LLM Mart Basic
@llm-mart · Joined Jun 2026
How to create new skills for this HQ — format, frontmatter, content structure. Use when you need to add a new skill to this repository, or when reviewing whether an existing skill is well-formed.
System design patterns, Clean Architecture, SOLID principles, domain modeling. Use when making architectural decisions, designing new modules, refactoring a tangled codebase, or reviewing system design.
Debugging methodology, hypothesis testing, reading stack traces, isolating issues. Use when facing an unexpected bug, a flaky test, a production incident, or any situation where the cause isn't immediately obvious.
Tailwind CSS v4 patterns, component styling, dark mode, responsive design, and design system integration. Use when styling components or reviewing CSS.
TDD red-green-refactor cycle, test structure, mocking patterns for Vitest/Jest. Use when starting a new feature, fixing a bug, or refactoring — write the test first, then the implementation.
TypeScript type system patterns, generics, utility types, and strict mode best practices. Use when writing or reviewing TypeScript code.
Web design best practices, accessibility, responsive layout, color contrast. Use when auditing a UI for a11y compliance, designing responsive layouts, or establishing design standards across a web app.
Playwright E2E patterns, Testing Library component tests, test selectors. Use when writing browser tests, component tests, or setting up an E2E testing pipeline for a Next.js or React app.
Generating Excel files with xlsx/exceljs in Node.js. Use when generating .xlsx reports, data exports, dashboards, or spreadsheets from database data.
Reports on the health and state of architecture documentation (counts of ADRs, reviews, activity levels, documentation gaps). Use when the user asks "What's our architecture status?", "Show architecture documentation", "How many ADRs do we have?", "What decisions are documented?"
Creates a NEW Architectural Decision Record (ADR) documenting a specific architectural decision. Use when the user requests "Create ADR for [topic]", "Document decision about [topic]", "Write ADR for [choice]", or when documenting technology choices, patterns, or architectural ap
Displays the roster of architecture team members with their specialties and expertise areas. Use when the user asks "Who's on the architecture team?", "List architecture members", "Show me the architects", "What specialists are available?", "Who can I ask for reviews?", or wants
Enables and configures Pragmatic Guard Mode (YAGNI Enforcement) to prevent over-engineering. Use when the user requests "Enable pragmatic mode", "Turn on YAGNI enforcement", "Activate simplicity guard", "Challenge complexity", or similar phrases.
Statistical significance calculator for A/B test results with sample size requirements, segment breakdowns, and hypothesis generation. Use when feeding test results, checking statistical significance, calculating sample sizes, analyzing experiment outcomes, or generating next tes
Designs statistically valid split tests for ads, audiences, landing pages, or bid strategies. Calculates required sample sizes before you start, monitors results during the test, and calls winners when statistical significance is actually reached — not when you feel like one is w
Evaluates your campaign and ad set structure against your actual goals and budget. Flags over-segmentation that fragments your data, under-segmentation that hides performance differences, budget allocation issues, and consolidation opportunities that would improve algorithmic del
Analyzes your top performing ads, identifies what's working in the hooks, CTAs, messaging angles, and formats, then generates new variants that follow the same winning patterns while introducing enough variation to test meaningfully. Platform: Google and Meta.
Reviews all your Google Ads extensions — sitelinks, callouts, structured snippets, call extensions, image extensions, price extensions — across every campaign. Flags what's missing, what's underperforming, what's outdated, and writes replacements based on your best performing ads
Multi-channel budget optimization using MER, marginal ROAS, and diminishing returns analysis. Use when pasting multi-channel spend and results data, requesting reallocation recommendations, analyzing budget shift priorities, or optimizing marketing efficiency across Google, Meta,
Audit how visible your brand is inside AI answers (ChatGPT, Claude, Gemini, Perplexity, AI Overviews). Claude builds a prompt panel for your category, scores where you show up vs competitors, and turns the gaps into a prioritized fix list. Platform: AI visibility.
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.
/audit
Audit
Assemble the governance record for a range — commits, overrides, ADRs, sprint auto-decisions, open questions, checkpoint findings — into one dated audit packet. Read-only.
/btw
Btw
Lightweight Q&A about the project — answer from context and return, no routing, no state change.
/checkpoint
Checkpoint
Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.
/chore
Chore
Sanctioned lane for non-behavioral work — docs-only edits, dependency bumps, reverts. Type-scaled gates; no TDD demanded of prose.
/cleanup
Cleanup
Clean up an already-merged local branch after proving containment. Confirm each discard and preserve unique work.
/commands
Commands
Show the codeArbiter command catalog — the public command list and what each routes to.
/commit
Commit
Create a verified local Git commit when committing changes is requested. Not for explaining commit history, drafting a message only, or postponing a commit. Applies every commit gate and never implies a push or PR.
/conflict
Conflict
Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.
/context-check
Context check
Audit stale provenance-tracked docs on request. Report first; re-scout or re-baseline only for selected docs.
/create-context
Create context
Build project context from an existing codebase through isolated scouts, resolve gaps, and preserve initialization gates.
/debug
Debug
Investigate an unexplained defect or unexpected behavior without changing application code. Use for root-cause diagnosis and an evidence-backed handoff. A no-action close records a board note. Not for implementing a known fix, new features, or explanation-only questions.
/decompose
Decompose
Develop greenfield project context through a layered interview, preserve decisions, and initialize only after the required gates.
/doctor
Doctor
Verify the active host install, package, command ownership, enforcement, and harmless live-fire probe. Read-only.
/feature
Feature
Start a feature: brainstorm a spec, get it approved, then drive it test-first through the pipeline. The one entry to implementation.
/fix
Fix
Fix a confirmed bug: a failing regression test first, then a minimal fix, then the rest of the tdd gates.
/init
Init
Opt this repo into codeArbiter — scaffold the root-level .codearbiter/ state store.
/metrics
Metrics
Read-only 3-metric governance glance — override rate, small-lane rate, sprint low-confidence ratio — each with a trend arrow vs. the prior 20-commit window.
/override
Override
Sanctioned, logged bypass of a gate or hard rule — one audit line, then proceed.
/pr
Pr
Open a PR or finish branch disposition; route CI watching and post-merge cleanup to their owners. Merge and discard need explicit authority.
/preview
Preview
Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.
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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