LLM Mart Basic

The end-to-end procedure for one trade on the HyperGrok desk - from an idea to a reviewed, journaled result - with the ticket format, who owns each stage, and what "done" looks like. Use whenever the user wants to open, adjust or close a position, or whenever any Bot is about to

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。

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.

Turn a GAIA workflow misfire into a redacted, classified, filing-ready bug report in one read-only pass. Self-diagnoses config issues inline; files probable bugs upstream on confirmation.

Judge-the-form, human-gated hardening. Reviews recurring code-audit-frontend findings and, with approval, drafts the lowest-context-weight form (deterministic check / skill / path-scoped prose rule) into the working tree. Pass `list` to see live candidates or `why <finding_class>` to explain one.

Initialize a new project from the GAIA React template, renames, strips GAIA branding, configures i18n, installs Claude skills/plugins.

Plan a complex feature using GAIA's task-orchestration pattern, structures the work into fresh-context subagent phases for your approval. Does not implement.

Cut a new GAIA release, bump version, graduate CHANGELOG, regenerate manifest, open release PR, then tag on merge. Maintainer-only.

Detect and, on explicit consent, additively append the languages Serena is not indexing to the `languages:` list in `.serena/project.yml`, then prompt a Serena restart. Never mutates without a yes; inert without Serena.

Author an immutable SPEC artifact through Socratic discovery (spec-kit wrapper), then STOP. Terminal, never runs /gaia-plan; it prints a /gaia-plan prompt the human pastes into a fresh session. Pass `auto <description>` for non-interactive mode that answers its own questions.

Maintainer-only autonomous health audit + auto-heal loop. Runs N=3 fresh-team audit-fix-audit cycles with circuit breakers, reports an F-to-A+ verdict (folding in the shared Claude-integration fitness grade) or escalates.

Single post-init onboarding command; detects situation, runs only owed phases; safe to re-run. --reconfigure rotates token and re-selects tools.

GAIA before_specify hook: constitution placeholder check + spec-kit version-pin drift detection.

GAIA after_specify hook: immutability lint over the just-written SPEC artifact.

Close a plan after implementation+merge. Offers wiki-promote for the plan's consolidated SUMMARY.md, cold-consolidates an out-of-band merge, then early-reaps the local plan folder once cost is represented in cost.jsonl.

GAIA self-review: pre-gate-2 review pass on the in-progress SPEC draft.

Close a SPEC after implementation+merge. Optional drain of deferred wiki-promote, cold-consolidates an out-of-band merge into SUMMARY.md, then early-reaps the local SPEC folder once cost is represented in cost.jsonl.

GAIA Socratic discovery wrapper: /speckit-specify for the initial draft, then GAIA's own Socratic clarify loop.

GAIA before_implement hook: render PO-authored UATs into Playwright e2e specs at .playwright/e2e/spec-NNN/.

Promote merged SPEC or plan content into the GAIA wiki.

This project uses the GAIA preset. Bare `/speckit-clarify` is not the clarify path here: core clarify writes an off-shape artifact (a `## Clarifications` / `### Session` block with five-word answers) and carries a question cap GAIA does not use. Run `/gaia-spec` instead — it driv

GAIA-wrapped /speckit-specify: writes through core, then relocates the artifact to .gaia/local/specs/SPEC-NNN/SPEC.md and stamps GAIA frontmatter.

Show or configure the compact Fallow Impact statusline in Claude Code

An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作

Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.

The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.

Transform and optimize your markdown documentation for Large Language Models (LLMs) and RAG systems. Generate llms.txt automatically.

合乎周礼：DeepSeek-powered Zhouli-style Chinese translator, web app, and distributable Skill package.

This is a fork of the https://dockbox.dev project I made

🏆 Curated, ranked list of AI agent harnesses (100+) — plus an MCP server, llms.txt & JSON so agents can recommend them too. Rescored weekly.

A Python framework for modular, self-contained skill management for machines.

ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cogn…

AI Agent 驱动的开源可自部署视频工作台：将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿，支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video producti…

DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.

Autonomous Offensive Security, Bug Bounty & Red Teaming Agent Framework powered by Hermes Agent, specialized reasoning skills, and multi-model LLM orchestration…

⌥ Coding agent with the IDE wired in

Supercharge AI Agents, Safely

X (Twitter) Scraper API and X API Alternative. You do not need an official X developer account. You do not need to connect or use an X account for supported scr…

My AI Stand. Realtime by day, rewriting itself by night. Summon my AI superpower.

Open-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.

观澜 / Guanlan：AI Agent 的中文互联网研究、阅读与信源路由工具。

Mac Agent for macOS 26: the agentic AI harness for your Mac Desktop. Computer use, automation, scripting, coding, and more. Powered by 18+ providers across loca…

Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 28 languages via tree-sitter. Built for coding agents.