LLM Mart Basic
@llm-mart · Joined Jun 2026
Flip the session into coordinator mode — the parent agent plans, scopes, reviews, and ships, but delegates all real work (exploration, implementation, review, fixes) to sub-agents routed by an empirically benchmarked model capability table. Use when the user invokes /orchestrate
Drive one tracked ticket from arrival to resolution through four verbs: triage, start, revise, finalize. Use when the user says triage/start/revise/finalize with a ticket id, asks to turn a ticket into a locked brief, to execute a work order, to action a review round on a ticket'
Lifecycle for user-facing surfaces — revise a shipped surface in the running app, lock a greenfield visual spec, build to a lock, critique/audit/polish a UI, or re-settle a locked term. Use for any request to design, review, or verify rendered UI (screens, dashboards, flows, comp
Register maintained or ephemeral Git checkouts with codebase-memory-mcp, keep long-lived indexes current through non-clobbering Git hooks, and tear down ephemeral indexes by exact deterministic identity. Use when asked to index, onboard, register, remove, or keep a repository cur
Vocabulary and principles for well-designed CI. Use when the user wants to design, review, or audit CI, says CI is noisy, slow, or expensive, or is designing a workflow yml.
Review the changes since a fixed point (commit, branch, tag, PR, or merge-base) on two axes — Standards (does it follow this repo's documented rules?) and Spec (does it do what the originating issue asked?). Each axis returns a verdict per enumerated item rather than an open-ende
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
Use the codebase knowledge graph for structural code queries, trace call paths and dependencies, inspect architecture, assess change impact, or activate the bundled Claude Code discovery hooks.
Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.
Launch or connect to a local development web server and drive it with a reusable headless-Chromium command interface. Use when asked to render, smoke-test, interact with, verify, or screenshot a local frontend or HTML mockup.
Produce a decision-safe handoff for a fresh agent. Use when a task changes hands, a session is ending midstream, a user asks for a handoff, or an agent needs to preserve a design/map/implementation decision without making the next agent rediscover it.
Convene a small panel of persistent reviewer personas (curated colleague-likenesses plus invent-on-demand) to review a document cold, in character, then synthesize a panel verdict. Use when the user wants a document reviewed by a panel, wants named perspectives on a plan or desig
Adversarially review a plan, work order, spec, or agent brief before anything gets built. Use when the user wants a plan reviewed, stress-tested, audited, or countersigned, says "plan review" or "poke holes in this plan", or wants a pre-build check on an issue/brief/PRD.
Write a pull-request body and score it before the PR is opened, or audit an existing PR's body against the same rubric. Use when about to run gh pr create, when a PR body needs writing or rewriting, or when asked whether a PR description is any good. Invoked as /pr-body write <bo
Use when a plan, spec, work order, or process doc is drafted and about to enter review or execution — grounds its facts, spikes its first hour, and single-sources its rules so review rounds start deep instead of shallow.
Build a throwaway prototype to flesh out a design — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
Shape every response for a reader who wants the answer first and nothing after it. Answer-first structure, numbered steps, domain language governed by a per-repo glossary of approved terms, one instruction per sentence, no preamble or recap. Invoke with /say-less for full shaping
Create an isolated Git worktree for issue, pull-request, branch, or parallel agent work without editing the control checkout. Use when starting task work from fresh remote state, avoiding a dirty or shared checkout, or preparing a dedicated worktree for another agent.
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
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.
/update
Update
CoalWash self-update — check for a newer version and offer to apply it, or set how updates are handled.
/create-skill
Create skill
Create an AI skill from any source (URL, repo, PDF, video, notebook, etc.)
/install-skill
Install skill
One-command skill creation and packaging for a target platform
/sync-config
Sync config
Sync a scraping config's URLs against the live documentation site
/mc-validate
Mc validate
Generate and run validation queries for the current change
/mc-validate
Mc validate
Generate and run validation queries for the current change
/setup-code-intelligence
setup-code-intelligence
Check code-intelligence prerequisites (ripgrep + a language server) and print install hints
/ci-mockup-figure
Ci mockup figure
Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion
/editable-figure
Editable figure
Design concise overview, mechanism, or workflow figures as editable PowerPoint objects
/implement-review
Implement review
Run the implement-review staged-change review loop
/my-router
My router
Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill
/prun
Prun
Run prun: parallel delegation fan-out on Agy workers (the session coordinates)
/readme-polish
Readme polish
Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim
/vet
Vet
Vet the staged change: run the implement-review review loop (short alias)
/ci-mockup-figure
Ci mockup figure
Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion
/editable-figure
Editable figure
Design concise overview, mechanism, or workflow figures as editable PowerPoint objects
/implement-review
Implement review
Run the implement-review staged-change review loop
/my-router
My router
Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill
/prun
Prun
Run prun: parallel delegation fan-out on Agy workers (the session coordinates)
/readme-polish
Readme polish
Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim
VCP 部署在 AI 模型 API 与前端应用之间,是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架,将原本“无状态、无记忆、无工具调用能力”的大语言模型,彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。
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