LLM Mart Basic
@llm-mart · Joined Jun 2026
Place, cancel and modify Hyperliquid orders correctly from the desk computer - limit and IOC (market-style) orders, take-profit and stop-loss trigger orders with grouping, client order ids, reduce-only, batch actions, price and size rounding, and how to read every response status
Prepare the desk computer to work with Hyperliquid - install the SDKs, pick testnet or mainnet, verify connectivity, and (only when the user asks) provision a trade-only API wallet through the secure secret store and verify it is approved. Use during desk setup, when moving betwe
Subscribe to live Hyperliquid data over WebSocket from the desk computer - mids, order book, trades, candles, best bid/offer, and per-account fills, order updates and events - with raw JSON, Python SDK and TypeScript examples, plus how to run a supervised watch that logs to a fil
用证据链和 X/Y/Z 立体分析法研究产品、公司、技术、概念、人物、行业、市场或复杂事件,交付可追溯的深度研究报告。用户要求 deep research、系统调研、竞品或市场研究、尽职调查、来龙去脉分析、证据链或正式研究报告时使用。简单名词解释、新闻摘要、短篇观点、仿写,以及 3D 建模、渲染、CAD 或图形设计不使用。
起草或润色可直接发送的职场即时消息和邮件。用户明确要求“怎么说、怎么发、润色、改写、写消息、写邮件”,或提供职场素材并表明要发给某人时使用;仅展示背景、讨论沟通策略、撰写 PRD、报告或长篇文档时不使用。
Curated Agent Skills collection for AI-assisted development. Open standard — agentskills.io. Portable across Claude Code, Cursor, Copilot, Codex, Gemini CLI, an…
发布后独立质量循环——单盲四角色流水线(A 审 12 视角 → B 修 → C 验 → D 复核),每轮新 session 保证零上下文,连续 2 轮无 P0/P1 即停。
发版前自动验证闸门——V 验证 + F 修复循环(verdict FAIL → F 改代码 → 跑 audit → V 重验),最大 3 轮直到 PASS。纯只读验证 + 最小修复。
一次挂载 sofagent 全套能力——6 项能力一次到位(注入 · 审计与验收 · 经验 · 回溯 · 巡检 · FDE 三域)(seam: non-seam:plugin-suite)——只编排不重实现——sofagent 约束层在 DSH(DeepSeek Harness)生态的插件形态。
变更机器审阅 + 验收硬门禁——24 规则 + git diff 硬证据 + Turn 停止验收判定(验收不过不放行,开关独立可关)(seam: tools/result + tools/pre-execute + fs/write-intent + agent/turn-stopping)——桥接 @sofagent/audit runRules——DSH(DeepSeek Harness)cordis plugin。sofagent 约束层在 DeepSeek Harness 生态的插件形态。
7×24 巡检 + 健康监测 + webhook 推送(seam: non-seam:host-process)——桥接 @sofagent/daemon startCron——DSH(DeepSeek Harness)cordis plugin。sofagent 约束层在 DeepSeek Harness 生态的插件形态。
经验沉淀——think.md 反思 + Dream Cycle + evolve + instinct→skill + refine(seam: turn/end)——桥接 @sofagent/think generateThinkEntry——DSH(DeepSeek Harness)cordis plugin。sofagent 约束层在 DeepSeek Harness 生态的插件形态。
FDE 进场与能力流通——把企业业务梳理成 AI 能力,并让这些能力在企业内被发布、发现、调用、评价、退役(seam: non-seam:tool-set)——桥接 @sofagent/orchestrator publishCapability / @sofagent/ontology generateOntologyView / @sofagent/core restoreSnapshot——DSH(DeepSeek Harness)cordis plugin。sofagent 约束层在 DeepSeek Harness 生态的插件形态。
启动注入企业约束——四层加载链(seam: agent/pre-step)——桥接 @sofagent/harness buildConstrainedSystemPrompt——DSH(DeepSeek Harness)cordis plugin。sofagent 约束层在 DeepSeek Harness 生态的插件形态。
出错逆序撤销——git snapshot → effect disposer(seam: agent/error)——桥接 @sofagent/core getHistoryFilePath——DSH(DeepSeek Harness)cordis plugin。sofagent 约束层在 DeepSeek Harness 生态的插件形态。
当 FDE 需要对工作流节点做 AI 分类判定时用这个 Skill—— 不是"它是干什么的",是"什么时候用"。 写错 description = Skill 永远不会被触发。
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.
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
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.
/do
Do
Smart router: classify requests and route to the correct agent + skill
/generate-claudemd
Generate claudemd
Generate project-specific CLAUDE.md from repo analysis.
/github-notifications
Github notifications
Triage GitHub notifications: fetch, classify, report actions needed.
/github-profile-rules
Github profile rules
`github-profile-rules` — extract programming rules and coding conventions from a GitHub user's public profile via API.
/gm-brilliant-implementation
Gm brilliant implementation
Run the complete 34-stage implementation workflow for a large, multi-system, multi-wave, or CPU-delegated 5 Star Booker GM program.
/install
Install
Plan, then apply, the VexJoy Agent install with the vexinstall engine
/pr-review
Pr review
Comprehensive PR review using specialized agents, with automatic retro knowledge capture
/reddit-moderate
Reddit moderate
Reddit moderation: fetch modqueue, classify content, take mod actions
/retro
Retro
Learning system interface: stats, search, graduate learnings. Backed by learning.db (SQLite + FTS5).
/system-upgrade
system-upgrade
Systematic upgrade pipeline for adapting agents, skills, and hooks when Claude Code ships updates, user goals change, or retro learnings accumulate.
/full-equity-research
Full equity research
agentii.full-equity-research — the spec 046 kit command. Use the Skill tool to run agentii:full-equity-research on this workspace.
/synthesize
Synthesize
agentii.synthesize — the spec 046 kit command. Use the Skill tool to run agentii:synthesize on this workspace.
/agent-diversity-review
Agent diversity review
Run the Agent Diversity Review gate and emit the result table
/create-specialist-agent
Create specialist agent
Scaffold a new spawnable specialist agent def and register it in the agent taxonomy
/customer-changelog-check
Customer changelog check
Audit whether user-visible changes in the current session have matching CHANGELOG.md entries; report MISSING with suggested lines; --fix auto-appends
/dashboard-cockpit
Dashboard cockpit
Repeatable pass upgrading an Angular admin dashboard into a compact black-and-cyan developer-cockpit PWA
/drift-check
Drift check
Run the drift-detection checklist (incl. agent-drift signals); report + fix in-turn
/final-review
Final review
Orchestrate the final review fan-out (integration + diversity + risk + release readiness)
/improve-lint
improve-lint
Run the AI-augmented lint self-improvement loop on the current project. Scans `.lint-history/` for recurring violation patterns (≥3 hits in 30d window), drafts a Claude-ready prompt to author a new semgrep rule for the top candidate, and surfaces the proposal under `.lint-history/proposals/<ts>.md`. Non-blocking analysis. See rules/lint-doctrine.md § Self-improving.
/install-lint-stack
install-lint-stack
Bootstrap industry-leading lint+autofix+commit-hygiene stack on the current project. Drops in lefthook, oxlint, ESLint, Prettier, Stylelint, markdownlint, ruff, shellcheck, shfmt, yamllint, hadolint, actionlint, jscpd, knip, semgrep, gitleaks, commitizen + git-cz-emoji (emoji-mandatory commits), and semantic-release. Idempotent — re-runs upgrade safely. See rules/lint-doctrine.md.
🤖 MateClaw — Your second brain with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, Dream, and Multi-Channel Support. Built on Spring AI Alibaba.
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