a project: set up CLAUDE.md, remove kit files
/commit-claude-config
Commit claude config
Un-ignore and commit the kit config dir, instruction file, .mcp.json and .gitmodules
/debug-user-tx
Debug user tx
Replay a user's failing transaction on forked state and map the error to source
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…
29 views 0 likesGovernance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…
17 views 0 likesUltimate Multi-Agent OS for Autonomous AI NPCs 2026
14 views 0 likesPersonal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant
26 views 0 likesProven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control
29 views 0 likesSlash API Batch: Cut AI Costs by 50% in 2026
15 views 0 likesWeb dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics
19 views 0 likesAgent Skills for Solopreneurs
31 views 0 likesAirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card
121 views 0 likesZero, your trustworthy AI teammate for real work.
16 views 0 likes一套 DSH runtime,Desktop、Web 与 TUI 三种开发体验。
11 views 0 likesOpen-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.
16 views 0 likes⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.
28 views 0 likesFramework for AI agents to build and maintain a digital brain through Obsidian wiki
16 views 0 likesApache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…
25 views 0 likesNeo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…
25 views 0 likesAgentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…
19 views 0 likesNocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…
27 views 0 likesAn open-source AI coding agent that lives in your terminal.
29 views 0 likesPawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…
14 views 0 likes