LLM Mart Basic

Use when the user requests diagrams, flowcharts, architecture diagrams, ER diagrams, UML / sequence / class diagrams, SysML / MBSE diagrams (block definition, internal block, requirement, parametric), BPMN business process diagrams, swimlane / cross-functional flowcharts, network

Read the clawock request file, write decision.json, let clawock validate. Use when a clawock run request is present in .clawock/work/.

kcn 每个工作日 08:00 HKT 跑一次的盘前全 swarm 深度分析。harness 化：`clawock brief preflight` 计算并编译 typed decision packet，LLM 只做 Tier 1/2/3/Judge 与受限 judgment overlay，`clawock brief postflight` 验证、生成 Pages projection、commit 并自动投递微信。**输出**：完整 markdown、结构化 plan、受限 judgment JSON 与紧凑微信卡。**只在每日 8 点 cron

Manual, event-driven earnings review for a US or HK holding, backed by first-party filings. Use when a company reports, when a management promise comes due, or when a thesis review needs primary-source numbers. Produces a structured artifact under memory/earnings/<TICKER>/<period

Pre-investment screening gate for a name that is not yet researched or held. Use before spending a deep-research run or opening new exposure, to answer only "is this understandable and researchable enough to proceed?". Grades information richness separately from investment qualit

Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.

Workspace-aware Hong Kong stock analysis for kcn. Routes through clawock analyze-hk (Tencent primary + Eastmoney full-batch independent cross-check/fallback → stooq → yfinance) for price/技术指标/news, layered with HK-specific concepts — 南向资金, HSTECH 方向, 杠杆 ETF 衰减, 老千股警惕, T+0 无涨跌幅. U

OpenClaw **system-level** maintenance — cleans sessions/.bak rotation, disk bloat under ~/.openclaw/, validates model fallback chain, audits cron health, prunes short-term-recall noise. Run after `openclaw update` or every 1-2 weeks. Different from **workspace document tune-up**

Safe OpenClaw version upgrade with regression checklist. Use when kcn says "升级 openclaw" / "openclaw 有没有更新" / "/openclaw-upgrade", or after noticing a newer npm version. Checks for in-flight crons, uses the built-in updater, reapplies all host-local dist patches, and runs the ful

Single-pass holdings analysis for kcn using workspace files and the local fetch chain. Use for portfolio review, position risk ranking, US-HK cross-market read, leverage ETF risk assessment, and one-shot actionable reports based on portfolio.json plus fresh quotes from `clawock a

Multi-agent swarm review of kcn's current holdings. Inspired by TauricResearch/TradingAgents framework already in workspace — three-tier analysis (analysts → bull/bear debate → risk debate + judge) with confidence scoring. Use for post-close reviews, holiday/next-session planning

Imported from kcnyu/clawock/skills/scrapling.

Turn an investment agent into a supply-chain bottleneck hunter. Use this skill for source-backed investment research, live market/theme scans, AI/semi/technology value-chain mapping, A-share/HK/US stock screening, thesis stress tests, and Serenity-inspired research conversations.

AI-optimized web search via Tavily API. Returns concise, relevant results for AI agents.

Trading analysis and education. Technical analysis, chart patterns, risk management, and position sizing for stocks, forex, and crypto.

Workspace-aware US stock analysis for kcn. Routes through `clawock analyze-us` / `clawock us-quotes` instead of generic web search, then layers fundamental/technical/news analysis on top. Use when user asks to analyze a US ticker (e.g. "analyze AAPL", "look at RKLB", "compare TSL

Produce an evidence-linked investment decision with an explicit bull case, opposing bear case, thesis invalidation conditions, bounded action, and reconciled order/FX amounts. Use when an agent must analyze a security or portfolio action and publish a verifiable decision artifact

Run a clawock investment decision — read the prepared request, research with the host's own tools, write decision.json with evidence and an explicit bull/bear debate, and let Python validate and settle. Use when the user asks for an investment decision or a clawock run request is

Implement a piece of work based on a PRD or set of issues.

Adopt OpenSpec in a repo that lacks it: scaffold the openspec/ layout, write baseline specs describing the system as it exists today (from code, docs, and git history), and deliver the whole thing as a documentation-only PR. One-time per repo. Trigger when the user asks to adopt

A green PR, a controller reporting success, and not one line of the new code running

Validate application configuration with schemas, per-environment rules, runtime checks, and secure handling of sensitive values

Preflight a DGX Spark system for an ML training or inference workload and emit env-report.json

Set up debugging and tracing with remote debugging, distributed tracing, debug logging, profiling, and production diagnostics

Generate API, architecture, code, and user documentation from a codebase and automate keeping it current

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Generate comprehensive migration plans and scripts for transitioning codebases between frameworks, languages, versions, or platforms with minimal disruption.

Plan and execute safe, incremental dependency upgrades with minimal risk — including breaking-change migration paths and proper test verification.

Orchestrate legacy system modernization using the strangler fig pattern with gradual component replacement

Scaffold React and React Native components with TypeScript, tests, styles, and Storybook stories

Scan React, Vue, Angular, and vanilla JavaScript code for XSS vulnerabilities and report fixes with secure coding examples

Orchestrate end-to-end full-stack feature development across backend, frontend, database, and infrastructure layers

Orchestrate git workflow from code review through PR creation with quality gates

Create a role-specific onboarding plan for a new team member, from pre-arrival setup through the first 90 days

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.