LLM Mart Basic
@llm-mart · Joined Jun 2026
Read a Hyperliquid account from the desk computer - positions and margin, spot balances, open orders including trigger details, fills, funding paid, ledger updates, order status by oid or cloid, historical orders, portfolio history, fee tier and rate-limit budget - with curl and
Less common Hyperliquid actions and their rules - dead-man's switch (scheduleCancel), TWAP orders, spot orders, expiresAfter and nonces, API wallet approval from code, sub-account and vault addressing, HIP-3 dexs, and what the desk deliberately does not do (transfers, withdrawals
Compact reference for the Hyperliquid API as the desk uses it - endpoints and envelopes, every /info request type, every /exchange action with its signing scheme, order and status vocabularies, asset ids, tick and lot rules, rate limits, WebSocket subscription list, error strings
Read live Hyperliquid market data from the desk computer with curl or the Python SDK - mid, mark and oracle prices, order book depth, funding (current, predicted, historical), open interest, volume, candles, perp and spot metadata, margin tiers, and how to save datasets for the s
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。
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.
/plan-es
Plan es
Iniciar planificación de archivos estilo Manus. Crear task_plan.md, findings.md, progress.md para tareas complejas.
/plan-goal
Plan goal
Bridge Claude Code's /goal to the active plan. Derives a goal condition from task_plan.md and invokes /goal so Claude keeps working until the plan is complete. Available since v2.38.0.
/plan-loop
Plan loop
Run a planning-aware cadence with Claude Code's /loop. Default tick checks plan status, runs check-complete, nudges progress.md update if stalled. Available since v2.38.0.
/plan-zh
Plan zh
启动 Manus 风格的文件规划。为复杂任务创建 task_plan.md、findings.md、progress.md。
/plan-zht
Plan zht
啟動 Manus 風格的檔案規劃。為複雜任務建立 task_plan.md、findings.md、progress.md。
/plan
Plan
Start Manus-style file-based planning. Creates task_plan.md, findings.md, progress.md for complex tasks.
/pwf
Pwf
Short alias for /plan. Starts Manus-style file-based planning: task_plan.md, findings.md, progress.md. Available since v3.0.0.
/start
Start
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Now with automatic session recovery after /clear
/status
Status
Show current planning status at a glance - phases, progress, and any logged errors.
/adversarial
Adversarial
Run three-agent adversarial analysis -- advocate builds the case, adversary challenges it, judicial analyst synthesizes
/briefing
Briefing
Structured pre-execution briefing session -- collects case context through specialist panel, builds execution plan, supports resume and depth control
/cantonal
Cantonal
Analyze cantonal law for all 26 Swiss cantons -- cantonal court decisions, cantonal legislation, procedural specifics, and interaction with federal law
/cite
Cite
Validate, format, and look up Swiss legal citations including BGE/ATF/DTF decisions and statutory references
/create-workflow
Create workflow
Create a reusable custom workflow by combining BetterCallClaude agents. Interview-based: pick agents, order them, define the output. Saved for future use with /bettercallclaude:workflow.
/doc-analyze
Doc analyze
Analyze Swiss legal documents -- identify legal issues, extract key clauses, verify citations, and assess compliance
/doctor
Doctor
Diagnose MCP server connectivity — tests each server, reports status and impact in plain language, suggests fixes for issues.
/draft
Draft
Draft Swiss legal documents including contracts (OR), court submissions (ZPO), and legal opinions (Gutachten) with multi-lingual support
/federal
Federal
Force Federal Law Mode for Swiss federal legal analysis, overriding cantonal auto-detection
/help
Help
Show complete BetterCallClaude command reference, available agents, skills, and usage examples
/legal-5step
Legal 5step
Execute the BetterCallClaude 5-step Swiss legal framework: intake → research → strategy → adversarial → draft. A complete end-to-end pipeline for any Swiss legal matter, from document analysis through final legal output.
Your car as a chat-room agent: Raspberry Pi 5 + dashcam + local AI. CodeWatch's sibling for the garage.
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